Deep Dive: AI is a tool for changing culture
Can distributors lead the value chain by leveraging AI not just to improve effectiveness but to intentionally spur organizational change?
Innovating distribution is not a thing, and customers suffer for it. While researching Innovate to Dominate, I found that the theory and practice of innovation are focused almost exclusively on innovating in the context of products or technology. I pushed for an explanation and most often found one of two answers: Distribution is “only” an extension of product, adding value to complete a product’s customer experience; or, distribution is a legacy, friction-filled function, and the target of disruptors, driving change from the outside. More and more, I believe that distribution must take steps to carve out its own space as a business activity that creates value from scratch for customers, independent of products delivered for manufacturers. All companies engaged in distribution must intentionally design and manage their culture—not just in terms of values, but as distribution’s most consequential processes, actions, and behaviors. The findings of an MIT Sloan Management Review, Big Ideas Initiative, published as The Cultural Benefits of Artificial Intelligence in the Enterprise and written by Sam Ransbotham, et. al., provide invaluable insights for B2B innovators by reporting that as companies implement artificial intelligence projects, they achieve financial AND cultural benefits. Knowing this, B2B innovators can implement artificial intelligence as they simultaneously and consciously renovate their culture as a distribution-first business model. The report shares benefits for culture at the team and organizational levels, but in this edition, I cover only the team benefits. I encourage every B2B innovator to download the free report, read it, and draw conclusions.
Using AI to transform culture
Leveraging the power of AI to help transform distribution’s culture begins as the technology is introduced to teams. Every team has a culture, and culture is always a barrier at the beginning. Drawing on additional research, the report explains, “Culture is like a team’s immune system: It is for the group what defense mechanisms are for the individual.” In my work, I have found that as an organization drives the adoption of artificial intelligence, often from the top-down, managers and members must understand AI’s role in achieving market success and their team’s specific contribution. More than that, successful AI implementations require well-designed algorithms and the best possible data. From the start, teams can be included in the design and purposing of AI, helping to overcome barriers as implementation proceeds.
With buy-in established from the beginning, the effective use of AI creates a virtual circle. Success builds confidence, confidence benefits culture, and AI becomes a valued tool. The report finds:
Using AI can strengthen team performance. But, more importantly, cultural benefits [emphasis added] emerge when teams improve decision-making and efficiency with AI, and, transitively, these benefits would not have emerged if the team’s culture had not embraced the AI solutions in the first place. When teams become efficient and make better decisions because of AI, several aspects of culture also improve, including collective learning, collaboration, morale, and clarity of roles.
My jaw dropped when I read this paragraph because cultural benefits—collective learning, collaboration, morale, and clarity of roles—are at the heart of the challenges and opportunities B2B innovators face. I share the findings that most stood out for me below and have added observations from my work.
Collective learning
B2B creates value for customers through supplier and distributor collaboration, operating within norms and practices of the established value chain. The partnership evolves as suppliers and distributors, acting in their interests, adopt a full range of digital technologies, including e-commerce, automation, sensor-enabled products, data analytics, and artificial intelligence. The implementation of AI within a distributor or supplier creates collective learning across functions within their organizations. By proactively sharing knowledge with partners, AI implementations can achieve collective learning across organizations, strengthening collaborations and the value chain.
The report shares one example of an AI-driven project within an energy-focused distributor (Rexel). In the example, the AI tool was initially designed to drive increased sales across all vendors. Over time, Rexel recognized that the tool’s greater value was to train new vendors. By advancing learning around what products to offer as an upsell or cross-sell, Rexel increased sales and reduced the need for veteran salespeople to teach newcomers. This is an example of collective learning across partners, Rexel and vendors, in a value chain:
French energy company Rexel … designed its Next Best Offer tool for vendors to recommend upselling or cross-selling to clients based on their specific circumstances. The initial rollout of the tool had mixed success: Some vendors almost always used the tool’s recommendations, while others seldom did. The AI team working on the tool discovered that a vendor’s tenure determined its use of the tool. Newcomers, who had few ideas about what to offer next, were glad to have it. Veterans didn’t need the tool’s advice, but it turned out that they were also glad to have it, albeit for a different reason than the newcomers. New vendors had been pressing the veterans with requests for advice and support. As the tool became more effective, they stopped doing so. … Eventually, Rexel began using the tool explicitly for vendor training (while preserving its use as a recommendation engine).
Clarified responsibilities
As distributors and suppliers adopt AI and digital technologies, they are doing more than reaching new performance levels for established activities. Digital transformation is changing both partners’ business models. New business models mean new capabilities, and therefore, new roles for achieving mutual success in the collaborative partnership for serving customers. If business models evolve without intentional culture development within and across suppliers and distributors, the impact of AI will push partners apart, not bring them together. The report shares a story about how pharmacists used AI to better serve customers by improving their skills, and in the process, better understanding their role:
Slawek Kierner, senior vice president, enterprise data and analytics at Humana, explains how pharmacists in the healthcare company’s call centers used AI to improve how they handle interactions with customers: “We started with this emotional AI—essentially a software piece that listens to the conversation of our pharmacists at a call center. It picks up emotional signals in this conversation and then suggests what the pharmacist could do to provide a better experience for the member.” … Pharmacists who used the tool came to a new understanding of how to execute their role. They learned something about themselves, their customers, and how to handle customer calls. Our survey findings show that this is a common result of effective AI implementations. Among those who reported increases in efficiency and decision quality from their AI implementations, 65% saw improved clarity of roles.
This same evolution is happening every day whenever distributors and suppliers implement AI for roles that include marketers, salespeople, financial teams, operations management, general managers, and more. I can imagine industry-wide efforts, perhaps led by trade associations, to foster communication among suppliers and distributors around the impact of AI on skill development and the evolution of roles for team members on the front lines of serving customers. Such an initiative would point to how both partners are creating the future for their unique business models, thereby highlighting new opportunities for collaboration. This work would also deflate fears of disintermediation by suppliers and diverging loyalties by distributors. The partnership will evolve, but by working to define future-focused cultures, the partnership may survive.
Affected collaboration
Digital tools, especially AI, are often implemented on the front end of a B2B company’s business model, improving not only organizational effectiveness but also the customer experience. The report shares a story that should resonate with every B2B innovator:
Amy Adams, senior director of global CRM and martech strategy at McDonald’s, notes, “As we work to elevate McDonald’s customer experience, we are using advanced analytics in a more advanced, agile way. This data allows us to better understand customer needs and expectations, enabling us to deliver the most relevant experience. We’ve also developed a global test-and-learn practice that allows us to better anticipate what will resonate with customers by testing various hypotheses. We’ve been building this new way of working and muscle over the last few years, and this capability has really motivated and influenced the organization to work cross-functionally [emphasis added] in a different way than we had ever done previously.”
Again, knowing upfront that AI will lead to cross-functional collaboration—often an exceptionally difficult ambition—is empowering for forward-looking managers and teams. Cross-functional collaboration requires a culture shift, meaning that AI can be intentionally implemented as a precipitant for that shift. Monitoring customer experiences for learning and ensuring the entire organization responds is also collaboration. By stating not just the value of collaboration, but by defining the processes, actions, and behaviors for leveraging data and managing customer experiences, every B2B innovator can guide teams toward new and consequential digital-age cultures.
Improved morale
Distribution is essential for business. Without distribution, there would be no trade between manufacturers and customers. As distribution workers realize their importance and—through innovation enabled by AI—continually upgrade their professional contributions, progress will lead to improved job satisfaction and team morale. The report tells several stories. I like this one:
Swedish fast-fashion retailer H&M Group experimented with different ways of using AI to help price products for end-of-season sales. It tested scenarios in which humans priced items, an algorithm priced items, and a human and an algorithm worked together, with the human evaluating and tweaking the algorithm’s decisions. The combination of human and machine worked best, and the retailer’s employees welcomed the technology. “Everybody loved it,” recalls Arti Zeighami, former chief data and analytics officer at H&M Group. “They said, ‘This makes me more precise. It makes me sharper. It helps me make better decisions. It makes my work more fun. [Emphasis added.]’”
Join our innovation community by asking questions
Culture is a too-little used tool by many innovators, including those dedicated to ushering in the coming B2B revolution. I suggest several questions to help add culture to the theory and practices of B2B innovation:
For every innovation, planned or executed, can you list the basics of culture—values, processes, actions, and behaviors—that are affected by your innovations?
Working with this list, can you identify the barriers that culture creates?
Thinking beyond barriers and imaging the future, can you define how the use of AI and other digital technologies will positively impact your team’s culture?
Can you define how improved culture at the team level will improve the attainment of overall organizational goals and strategies?
Across all of these questions, can you update your innovation missions and practices to intentionally include culture as a frequently used tool?
Please download, read, and share The Cultural Benefits of Artificial Intelligence in the Enterprise, and let me know what you think. Did I miss any important findings? Do you disagree with my observations? Do you have examples from your innovation experiences or across your industry? Don’t be a stranger. Please leave your comments below, click here to schedule a call, or send me a note at mark.dancer@n4bi.com.