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  • 600. Jeff Sinclair, The History of the Operations Practice at McKinsey

    600. Jeff Sinclair, The History of the Operations Practice at McKinsey
    2025/02/17
    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 ...
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    51 分
  • 599. Anne-Laure Le Cunff, Author of Tiny Experiments: How to Live Freely in a Goal-Obsessed World

    599. Anne-Laure Le Cunff, Author of Tiny Experiments: How to Live Freely in a Goal-Obsessed World
    2025/02/10
    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 ...
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    43 分
  • 598. Harsh Sahai, AI-powered Due Diligence

    598. Harsh Sahai, AI-powered Due Diligence
    2025/02/03
    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...
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    50 分
  • 597. Jim Ettamarna, A Framework for Commercial Excellence

    597. Jim Ettamarna, A Framework for Commercial Excellence
    2025/01/27
    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 ...
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    31 分
  • 596. Bart Sayer, Looking Beyond the Mirror: The Business and Science of Beauty.

    596. Bart Sayer, Looking Beyond the Mirror: The Business and Science of Beauty.
    2025/01/20
    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 ...
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    35 分
  • 595. Robert Garmaise, AI Marketplace Insights

    595. Robert Garmaise, AI Marketplace Insights
    2025/01/13
    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...
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    24 分
  • 594. Marilyn Lin, SaaS Customer Support

    594. Marilyn Lin, SaaS Customer Support
    2025/01/06
    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,...
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    29 分