Show Notes:

Stephan Meier, a professor at Columbia Business School, is the author of the book "Employee Advantage." He teaches the business strategy core class, which is required for all MBA students. Stephan also teaches an elective on the future of work, focusing on how treating employees and labor interacts with technology and business strategy. Stephan conducts international trips to African countries, such as Ghana, South Africa, and Kenya, to provide students with international experiences and perspectives on businesses, strategy, and different environments. His focus is on putting workers first to help businesses thrive.

The conversation turns to Stephan’s book and the concept of the workplace and business strategy. He mentions how the pandemic brought the workplace under the spotlight and technology use ramped up, while at the same time, Stephan was teaching a class on the Future of Work. The conversation turns to the concept of putting workers first as a key element of business success, and how the business language reveals the mode of managing the employee base. This outlook has led to a large divide between employee and employer. According to Gallup surveys, about 65% of Americans are not engaged at work, and this number is even higher worldwide. Stephan also talks about customer centricity and how employee experience is crucial for both innovation and customer satisfaction.

The Employee First Approach

Stephan cites Jeff Bezos, and Amazon as examples of organizations that prioritize employee satisfaction. Amazon's CEO Jeff Bezos believes that learning from dissatisfied employees can lead to continuous improvement and better business outcomes. This mindset is also seen in other industries, such as Costco in the US, which provides clear career paths, communicates clearly, and promotes internally. DHL Express, for two years in a row, was named the best employer in the world on the best workplaces in the world list for two consecutive years. They put employees first because they realized that turnover is terrible and happy employees are more engaged and leads to satisfied customers. They changed aspects of communication, listening, training, and career path within the organization, leading to financial success.

How the Employee/Customer Centric Approach Wins

Stephan discusses the importance of treating employees well and putting them first at the margin when making trade-offs. He talks about Starbucks, where the company's customer-centric approach has led to a loss of a customer-centric environment. He talks about how this could be improved. Stephan also emphasizes that both customers and employees are critical stakeholders that create value within the organization. Companies that prioritize their employees are more likely to be successful. This is because they have a strong focus on competence, which is encouraged by offering the right tasks that push employees optimally. This is crucial for motivation and retention, as people often leave organizations when they don't learn anything new.

How Successful Companies Prioritize Employees

Stephan states that companies strive to differentiate through a customer-centric approach, but he goes on to explain that the employee-centric and the customer-centric approach are often interchangeable. He offers examples of companies that prioritize their employees including Costco, DHL Express, and MasterCard. Microsoft uses an AI-powered tool called Unlocked, which allows employees to choose projects they want to participate in and matches them with opportunities within the company. This approach not only improves the internal market but also creates a better experience for employees. Companies like KKR, which invest heavily in portfolio companies, implement ownership programs, which give employees stock options as a start. To differentiate between companies that prioritize their employees, companies should consider metrics such as engagement level and turnover rates. By focusing on these early indicators, companies can better understand their commitment to their employees and work towards creating a healthy workplace culture that leads to productive and engaged workers.

How to Build an Employee-centric Workplace

Stephan suggests that companies should start by focusing on what they do with customers and how they do it with employees. They can use ideation workshops to understand customer needs and differentiate themselves from competitors. For example, Eli Lilly applied customer journeys to employees, focusing on their experiences and moments that matter. This approach helped them get more people promoted and had a significant impact on their business. Stephan recommends designing workshops to help employees think about ideas and motivations, as well as redesigning processes and procedures within the organization. By doing so, companies can better understand their employees' needs and preferences, leading to a more engaged, productive, and innovative workforce.

Timestamps:

04:09: Development of The Employee Advantage

04:29: Counterintuitive Claims and Examples of Employee-Centric Companies 

12:29: Balancing Employee and Customer Centricity 

15:01: Practical Examples of Employee-Centric Companies 

19:44: Criteria for Identifying Employee-Centric Companies 

23:23: Industry-Specific Considerations 

27:30: Consulting Approach for Implementing Employee-Centric Strategies 

Links:

Website: https://www.stephanmeier.com/

Stephan’s Book: The Employee Advantage

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes:

Dori Yona, founder of Simple Closure, explains the process of shutting down a company. The process is painful, manual, and bureaucratic, with an average time of nine to 12 months. It can cost companies thousands of dollars or even hundreds of thousands of dollars in fees. Many companies end up doing it incorrectly, leading to fines and penalties.

The Multiple Moving Parts of a Business Shut Down

Dori explains that the main difficulty in shutting down a company is the coordination of multiple moving parts, such as the state of incorporation, IRS, lawyers, accountants, payroll provider, vendors, service providers, investors, payroll, and state departments. The average shutdown for a venture-backed company has about 95 moving parts, and if any of them are missed or not done correctly, the process can drag on and on.

First Steps in Shutting Down a Business

Dori talks about three typical approaches for a shutdown of a firm, which they categorize into three main “buckets”.  The first bucket is companies that reach out six to nine months before they need to shut down, as they are running out of cash and trying to raise another round or convince existing investors to invest more in their company. They want to be ready for what happens if it doesn't work out, so they reach out to the Simple Closure six months before to discover what the process involves. Dori mentions the Shut Down calculator his firm developed and put on their website to help business owners work through costs and assess the time they have left before going into the red and complicating the shut down. Bucket number two is when companies decide to shut down immediately, need quick media advice, need help presenting to the board, or with winding down the business. Bucket number three is when companies have shut down operationally six months or a year ago but never dealt with properly winding down the business. They may face penalties, fines, and liens on their personal property due to improper actions.

The Financial Reality of Shutting Down a Business

Dori emphasizes that it is not easy to walk away from a company, as it can come back and haunt the owner(s). He explains that while a corporate entity is there to protect board members, investors, and founders,  if certain things are not done properly, it can pierce the corporate veil, making the board and founders personally liable and potentially sued. The most common issue is wages, where an employee is owed wages and has not been paid. Companies should make sure that the proper winding up process is done to avoid loose ends and potential lawsuits from stakeholders, such as vendors, investors, state departments, and payroll departments. Dori also stresses the importance of considering investors during the shutdown process.

Payroll Providers and the Shut Down Process 

A company's shutdown process involves understanding the number of employees it has and how to properly shut down them. Dori uses a typical seed stage company as an example. This type of company usually has around 15 to 20 employees at its peak, with a few founders and one more engineer or person. To properly shut down the company, it is crucial to know who is currently on payroll, whether full-time or contractors, and how many employees the company had at its peak across different states and locations. Most startups use payroll providers, but they are not good at shutting down payroll accounts. When a company shuts down, they terminate the relationship between themselves and the payroll provider, this does not mean the payroll provider has closed down all accounts in all states. To help close out all accounts and notify all states, companies should ask for the HRIS census, which provides background and history of employees. Analyzing this data helps determine who is a past employee versus an active employee. The discussion explores the issue of 1099s for companies that are about to shut down, such as those in the US. Dori explains that the ultimate goal is to close out all accounts and notify all states, as every state operates differently and how to shut down accounts for active and non-active employees, and contractors.

Technology that Automates and Scales the Shutdown Process

The goal of Dori’s company is to build a technology solution to automate and scale the process of closing out payroll departments. The company aims to be the TurboTax shutting down platform, providing a platform for companies to easily close out their payroll departments. He mentions that the company has built automations to automate various processes, such as faxes, phone calls, emails, and online forms. However, there are many AI solutions available today, such as outbound SDR and AI calls that can call in and provide basic account information. The company's goal is to develop a platform that allows companies to easily close out their payroll departments and help streamline and automate the process. Dori also talks about shutting down repeat services such as subscriptions. 

Three Main Phases of a Company Shut Down

The winding down of a company involves three main phases: dissolution, wind up, and shut down. In Delaware, the first phase involves notifying the state and other entities, such as shareholders, board, and employees, about the decision to shut down the company. This involves notifying the state, preparing franchise taxes, filing the certificate of dissolution, and canceling the EIN. The second phase is the winding up phase, which involves unwinding payroll, paying out vendors, collecting invoices, and dealing with accounts receivable and payable. After the dissolution phase, the company must file a final tax return, distribute any remaining money to investors or creditors, and close out bank accounts. The third phase is the shutdown phase, which involves closing out bank accounts and sending out certificates of closure to investors and shareholders. It's important to have an export of all contracts with vendors and understand their options for cancellation. This process depends on the type of vendor and the company's capital. Dori shares information on how to deal with vendors during the shut down process.

The Legal Requirements of Data Retention 

The conversation turns to the importance of data retention and the value of company data and IP. Dori talks about the importance of understanding the industry and company type, such as healthcare companies needing to keep patient records for seven years post-shutdown. Dori recommends using data custodians to store these records in a safe place, adhering to protocols and encryption levels. He also discusses the need for tokenization around the store to ensure a safe and secure process. On the IP side, Dori explains how founders can monetize their IP after the company shuts down. Delaware law states that winding down the business should maximize value for shareholders, as it is the shareholders' company. They can either acquire the IP or sell it, depending on the situation. They also support the process of repurposing IP, which can take various forms, such as acquiring a domain or selling the domain. Overall, the conversation highlights the importance of considering the legal requirements and the value of IP in the business world.

Sale of Data during a Business Shut Down

The discussion revolves around the process of closing a company, including the sale of data, intellectual property, patents, and code base. A platform called Simple Closing offers buyers to buy assets of companies shutting down, making the process as simple and streamlined as possible. Tax reporting and other tasks are prepaid by the accountant or accounting firm, but the final stage involves closing the bank account, paying off vendors, and sending out final checks to investors.The final stage involves record retention, notifying the IRS about the shutdown, and distributing funds to investors. This process is methodical and involves a waterfall calculation to determine the amount each person should receive back. This calculation is done on a pro rata basis, and after paying all taxes and closing the company, the money is wired out and distributed back to investors.

The Final Stage of a Company Shut Down

The final stage involves closing the bank account, paying off vendors, and sending out final checks to investors, record retention, payment of vendors, and distribution of funds. The final stage involves tying up loose ends and ensuring accurate distribution of funds to investors. Dori explains the process of closing a business, particularly when it comes to payroll, and the challenges faced by founders, such as filing quarterly taxes and dealing with payroll issues. He also talks about the importance of estimating the involvement and duration of founders, such as prepaying themselves with severance packages or bulk sums and why waterfall calculations must be done and how they work. 

The Simple Closure Company Explained

Dori talks about Simple Closure, an online platform that helps founders and operators in the unfortunate position of wanting to shut down their firm. Their mission is not to shut down companies, but to help founders and operators have the peace of mind to move on to what's next. They believe that entrepreneurship is a community of repeat founders and businesses, and the faster they can get founders back on their feet, the more mind space they can give them to build and find their next job. He shares his company's go-to market, which includes referrals from venture-backed firms or inbounds from their website. He explains that they invest in partnerships to meet customers at the right moment in time and build trust with them. The company aims to partner with companies, firms, or entities, such as venture-backed firms, to help them navigate the process and ensure their brand reputation is built.

Timestamps:

02:49: Overview of Shutdown Process 

05:42: Handling Payroll and Employee Wages 

19:28: Wind-Up Phase and Vendor Management 

27:36: Data and Intellectual Property Management 

31:53: Final Stages and Distribution of Funds 

38:44: Go-to-Market Strategy and Pricing 

Link:

Company website: simpleclosure.com

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes

Jacob Bank, founder and CEO of Relay.App, talks about the rise of AI agents, a type of chatbot that can work on your behalf in the background. He explains that AI agents can perform tasks similar to junior-level employees or interns. 

How AI Agents Work

An example of an AI agent working on your blog post is Chat GPT, which can automatically draft a blog post about a new recipe. The agent may ask for feedback and then publish it for you. This makes AI agents less of a thought prompt partner and more like an intern who takes on a mission on your behalf. There are two ways AI agents can take action on your behalf: making direct computer calls called API calls, or controlling your computer. API calls allow agents to make direct connections with tools like Salesforce, Calendly, Microsoft Teams, Google Calendar, and HubSpot. The second approach involves the AI controlling your computer, i.e., constantly looking at the screen and clicking buttons on it. Relay.App focuses on business productivity applications and automated calls, so it cannot log into your bank and perform actions on your behalf. However, a tool using the computer use capability would need two factor authentication and captcha.

AI Agent Interaction: Solutions and Problems

AI agents can interact with any website or tool that has an API, such as email browsers, CRM systems, and business productivity tools. There are three categories of AI agents: APIs, which perform tasks on a computer screen, AI in-built capabilities, and capabilities in reasoning. One problem AI agents need to solve is how they interact with their tools, such as reading and writing data from Salesforce, and how they can do this either via an API or by controlling the browser. Additionally, AI agents have the ability to extract information from PDFs, translate language information, turn text to speech, create videos automatically, and browse the web and do research.

Three Models of AI Agents

There are three models of AI agents to keep in mind: one class is a tool like relay.app, where the tool comes on your cloud or services, and interacts with things, while another class is a tool owned by the customer or freelancing agents. Models to consider when building AI agents: pre-built AI agents, which are commonly used in customer support tools, custom AI agents, and freelancing agents. These models are designed for specific vertical use cases and can be hosted on a platform or servers. AI agents can interact with various tools and platforms, including email marketing tools, CRM systems, and cloud-based versions of Microsoft tools. They can also perform tasks such as transcription, summary notes, and internet research.

Customer Service Agents

Customer service agents can be trained on a company's knowledge base. These agents can take various actions, such as replying to emails, triggering password reset emails, or issuing refunds. There are three main types of customer support agents: pre-built agents for specific use cases, custom built agents on easy-to-use platforms like lyndee.ai, relevance.ai, and Zapier, and engineers building their own agents using developer-focused frameworks. There are two options for building agents: one that interacts with APIs, and another that almost takes over your desktop. The fully browser-based approach is less reliable and predictable, but API-based approaches provide clearer guardrails for the agents.

Common Use Cases for Relay.App 

The most common use cases for Relay.app include email handling, calendar management, customer interaction and relationship management, and marketing content creation. Email calendar management involves extracting information from emails, summarizing PDFs, forwarding them to others, drafting or applying to emails, labeling them, and archived emails. Personal productivity use cases involve managing emails, scheduling meetings, and reminding people to RSVP. Customer interaction and relationship management involves researching prospects, sending personalized emails, creating contracts, and reviewing support tickets. Marketing content creation involves creating life cycle marketing campaigns, blog posts, LinkedIn posts, and Twitter posts. These are the big three use cases for AI agents. However, there are also a wide range of businesses with different bespoke use cases, so they can build AI agents to do custom tasks.

AI Agent Meeting Prep

Jacob shares the step-by-step process to using the AI agent. The agent will help prepare for meetings by providing information about the person they are about to meet. The next step is to add a trigger, which is what happens in the outside world that causes the agent to wake up and start working on our behalf. The trigger can be based on an event in an application or on a scheduled basis. In this case, the trigger will be when an event is upcoming in Google Calendar. The agent will then be able to check if any changes in the person's calendar are made and reschedule the meeting. The AI agent will then be able to look at all the meetings that the person has tomorrow, and the time picker will show that the trigger will happen daily at 5pm.

Using AI Agents to Find Events

Jacob introduces a new step in Google Calendar that allows users to find events and filter them based on criteria. The step is set up to find all events that match the specified criteria, such as start time coming after today or before today plus two. If no events are found, the system can either notify the user or continue with the day without meetings. The next step is to use an iterator to iterate over the list of events found in the previous step. The output of one step can be used as input for the next step, as it often references previous information. In this case, the list of events is the list of events found in the previous step.

Using AI Judgement

To use AI judgement, Jacob adds a step to an AI step, selecting Custom Prompt. This prompts the AI to provide detailed instructions and insert relevant data for context. For example, if everyone has responded to a meeting, Jacob sends an email stating "looking forward to seeing you tomorrow" and if not, an email asking if the meeting still works for everyone. A path is created, which allows the user to decide whether to proceed with the AI's task. The first branch of the path is everyone replied, where the user can choose which rules determine whether to go down that path. In this case, the user selects "everybody replied," which will send an email to the list of guests, stating "looking forward to seeing you tomorrow." The email can be written manually or sent by the user.

AI Agents' Primary Target Audience

The primary target audience is non-technical individuals who have never written code or used code tools. The goal is to make the product easy for everyone to use. The company offers a partner program with automation and AI experts and agencies to help businesses set up workflows or advise on AI usage. Jacob also provides YouTube tutorials that can be helpful for creating workflows. Once people watch tutorials and follow them, they can understand the process at each step. The hope is that everyone can create their own workflows without needing a partner. However, complex business needs may require assistance.The goal is to make the product accessible to everyone, regardless of their technical skills. The company also offers a partner program with automation and AI experts to help businesses set up workflows and advise on AI usage.

Relay.App Pricing

The pricing of the tool is a standard self-serve freemium model, with subscriptions based on how much users use the product. The free tier offers 200 steps and 500 AI credits, while the first paid tier is $9 a month, which includes more steps and AI credits. The team tier starts at $59 a month for companies using it with multiple people. As users use the tool more, it needs more steps and AI reasoning. Bundles of credits are available on top of the subscriptions.The typical cost for a typical business is between $100 and $200 a month. However, if users are getting value from the product, they will pay $100 to $200 a month. 

Finding Talent with Relay.App

On the Relay.App website, which features a gallery of common use cases, such as competitive research, pre-meeting dossiers, and email extracting. The app also includes a human-in-the-loop step where users can ask for help in identifying the right profile based on their information. This human-led approach can help AI agents make more informed decisions and ensure the effectiveness of their work. The app also includes a human-in-the-loop step, allowing users to identify the most suitable profile based on their information. 

Timestamps:

03:12: Capabilities and Limitations of AI Agents 

10:01: Interaction Models and Use Cases 

14:13: Building an AI Agent: Step-by-Step 

29:56: Advanced Features and Customization 

31:25: Pricing and Availability 

33:33: LinkedIn Profile Finder Use Case 

38:02: Conclusion and Resources

Link:

Company website: https://www.relay.app/

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Nikola Lazarov is the co-founder and CEO of Eilla AI, a tool that provides AI workers for private market intelligence. Nikola is an AI engineer who started his career at a London-based hedge fund, Marble Bar Asset Management, where he worked as a quant. He realized the value of AI in structuring unstructured data for private companies and decided to start a company almost three years ago.

What Eilla AI Does

While Nikola mentions that their target clients are investors and investment bankers, Eilla AI's tool does various tasks, such as finding competitors, analyzing their USP, target market, and financials. It also offers a solution for finding comparable transactions and conducting valuation reports. By searching for similar companies, it can determine their multiples, revenues, and valuations. The tool collects data from various data providers, including CrunchBase Zero and PitchBook, and scrapes it on its own. One of the most exciting solutions offered by Eilla AI is finding comparable transactions and doing valuation reports. This involves finding similar companies, analyzing their financials, average multiples, and what is driving these valuations. The tool automatically gathers and compares the data, providing valuable insights for startups, investors, and investment bankers.

How Eilla AI Works

The conversation turns to how it works. Nikola talks through using the software and explains the visuals on the screen, which includes tabs such as company, profile, competitor, research, buyer, selection, investment highlights, key questions, risks and mitigates, and a one-pager. The company profile page provides a consolidated set of information about the company, including its headquarters location, number of employees, founding status, total raised, and last transaction. The company description, industry, problem solved, key team members, funding, product, clients, business model, digital intelligence, and news are all included. The platform is similar to CrunchBase and other data aggregators, but it aggregates data from various sources, such as LinkedIn, their website, CrunchBase, and Capita. The platform also offers footnotes for each piece of data, allowing users to hover over it to see the source of the information. The platform also provides information on the website traffic, such as the source and the number of followers.

Aggregating Data from Various Sources

Nikola explains how the tool works using competitor research as the example to find the closest competitors to Pay Hawk. He explains that this process saves time and helps save time by aggregating data.  However, what differentiates Eilla AI is what happens on top of this aggregated data. It uses a proprietary database of in-depth product information to gather information from over 7 million companies, ranking them based on funding, cat count, and other factors. AI is used to determine the number of competitors and similar companies. 

A Vertical View of Information

Users can select a few companies to dive deeper into, and a vertical view allows for a comparison table. The table includes company name type, description, product description, headquarters location, team, year of founding, last round of funding, status, ownership status, detailed offering, unique selling proposition, and target market. The information is organized in a way that would take weeks to pull together. Users can use the vertical view to see the companies side by side. The platform also includes green dots on product descriptions to indicate high similarity and source information. This tool is unique in that it not only provides data but also replicates the workflow of competitor research. It offers insights such as a SWOT analysis on the strengths, weaknesses, opportunities, and threats of Pay Hawk versus its competitors.

Product and Services

The platform also includes a Products and Services tab with bullet points around PayHawk versus its competitors. Each product has a footnote where users can click to see the sources and scroll down to understand the differences between the two companies. Nikola also mentions the upcoming release of Cap IQ Financial, which includes important information like revenue, beta, valuation, and financials. The buyer selection tab is particularly interesting, as it shows all similar companies to Payco, including acquisitions and mergers. These companies are split into potential strategic buyers, competitors, and financial buyers. The tool also highlights the similarities between Pay Hawk and other companies, such as Visma and Instant, a platform that automates control for secure payments and trustworthy suppliers. The platform also assesses the financial capabilities of the company to buy companies like Pay Hawk.

Eilla AI Features Eilla AI 

Nikola explains that the platform aims to replicate the workflow of investors and investment bankers by breaking down complex workflows into simpler steps. This is done by breaking down data from various sources, such as data providers, CRMs, emails, and nodes. The goal is to provide a comprehensive overview of the company's funding, team, head count, product, services, USP, and detailed offering. The platform also offers a one-pager, which can be easily downloaded and viewed as a PDF. This information provides a detailed overview of the company's funding, team, head count, product, and services, as well as its unique selling points. The platform also provides a free seven-day trial for potential customers, such as corporate executives or business consultants looking for acquisitions.

Eilla AI Pricing Schedule

The pricing schedule is based on the number of requests per user and the amount of time spent on due diligence. For larger companies, the standard price is $98 per month per seat, while for smaller companies, it is $300 per month per user. The platform also offers a free seven-day trial for those interested in trying out the product without the need for sales meetings.

Timestamps:

02:38: Overview of Eilla AI’s Services 

04:46: Demonstration of Eilla AI’s Capabilities 

09:50: Competitor Research and Insights 

16:08: Buyer Selection and Investment Highlights 

20:18: Key Questions and Risks Mitigation 

22:09: Customer Base and Pricing 

24:50: Conclusion and Next Steps 

Links:

https://Eilla.ai

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Jeff Sinclair, a senior global leader at McKinsey, discusses the history of operations at the firm. The firm was initially known as a strategy firm and did some organization and marketing work. However, in the 1980s, clients began to draw more attention to operations, particularly in the automotive industry in Europe and North America. Operations became a strategic function for automotive OEMs and part suppliers, as they needed to serve their customers with high quality, cost-effective, and operationally effective services.

Operations Practice at McKinsey

When Jeff joined the firm in 1981, there were about 500 people in the firm. Today, it is estimated that there are 40,000 people worldwide. The firm started building its operations capability in the 80s by recruiting people with specific functional expertise, particularly in manufacturing. They started hiring people from Toyota Supplier Support Center, and creating a well-defined career path within the firm, which is the specialist path or expert path. The operations practice was at the leading edge of other functional practices, such as marketing, market research, and organization. However, the firm had to create new career paths, which led to many iterations of the expert path. The firm had to continuously improve how it recognized and understood their contributions beyond the traditional generalist path.

Bureaucratic Maneuvering in Creating a Career Path

Jeff discusses the transition from a strong culture to multiple career paths within McKinsey. He explains that this change took about 18 years and was driven by the firm's strong culture and the willingness of senior partners in positions of power to help navigate the new path. As employees advanced in the firm, they had to develop relationships with senior executives, which led to ongoing opportunities to serve them. This made it difficult for experts to fit in and develop new service lines and ways of thinking about problem-solving. The firm struggled to recognize the contribution of subject matter expertise to their ability to serve clients and give them credit for developing new service lines and ways of helping clients execute more effectively. Experts were used on projects in a mixture of subject matter expertise, consulting  director roles, and full-time execution people. 

The Evolution of Consultants at McKinsey 

The firm gave some of the personnel role responsibility to the functional practices themselves, hiring lean manufacturing or supply chain experts into the practice. They would take over the personnel development role, evaluation of performance, counseling, and coaching on how to evolve these new career paths. Over time, the firm recognized the high value added contribution of functional practices and expanded its service to clients. While there is still a tension between generalist and specialist paths within McKinsey today, it has improved significantly. Bob Sternfels, the managing director of the firm, was a functional practice leader who recognized the level of contribution of functional practices and grew the career path within the firm.

McKinsey’s Expansion into other Industries

The firm's operations practice evolved from a dominant career path of the generalist partner to a more diverse range of ways of delivering value for clients. The firm initially faced resistance from some office leaders who believed that the new approach would lead to professional suicide. However, over time, the firm embraced the idea of having multiple functional practices, including the operations practice. In the 90s, McKinsey expanded its service to healthcare providers, which led to the growth of the operations practice. This led to the development of Lean principles, such as the Toyota Production System, which were applied in various industries, such as healthcare, consumer goods, and banking. These principles allowed the firm to create real value in areas where people didn't expect it. One example of this transformation is the expansion of the healthcare practice into other industries, such as consumer goods and banking. This allowed the firm to draw in functional expertise from other industries, such as manufacturing and supply chain management, which allowed them to create real value in these areas.

The McKinsey Impact 

Jeff talks about the impact of McKinsey's operations practice on various industries in America. McKinsey has contributed to changes in healthcare operating theaters and hospitals, and even hospitals that didn't work with McKinsey may have learned from their projects. Jeff emphasizes the importance of a partnership within the firm, as it takes many people to make things happen. He believes that McKinsey's strengths lie in its ability to nurture the capability to grow and work with industry practices to deliver functional capabilities to clients. 

The McKinsey Framework

The firm organized itself to develop partnerships with industry practices and work in the wholesale fashion, and working in the retail side of the firm for example. They continuously invested in new knowledge, both bringing in established knowledge and developing their own. They also worked on career paths and managed practices and enterprise, creating a four-part framework of client knowledge, people, and infrastructure to build a practice. This framework was explicitly managed through the 90s and 2000s to create functional practices as legitimate entities in parallel with offices and industry practices, ensuring co-equalization between industry practice and functional practice.

Building Manufacturing Capability

Jeff shares his experiences with building manufacturing capability in a company. He partnered with Felix Brooke to understand and codify the technical, management, and people leadership systems that drive performance transformation. This expanded to include processes in healthcare and banking. Jeff also discusses the importance of understanding the current state of operational capability in an organization and applying Lean thinking at the overall organizational culture and capability building level. Jeff also emphasizes the need to invest in understanding how to design the operating and management systems, train people, build capability, and use pilot projects to demonstrate their effectiveness.

Investment in Knowledge Project Work

The conversation turns to the firm's investment in knowledge project work, which includes research and application engineering. McKinsey excels at translating various theories into service delivery capability service lines for clients. The firm invests a significant amount every year, spending more than the top five business schools combined on research and development of new service lines. They sponsor projects across multiple functional practices, including operations practice, to take their current knowledge to the next level and serve clients more effectively.

Capability Building and Transformation

McKinsey has developed a network of model factories around the world for capability building and transformation in manufacturing operations. The model factories are physical locations where McKinsey teams can bring client people in and train them in a simulated environment. The firm recognized that training for capability building in many organizations was weak. They formed teams around the world to identify the modules that people need to learn, such as lean principles, rapid change over stamping operations, pull scheduling, and the Kanban methodology. They codified and made tangible the processes. Over time, they accumulated multiple projects and started building knowledge outside of the manufacturing operation. To provide client training, the firm built multiple factories around the world. The first model factory was started in Germany. These small model factories were 15 to 20,000 square feet with real operations within them. These models helped with client training. The model factories were designed to provide a realistic experience for clients and to help clients learn and adapt to the changing needs of their operations.

On Building a Practice

Jeff helped launch a practice that focused on understanding customer value and defining functional specifications. This practice, which involves working with companies to define customer value, translates these requirements into functional specifications, which then translates into technical specifications that translates into the work that is being done. The practice evolved from helping clients drive growth in a market with potential opportunities. Jeff learned how to do this by working with people who knew how to do things like functional discovery and functional specification development. This led to the development of various product development programs, including consumer products, high tech, and healthcare. The practice began in traditional industries like automotive, industrial, and electronics but expanded to areas like consumer products, high tech, and healthcare. 

Product Development Practice

In the product development practice, some classic project types include product platforming, product development roadmaps, and product teardown projects. These projects help identify market applicability, customer needs, and the platform that needs to be put in place to have a range of product capability. By understanding how to think about the platform from both a hardware and software point of view, the product development roadmap can be managed to get products to market faster, with each product being cheaper to produce and having a competitive price point. Jeff shares one example of a project that was involved in a major acquisition included doing a product platforming strategy and a product development roadmap. This helped identify the range of market applicability, customer needs, and the platform that needs to be put in place to maximize the amount of commonality across the product line. By understanding how to think about the platform from both a hardware and software point of view, the product development roadmap could be managed in a way that got the product to market faster. Jeff also talks about reverse engineering. 

Current Positions and Interests

Jeff has been teaching at the University of Michigan, focusing on business and customer discovery. He teaches engineers that their designs need to be able to meet customer needs and be willing to pay for them. He also works with undergraduates in a consulting class at the business school, helping them develop turnaround strategies for companies in the avionics business. Jeff is an adjunct faculty member and has been doing this for about a dozen years. He is also involved in a startup consulting effort with his son, who worked for a small boutique firm called Magnet, which focuses on serving smaller companies, and he is an investor in various small, private equity owned and startup companies.

Timestamps:

03:39: Building Operations Capability in the 1980s 

07:45: Challenges in Creating Career Paths for Experts 

09:55: Role of Experts in Projects 

12:10: Evolution of Career Paths in the 1990s 

17:10: Impact of Operations Practice on Industry Practices 

31:36: Knowledge Initiatives and Model Factories 

36:31: Product Development Practice 

43:34: Reverse Engineering Projects 

Links:

Company website: https://shorewaypartners.com/

LinkedIn: https://www.linkedin.com/in/jeff-sinclair-87a7392b/

Michigan Ross: https://michiganross.umich.edu/faculty-research/faculty/jeff-sinclair

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes:

Anne-Laure Le Cunff, author of Tiny Experiments and founder of Ness Labs, shares her approach to understanding her own life and why she does things the way she does. Anne-Laure explains that self anthropology is a powerful tool for problem-solvers and doers to understand their own lives and prioritize their priorities. By embracing uncertainty and turning it into curiosity, individuals can overcome procrastination and achieve more in their lives. She emphasizes the importance of self-anthropology in helping people become anthropologists of their own lives by observing themselves throughout their daily lives and asking themselves why they are doing things the way they do. This allows them to understand what is happening right now before planning for the future.

Overcoming Procrastination with Curiosity

One example of how self-anthropology can be applied to procrastination is by focusing on the problem with curiosity rather than trying to beat it. Procrastination is often seen as a signal from the brain and body that something is not working for you right now. By approaching procrastination from a place of curiosity, individuals can learn useful things from it. By identifying the problem, learning more about it, addressing it constructively, and seeking mentorship, coaching, and the right tools, individuals can design tasks in a more fun and enjoyable way. This approach allows individuals to move forward and get unstuck from the pressure to beat the problem. Anne-Laure explains that self-anthropology is a powerful tool for problem-solvers and doers to understand their own lives and prioritize their priorities. By embracing uncertainty and turning it into curiosity, individuals can overcome procrastination and achieve more in their lives.

A Framework for Overcoming Procrastination

The conversation turns to the effectiveness of a framework that treats procrastination with empathy, and overcoming procrastination by asking questions and experimenting with different approaches. This approach can be applied to various challenges, such as managing anger, managing health, and examining patterns in emotions and anxiety. Journaling is a great tool for reflecting on experiences and understanding the root causes of issues. Journaling is a mindfulness practice that allows for non-judgmental observation and self-anthropology. By taking notes about thoughts, emotions, and behavioral patterns, one can ask questions about why they happen, what could be different, and what new approaches or ideas could be explored. Regular reviews of journal entries can help identify patterns and changes in one's life, which can help in dealing with challenges in the present moment and providing material for future reflection.

Tiny Experiments and Atomic Habits

Anne-Laure discusses the concept of making PACTs and how they can be used in conjunction with habits. PACT stands for Purposeful, Actionable, Continuous, and Trackable and they work well with habits.  Atomic habits involve building habits by making tiny experiments with specific durations and outcomes. A tiny experiment is a type of PACT that involves choosing one action and a specific duration to collect data. The main difference between a tiny experiment and an atomic habit is that the experimenter withholds judgment until the data is collected, allowing them to decide if the habit is beneficial or not. The main difference between a tiny experiment and an atomic habit is that the experimenter withholds judgment until the data is collected. This allows them to determine if the habit is beneficial and if it is something they want to continue with in the future. Anne-Laure also discusses the importance of reflection in small experiments, as it helps individuals identify what they enjoy and what they should continue with.  Anne-Laure suggests aligning the data with the measures of success at the end. She suggests tracking internal and external signals, such as mood, heart rate variability, stress, or sleep score, and collecting quantitative data through journaling.

The Power of Learning in Public

Anne-Laure also emphasizes the importance of learning in public, such as announcing the experiment to others and building accountability. This can be done through social media, WhatsApp groups, or even with a few friends, or even just one accountability factor. She stresses remembering that dips in motivation are also important signals. If you notice procrastination or dreading, you can observe those responses and behaviors and try different things the next day. She explains how to keep going, noting any days where you missed it, and then trying something different the day after. If you find yourself bored or unable to stick with the experiment, you can either pause it and go back to designing a different version or consider that you have collected all the necessary data for one version. Additionally, success for an experiment is learned even if it is discarded, as it has allowed you to learn that it is not a direction you want to follow.

Greek Concepts of Time and a Shift in Perception

Anne-Laure Le Cunff discusses ancient Greek concepts of time, Chronos and Kairos. Chronos is the quantitative approach to time, where every minute is an identical box that needs to be filled efficiently. Kairos, on the other hand, is a qualitative approach that recognizes that time is elastic and each moment is unique and has a special quality. This approach is crucial in decision-making in daily life and work, as it embraces losing a sense of quantitative time, allowing deeper flow in projects. Anne-Laure goes on to talk about generativity, which is about focusing on the impact one can have today on others, rather than building something that will be forgotten after one or two generations. This approach aligns with an experimental mindset, as it allows for better understanding of what works and what doesn't, and allows for adjustments to be made in the present moment. She mentions her PhD research in ADHD and how it inspired her to adopt an experimental mindset and scientific method. She learned that success is not about getting to a specific destination but about learning something new. By applying this approach to her daily life and work, she noticed more progress without clinging to linear goals.

A Community for Curious Individuals

Ness Labs is an online community created by Anne-Laure. The community initially started as a newsletter, where she would translate concepts into practical applications for daily life. However, during the pandemic, people felt lonely and missed the opportunity to connect with others. Anne-Laure decided to create an online community for curious individuals who enjoyed discussing topics in her newsletter. The community allows anyone to host workshops, especially those still in the process of learning, and run Tiny Experiments together. During the pandemic, the community hosted events on various topics, such as meditation, creative collages, mental health, psychosis, psychedelics, and philosophical movements. The community also offered co-working sessions, guided creative exercises, and small experiments. Participants could create a log in the community, taking notes based on their experiments, and receive support from the community. The format includes a mix of Pomodoro sessions, intentions, and conversation, with participants sharing their progress and resources related to their projects. Anne-Laure shares a few examples of sessions and Tiny Experiments within the community and how she chose the design of the cover for her book

Timestamps:

03:30: Explaining Self-Anthropology 

05:40: Addressing Procrastination with Curiosity

10:38: Implementing Self-Anthropology in Journaling 

13:49: Introduction to PACTs (Productive and Curious Trials)

14:04: Collecting Data and Building Discipline for PACTs

23:38: Time Shift from Chronos to Kairos 

26:29: Focusing on Generativity Over Legacy

29:46: Influence of Academic Studies on the Book 

31:33: Introduction to Nest Labs 

36:22: Examples of Community Activities and Personal Experiments 

Links:

Book: TinyExperiments.org

Ness Labs website: https://nesslabs.com/

Anne-Laure Le Cunff website: https://anne-laure.net/

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes:

In this episode of Unleashed, Will Bachman interviews Harsh Sahai, CEO and co-founder of Bridgetown Research, a company that has built an AI tool and he talks about it in this episode. Harsh previously worked at McKinsey, where he focused on commercial due diligence. He also ran a machine learning lab at Amazon, where they researched sequential decision-making algorithms. 

AI Pricing Algorithms and Convex Optimization

Harsh talks about his work at Amazon where main use cases were pricing products, as people tend to remember old prices and make decisions based on what they remember. For example, planning the sequence in which to launch products or introducing new shows on Prime Video could be done in a multi-step planning process. Harsh talks about his background in convex optimization, which is a mathematical model that can be used to represent various outcomes. Convex optimization is often used to model price versus volume, and it helps in making more sequential decisions for more than just pricing. 

Bridgetown Research Explained

On founding Bridgetown Research, many of Harsh’s former colleagues joined him in the mission to build tools for the consulting industry and more. Bridgetown Research developed a platform that automates data collection and analysis, allowing them to curate these analyses and deliver value to clients. The firm developed software products that can conduct interviews at scale at a fraction of the cost, run 300 common analyses, evaluate approximately 10 decisions, and work alongside clients to build interactive documents. The firm primarily serves investors in the software industry, similar to McKinsey due diligence.

Automating Consulting Groundwork

They use AI agents to conduct interviews, breaking down high-level questions into sub-questions that can be answered by the AI agents. The agents then map the best sources of data for each analyze, such as Gartner or Forrester, and compile secondary research. The AI agents are integrated with a few expert networks, which they recruit on the company’s behalf. They have a fully adaptive conversation, similar to a consultant's conversation, and then parse out the analysis to answer the main questions. The cost of these interviews is lower than a normal human-to-human interview because they can do it on their own schedule. Harsh also discusses the benefits of owning a research platform for consultants. They have researched this topic extensively and have 1000 interview transcripts of both people who hired a consultant and like consultants. The platform offers voice-based conversations, text prompts, and interactive screens for additional context.

Using AI Agents in Surveys

The AI agent in the discussion is similar to a traditional survey, but it allows users to answer questions directly on their screen. It can also embed multiple choice or ranked sorting questions, and can follow a different chain of questioning depending on the user's response. The agent constructs a hypothesis based on secondary research and uses adaptive questions to collect enough data to either prove or disprove these hypotheses. If it disproves the hypotheses, it goes back and looks at all transcripts to come up with new hypotheses and start collecting more data. One of the reasons for the cost efficiency is that, unlike regular surveys, the AI agent doesn't ask the exact same questions, reducing the length by about 20 to 25% once statistical conviction is reached. This flexibility allows for discounts from the person taking the interview, as it's extremely convenient for them.

Examples of AI Agent’s Responsiveness

The agent's responsiveness works by comparing the user's responses to previous answers, such as asking about the main reasons they chose a particular software versus another. The agent then moves on to the next question based on the user's response. Harsh offers a few examples and verifies that the agents have received positive feedback from experts who are willing to interact with the voice agent, but they also interviewed people with slightly different profiles than consultants at McKinsey.

More Information about the AI Tool

The AI tool used in this discussion is a work in progress that aims to provide insights into competitor archetypes and their strategies. It is designed to be more efficient than traditional human interviews, as it can gather data from mid-tenure professionals and frontline users closer to the business operations. This approach allows for a more comprehensive understanding of the business, reducing the need for frequent human interviews. The tool is fully scalable, allowing for 100 interviews in three days, which is the time it takes to recruit individuals rather than the time it takes to interview them. This allows for the creation of compelling projects within a week. Before the interview phase, the AI tool asks a set of questions and breaks them down into sub hypotheses. The tool then constructs sub questions to explain various factors, such as margins, go-to-market channel, and strategy. The tool is capable of explaining up to 200 different factors, making it a versatile tool for analyzing competitor archetypes. It can also provide examples of how to segment competitors and investigate their cost. The tool's output includes eight hypotheses, which can be investigated through secondary research or questionnaires.

Examples of the Tool at Work

The AI tool is largely a work in progress, with multiple steps taken to chase each hypotheses down. The team is working on improving the UI and UX to make the process more tractable. Harsh explains that the sentiment analysis workflow involves a series of custom trained machine learning models that perform various tasks to produce a final output. He gives the example of an agent searching Reddit posts, determining if they are positive, negative, or neutral, and extracting themes from positive quotes. The main model categorizes comments as positive or negative, extracts themes, and summarizes codes by themes. Harsh explains that there can be around 300 analyzes executed by a permutation of 40 fundamental tasks. Another example is analyzing the average case buying process, deviations from the buying process, and key factors considered in decision-making stages. The standard KPC analysis on the platform includes two fine-tuned models: one extracting mentions of keeper Chase criteria across the transcript, and other clustering words to represent different meanings. The third component counts the number of mentions by category, which is the relative importance metric for each key purchase criteria.

Research Completed Before the Interview Stage

The secondary research that the platform performs before the interview stage, such as creating lists of competitors, acquisitions, customers, and suppliers. The platform triggers secondary research by identifying areas of interest and providing cues to help users interact more smartly. For example, when creating a new interview, the platform can identify main competitor types and determine reliable domains for secondary analysis. The tool can create personas of people to chat with, based on their background, geography, work experience, roles, and competitor employees. The platform then generates an interview guide for each segment, which includes text, background checkpoints, and a series of questions for the interviewee to answer. Users can edit these questions or add more options. The platform also provides a multiple choice option for users to choose from blank solution providers. The platform also offers an estimate of how long it would take for the person to fill out the survey, allowing users to save time and edit questions. The platform then prepares a granular set of hypotheses for each question, breaking them down and collecting data to either prove or disprove them. This process is similar to machine learning, where the information provided by the respondent validates or invalidates the hypotheses.

The Future of AI Tools and Human Consultants

Harsh shows a more manual flow where users can have full control over each step and explains how it works. The role of human consultants in the future is becoming increasingly important as AI tools become more prevalent. Three main factors drive clients' assessments of a consultant's contribution: experience, expertise, authority, credibility, and connections across the organization. These factors are fundamentally human and hard to replace. The tasks of early and mid-term consultants will shift from writing interview guides or conducting interviews to using AI tools or competitors. They will need to master these tools and learn how to review, approve, or edit the interview guide, synthesize the results, and make judgments about the quality of the results. 

Bridgetown Research and the AI Tool

The main business for the tool is providing customized versions of the tool to clients, catering to their specific analysis needs. However, there is a long wait list for users of the common platform, and one of the goals for 2025 is to onboard small to mid-sized consulting firms to use the product hosted by the firm without modification and see if they like it. Private equity investors are using Bridgetown Research's tool to conduct their own research, generating results directly without hiring consultants. The tool is cost-effective and provides a 60-70% answer without much effort. Investors typically hire consulting firms when they have a high degree of conviction to invest, but they are now using the platform for any deal they come across. The marginal cost is practically zero, making it a rational choice to use the platform for early stages of the deal pipeline. The platform is also available for use with investment professionals, consultants, and other professional services.

Timestamps:

04:17: Explanation of Convex Optimization 

06:53: Overview of Bridgetown Research's Platform 

09:06: Details of AI Interview Process

13:59: Examples of AI Interview Questions and Responses

19:51: Feedback and Adoption of AI Interviews 

23:22: Secondary Research and Hypothesis Generation

28:08: Examples of AI-Generated Analyzes 

40:26: Customization and Integration with Client Data 

Links:

Website: https://www.bridgetownresearch.org/

LinkedIn: https://www.linkedin.com/company/bridgetownresearch/?originalSubdomain=ca

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes:

Jim Ettamarna, a renowned expert in commercial excellence, defines it as incorporating commercial efficacy and efficiency. He believes that there are two key branches to drive down in this area, and it holds tremendous potential for clients and organizations. Jim's framework for commercial excellence is value creation, which involves understanding market demand, go-to- market models, market growth, and demand trends with a focus on each specific industry.

A Six Sigma Lean Framework

Jim uses a lean framework, starting with Six Sigma, to standardize the right work and ensure associates and employees are conducting the right activities and behaviors. He also emphasizes the importance of systems in psychology in commercial results, as it helps design standardized systems for onboarding talent, enhancing team engagement, and engaging with customers. In sales, motivation is crucial, and the human element of having a team is essential. However, dealing with complex buying processes can be challenging, so it is essential to tune processes and approaches to the specific needs of the customers.

A Go-to-market Model

The go-to-market model is a linkage between strategy and execution and commercial excellence. It should be tuned for the company's strategy and the strategic context. For example, a $300 million middle market private equity-backed company serving the Durable Medical Equipment market that sold to 5,000 independent organizations and specialty retailers. The company had to strategically think through market growth, accounts to capture, and the buying cycle for customers. To drive efficiency and effectiveness, the company had a set of building blocks, including an online component, independent sales reps, an inside sales team, and specialty sales people. The strategy piece involved determining what would drive value, growth, renewals, base volumes, and pricing. The go-to-market model was designed around these building blocks, and commercial excellence was driven by optimizing these aspects.

Components of Commercial Excellence

Jim discusses the importance of breaking down commercial excellence into various components, including channels, sales operations, content, and management systems. He emphasizes the need for segmentation at the top level to understand what will drive value and optimize the go-to-market model for the business. Within this model, he suggests ways to optimize each element, such as sales enablement, which includes training, scripts, and engagement strategies. He also emphasizes the importance of benchmarking and understanding the nuances of sales teams. He shares an example of a furniture retailer where he worked with 2500 full-time employees and 1000 part-time employees. The performance of the company was analyzed using Pareto curves, but some outliers were more successful than averages. To replicate these outliers, he spent time in the field with the best sellers and identified their backgrounds and profiles. He also highlights the importance of identifying B+ and A minus players and setting them as standards. The A plus players are often unique individuals that can be difficult to replicate, but they can still learn from them. Segmentation is crucial in understanding customer nuances.

Value Mapping and Needs-based Segmentation

In the past, value mapping and needs-based segmentation were crucial for designing sales teams and engaging with customers. This was particularly important when selling software into hospital systems, where hospitals may make localized decisions or have a system or GPO that drives these decisions. The CIO or clinical or nursing professional may specify the solution, and the CIO and finance will negotiate it. Jim cites a case where a big client involved segmenting the market and designing selling approaches based on how customers operated and how they bought. This involved investing in customer success research, conducting field interviews, and conducting surveys to understand their usage of the product. The consultant rolled out five archetypes and profiles for four segments, which were then rolled into product development and product teams. Different teams focused on different segments, such as geographic, size, SMB, or enterprise, and focusing on needs-based and purchasing behavior-based segmentation. The go-to-market model was designed around these archetypes, with territory design considering geographic, size, SMB, or enterprise boundaries. There is no right or wrong answer to this, but it is essential to consider these factors when designing the go-to-market model. This approach helps to understand the value in use and what drives value for customers.

Diagnostics and Metrics

The conversation turns to commercial excellence in organizations, particularly in B2B industrial or SaaS sectors. Jim emphasizes the need for a diagnostic assessment to understand opportunities and challenges. A diagnostic should focus on input and output metrics, such as sales reps' success, territories, and numbers. He suggests that data from sales operations and rev ops can be used to conduct quick diagnostics. Additionally, examining spreads and distributions to identify right spots and dark spots, which are indicators of opportunities and challenges. For example, he could work with a labeling client and identify bright spots where individuals were selling unique markets and promoting innovative products. These best practices could be disseminated among the team. A diagnostic should involve analytics, cost, interviews with sales people, and customer visits to gather customer feedback. The goal is to identify three to five things that can be done to achieve commercial excellence. Jim also offers tips on how to work with the sales department. 

The Role of a Sales Playbook in Commercial Excellence

Jim talks about the importance of rolling out a sales playbook and its role in commercial excellence. He shares an example of a software company that he helped develop a sales playbook for, which focused on making standard work and minimizing waste. The company had three different sales processes, and they trained employees on territory management, account management, and prospecting. They created a set of 10 difference makers based on actual activities performed by the best people, which were rolled out in a fun, gamified way to encourage adoption and recognition. Some of the key difference markers included prospecting, owning territory, and using Salesforce to drive compliance. 

Metrics to Monitor in Sales

Jim mentions the importance of having the right input and output metrics, such as the number of meaningful meetings and demonstrations per week, to ensure the right outbound results. By tracking these metrics, the sales team can make necessary adjustments to improve their performance and drive more profitable deals. To drive results in sales, Jim highlights metrics such as deal size, velocity, win rates, attachment, cross, sell, and upsell. He also emphasizes the importance of driving customer success and retention. He mentions that, in one case, key initiatives were displayed at the office, allowing for a competitive dynamic. The metrics were then distilled down to the board, with some metrics for frontline commercial team members and others for the board pack. The goal was to turn the dial on sales enablement, resulting in better win rates and accelerated funnel velocity. Jim also highlights the importance of gamification, making it fun, and rewards to encourage employees to work harder and drive competitive juices. 

Timestamps:

01:32: Value Creation Framework 

04:18: Go-to-Market Model 

07:24: Tangible Elements of Commercial Excellence 

11:10: Segmentation and Customer Nuances

14:18: Practical Segmentation Approach 

18:18: Diagnostic Approach to Commercial Excellence 

24:04: Sales Playbook and Metrics 

29:50: Customer Success and Competitive Dynamics

Links:

Company website: https://www.suttongrowth.com/

LinkedIn: https://linkedin.com/in/jimettamarna

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes:

In this episode of Unleashed, Will Bachman interviews Bart Sayer, an expert on the beauty industry. Bart worked for nine years at the Estée Lauder Companies, most recently as the International General Manager for one of its largest brands, Clinique, managing the $1B P&L. Previously, Bart was a partner at Booz & Company (now Strategy&, part of PwC), focused on strategy and commercial transformation in the Consumer & Retail sectors. The conversation focuses on understanding the structure of the beauty market and the main drivers of value creation.

The Beauty Industry Explained

Bart explains that the beauty industry is divided into four main categories: skincare, makeup, hair, care, and body. The market is divided into luxury and mass segments, with luxury beauty expected to grow between six and 8% in the foreseeable future. Taking the example of the United States, mass brands are more likely to be found in drugstores, such as Walgreens and CVs. Premium brands are more available in department stores or specialty multi, such as Sephora and Ulta, and a third channel being direct to consumer. At Estee Lauder they believed that distribution defines your equity, so prestige brands are careful about where they appear, hence the careful consideration and strict conditions associated with entering a channel like Amazon. Looking beyond the NA market, Travel Retail has been an important growth vehicle for luxury beauty brands over the past decade, though this growth has tempered in the past few years. Future growth of the beauty industry will remain defined by its two largest markets, the United States and China, while up-and-coming middle market countries will also represent attractive opportunities (e.g., India, Mexico, Brazil).

Manufacturing, Testing and Ingredients

The ingredients in mass and prestige products can differ in terms of the scarcity or rarity of the actives, including use of proprietary ingredients and formulations. Formulation philosophies vary widely across different entities. Many brands, for example, put extra protections in place to ensure product safety for sensitive skin and/or to conduct rigorous allergy testing. Bart discusses the importance of clinical testing in product and research development, highlighting that it is a high barrier to entry for indie brands. He also discusses the evolution of more nimble production models, including the prevalence of contract manufacturers that can manufacture the latest ingredients and bespoke formulations in quicker and more cost-effective ways than many of the brands themselves. This approach is not binary, as L'Oreal has over 40 different manufacturing facilities worldwide. Before leaving the manufacturing discussion, Bart quickly hit upon another topic, that of the evolution to more earned media-led marketing models, whereby companies seize organic market buzz before amplifying these messages with paid media.

Local vs. Global Adaptation

The concept of local versus global adaptation is crucial in the beauty industry. Brands must find a locally relevant articulation of their brand essence. Large media companies often have global ambassadors who can speak for the brand, but if a local face is not available, the brand may not get the traction needed. To succeed, brands must be more reactive to local market trends, deploying local influencers, tailored messaging and selecting locally relevant forums for generating PR, both online and offline.

Indie and Newer Brands

The conversation turned to the shift towards indie and newer brands in the beauty retail industry. The reasons behind the growth of the indies include lower barriers to entry on social media channels, an agile marketing model, the wide availability of contract manufacturers, and channel partners like Sephora that are focused on curating exclusive collections of the next “it” beauty brands. Often for these indie brands, the problem is not the launch itself (recruitment), but the stickiness (retention). Many of these companies struggle with repeat purchases, which are the key to success.

Sales and Distribution in the Beauty Industry

Bart discussed several high growth channels, including Sephora, a leading premium beauty retailer owned by the LVMH group, travel retailer and beauty e-tailers such as Zalando and Notino. Traditional points of distribution, such as department stores and perfumeries, have seen slower growth, especially in the West (and far less so in the East). Whatever the channel, the importance of constructing good “self-navigating experience” for prestige consumers is key. Across many of these newer retailers, clean beauty is a key theme, as is green and sustainable, free of parabens, sulfates, certain ingredients and fragrances. This raises the bar for brands to prove their bona fides in terms of ingredient publishing and sourcing. The conversation then pivoted to challenges in the supply chain, including shelf life of products (especially for consumers in the East) and SKU proliferation.

Demand Forecasting

Robust demand forecasting is crucial for brands to succeed to avoid out-of-stock situations and, conversely, the proliferation of excess. This can be particularly problematic when trying to create buzz and excitement with limited edition collections such as those sold over the holidays. Given profit, brand equity and sustainability concerns, rands have increasingly tried to err on the side of caution in their forecasts (FOMO). SKU periphery proliferation is another issue that brands are constantly fighting, seeking a balance between getting new out there while staying consistent and building out their portfolio.

Store Design and Staffing Models

In department stores, cosmetics brands often have significant control over the design of their stores, including all signage, key visuals and other elements of visual merchandising (e.g., gondola design, planogram setup). Done correctly, these can be huge differentiators. Unsurprisingly, prestige beauty brands have armies of store design, visual merchandising and staff (beauty advisor) education teams. Cost sharing with retail partners – CAPEX, staffing, promo – vary by channel and partner, thus representing a critical point in commercial negotiations (along with other topics like trade margin).

The Lucrative Nature of the Beauty Industry 

The cosmetics industry is a highly lucrative business with operating profits ranging from 10 to 25%. Gross margins can be 65% or more, depending on the brand and the type of product. Highest gross margin categories include skincare and luxury fragrances. However, there is no room for complacency, with many waging a constant war to lower the cost of goods through a combination of gross to net improvements, price increases, mix optimization, promo efficiencies and, of course, manufacturing savings. A hero-product focus is needed to get scale, thus providing ballast for marketing investments. Premiumization trade trends are continuing across categories and subcategories, with no sign of these trends abating.

 Timestamps:

03:30: Structure of the Cosmetics Industry and Market Segments

05:26: Specialty Channels and Distribution Strategies 

07:58: Differences Between Mass and Prestige Brands

10:06: Analyzing the Cosmetics Industry: Product and Research Development 

13:44: Marketing and Consumer Insights

18:33: Sales and Distribution Channels

22:49: Operations and Supply Chain 

31:57: Gross Margin Analysis and Financial Performance 

Website Links:

#1, Beauty Market Outlook:

https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/the-beauty-boom-and-beyond-can-the-industry-maintain-its-growth

#2, FDA Regulations of Cosmetics:

https://www.fda.gov/cosmetics/cosmetics-science-research/product-testing-cosmetics

#3, Risk of Indie Beauty Brands:

https://cosmeticsbusiness.com/how-indie-beauty-brands-can-break-america#:~:text=Indie%20brands%20are%20greatly%20influencing,and%20most%20likely%20through%202025.

#4, Beauty and Travel Retail:

https://wwd.com/beauty-industry-news/beauty-features/tackling-beautys-travel-retail-conundrum-estee-lauder-loreal-clarins-bulgari-dfs-heinemann-1236682262/

#5, Green Beauty:

https://www.forbes.com/sites/meimeifox/2023/12/22/green-glamour-12-clean-beauty-brands-leading-the-eco-revolution/

#6, Beauty & Supply Chain Challenges:

https://www.voguebusiness.com/beauty/new-ingredients-higher-prices-reformulating-beauty-in-the-supply-crisis

#7, QVC and Beauty:

https://entm.ag/1wEfOci

#8, Love, Indus (company referenced by Will and I during the discussion):

https://loveindus.com/collections/shop?gad_source=1&gclid=Cj0KCQiAkJO8BhCGARIsAMkswyiVNdA36DRltbku4DqHeLj-dAbZxAfsVOWmkyEP6Ah9bsxaNi3L4g4aAqP4EALw_wcB

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Rob Garmaise, VP of AI research at Info-tech Research Group, is at the forefront of Info-tech research, helping clients identify best practices across their IT operations. They conduct extensive primary and secondary research, speaking with industry experts and other clients to understand the drivers of value and proof that a given practice leads to better results.

AI Vendors, Verticals, and Research Taxonomy

Rob explains that the firm has a vast research taxonomy, with AI being an important part of it. They have a team in place to connect with thought-leading vendors and their leading adopter clients to gather insights on various functions, rules, verticals, and sub-segments where AI is taking root. The strength in the marketplace currently lies in the horizontal focus on functions and roles across organizations rather than the various verticals or lines of business. Most AI vendors aim to maximize their total addressable market which is difficult to do when focusing on just one vertical.

The Market and Vertically-orientated Competitors

Rob predicts that the mix of vertically-oriented competitors will change as the market evolves. Currently, the strength is 80% on functions and roles, 20% on verticals. This approach allows AI vendors to maximize their total addressable market and stay competitive in the market.

In this discussion, Rob discusses the implementation of AI solutions in various functions and roles within companies, including IT. He highlights the strengths in CO generation, data and analytics, service management, HR, sales, and marketing.

AI in HR, Sales and Marketing, and Operations

In HR, AI is being used to improve employee experience by indexing content and interacting with users. Talent acquisition recruiting uses AI on both sides of the recruiting equation, with AI being  used in talent assessment, helping to cut through biases and improve diverse hiring. Sales enablement and sales automation tools are the top lead and revenue-driving categories, while customer experience is the top cost-saving category. Operations are also being explored, with AI parsing information captured from video cameras for various applications such as shop floor settings, retail environments, and restaurants. Natural language conversations with equipment can lead to predictive maintenance, allowing organizations to strategize and optimize operations. Robert goes on to explain more about the improvements made using AI in HR, IT, and sales and management.

AI-based Solutions in the Retail and Insurance Industry

The conversation turns to the use of AI in various industries, including retail, and insurance. In the retail industry, AI-based solutions have impressed with their ability to scan store shelves with smartphones and receive critical metrics like stock availability, pricing, promotion, and competitor positioning. Smart Digital Signage solutions can also be used to adapt to demographics and reactions of customers. In the insurance industry, AI-based solutions include smart digital signage that can adapt to demographics and react to customer reactions. In the insurance industry, AI-based solutions include smart digital signage that can adapt to different demographics and respond to customer needs. Companies are exploring AI solutions to improve employee experience, sales, and marketing, while also focusing on cost-saving and predictive maintenance strategies. Robert discusses the potential benefits of AI in retail, such as real-time reactions to client information, and automated stock out detection.

AI in the Legal and Financial Sectors

In the legal sector, AI is being used for various purposes, including legal research, contract review, and contract management. This is particularly important for law firms and organizations with understaffed legal teams. In manufacturing, AI is being used to offer real-time instructions to machine line operators. Rob talks about disappointments in areas like financial services, healthcare, and government. In financial services, AI is being used for fraud detection, digital trust, and remote inspections. In insurance, AI can parse frequent documents into well-constructed spreadsheets or databases, and can conduct remote inspections. Rob also points out areas of disappointment. 

Advice on Adopting AI 

The conversation turns to the trend of AI being bought rather than built, particularly in the context of AI models. AI should be bought unless a build is absolutely necessary. The build side involves more uncertain investment levels and lead times, as it can lead to app sprawl and uncertainty in the market. Companies are advised to be deliberate about their build decisions, especially when it comes to AI models. On the talent side, companies are hiring new types of Chief AI officers or existing employees, such as Chief Digital Officers, Chief Technology Officers, and Chief Information Officers. These individuals are often left in charge of driving AI forward, but they may not have the necessary skills for building a new and unique model. On the build side, companies may need additional data scientists and data modelers, which can be challenging to achieve. On the consulting side, there is a growing trend of companies using top strategy firms on multiple AI projects. While most clients are still trying to orient themselves, consulting firms can help direct them towards buy-side scenarios where a POC or two can be done without a large implementation. Rob also touches on the importance of understanding the market and the potential benefits of AI solutions.

Timestamps:

03:40: AI Market Insights and Research Methodology 

05:28: Practical AI Applications in IT and Service Management

06:53: AI in HR and Talent Management 

08:11: AI in Sales and Marketing 

09:43: AI in Operations and Predictive Maintenance 

11:31: AI in Retail and Supply Chain 

14:49: AI in Legal and Manufacturing 

17:55: Trends in AI Adoption and Talent Management

22:30: Consulting and AI Marketplace

Links:

Website: https://www.infotech.com/

YouTube: https://www.youtube.com/@InfoTechRG

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.

Show Notes:

Marilyn Lin, a customer support thought leader with over two decades of experience, discusses the importance of customer support in driving business success in the Software as a Service (SaaS) industry. She has led global Technical Support Teams that not only resolve issues but also foster customer loyalty, drive renewals, and inform product strategies. In today's competitive SaaS landscape, customer support is not just a cost center but a linchpin of retention and growth.

Customer Support in the SaaS Industry

The conversation turns to the different terms for customer support, such as customer support, customer service, customer care, and customer success. Marilyn identifies the difference between terms. She equates customer success to the team focused on the health of a customer, focusing on how they are leveraging and using the product and solution, realizing value from their investments. They are more akin to the account management side of the organization, taking care to understand the customer's top priorities and helping guide them through leveraging and using the solution and products they have purchased or subscribed to. She explains that customer support and customer service are terms used interchangeably to describe the teams that help customers resolve issues with using their products or services. In B-to-B environments, customer support are more technical support teams, while customer care and customer service is more tactical and often describe teams within B-to-C environments.

Subcategories within Customer Support

There are different subcategories within customer support, such as onboarding teams, which help new B2B customers onboard with a SaaS company. Major functions  tied to customer support include customer training and onboarding, customer delivery teams, and customer escalation teams. The support delivery team handles cases and interacts with end users, helping them find solutions to their issues. A customer escalation team is involved when customers escalate issues or outages, ensuring timely resolution. Marilyn explains that historically, customer support organizations have been seen as reactive and cost centers rather than a strategic arm. However, there is a treasure trove of insights from the interactions with end users, which can be used to drive improvements in the product and solution. This information can feed into the product development cycle, helping product and engineering teams prioritize their roadmaps and drive the voice of the customer. Support teams can also provide insights related to training and enablement, usability, and user experience, which can be shared with the enablement and design teams.

The Importance of Customer Support in Business

The importance of customer support in a business is discussed, including the need for analytics to understand the impact of the customer support team and how that ties back to customer retention rates. A high retention rate can lead to increased value and a better brand image. Marilyn talks about key metrics she pays attention to as VP of customer support, including the importance of understanding the time to resolution, common themes of issues, and the financial impact of these metrics is mentioned. In a recurring revenue environment, it is crucial to highlight top case drivers or issues tied back to the customers and provide the ARR to the executive team. The need to prioritize areas like product bug fixes or feature enhancements is stressed, and the cost to serve customers, breaking it down by segments and regions to better understand customer needs and improve efficiency. By focusing on these metrics, businesses can better serve their B2B customers and drive more value. Examples are shared.

Tracking Trends and Changes in the Support Business

In a VP of Customer Support role, key metrics include time to resolve issues, first time to resolve, and the ability to address user issues with the first interaction. Additionally, the team and individual level is monitored to identify areas for improvement. Employee engagement is a key focus, with companies conducting quarterly or twice a year employee satisfaction surveys. The focus is on analyzing trends and identifying high priority areas for improvement. In a support organization, it is crucial to prioritize employee experience, provide the right tools and processes, and listen to employee feedback. Support leaders should prioritize their team's well-being, as it translates into better customer service and interaction. By taking care of their employees, support leaders can improve their overall customer experience.

Evaluating a SaaS Company’s Customer Support

In evaluating a SaaS company, it is essential to consider whether the support organization has a strategic roadmap outlining their vision and quarterly milestones. This roadmap should evolve as business objectives and priorities change. A more holistic view of investments should be considered, not just focusing on key metrics. Marilyn suggests that organizations should give their team the support to take time to step back and look for ways to make things more efficient, such as creating knowledge articles based on interactions to prevent customers from having to log cases. Training and enablement should be provided for employees to continue learning and grow.

AI Customer Support Solutions

AI solutions are being evaluated and implemented by support organizations to enhance customer service. Marilyn led the first support team at Salesforce  to leverage AI and machine learning within their support processes, using SupportLogic. The app helped identify potential cases that would escalate, allowing managers and teams to be aware of potential cases and provide timely resolutions to end users.

The SupportLogic app has improved the way managers manage their teams and assigned cases to the right agents with the right knowledge and experience to handle unresolved cases more efficiently. This has led to improvements in the way managers manage their teams and elevating the customer experience provided by their support agents.

Timestamps:

03:40: Defining Key Customer Service Terms 

07:47: Classification of Customer Service Roles 

10:22: Transforming Customer Support from a Cost Center to a Revenue Driver 

13:00: Metrics and KPIs for Customer Support 

18:00: War Stories and Practical Examples 

21:48: Daily, Weekly, and Monthly Metrics for VP of Customer Service 

25:44: Evaluating Customer Service in SaaS Companies

29:07: Implementation of AI in Customer Service 

Links: 

Resource: https://umbrex.com/resources/how-to-analyze-a-saas-company/

Website: Golotusgroup.com

LinkedIn: https://www.linkedin.com/in/marilynlin/

Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.