Where Artificial Intelligence Meets Emotional Intelligence: 3 Steps to Strategic Retail Pricing Transformation
For all the talk about the power of artificial intelligence (AI) to drive meaningful transformation for retailers that want to reinvent themselves for today's demanding renvironment, many companies fall short of harnessing the full benefits of AI and analytics for actionable insights.
That’s because many of these attempts fail to take into account the human element of effective change management. For retailers to successfully benefit from AI, there must be systematic, organizationwide commitment to driving meaningful change and creating a data-driven culture.
Understanding and Engaging the People Element
In more than 10 years of deep engagement with retailers working to adopt AI-based price and promotion optimization, I’ve learned that AI and analytics alone do not power true transformation to a more agile and nimble strategy.
Instead, real success comes when a company embraces wide-ranging organizational change. Doing so takes a combination of top-down leadership and broad support among peer groups, meaning engaging at each level of the organization with champions from among their peers.
In other words, success with artificial intelligence requires emotional intelligence. Here are three steps to dovetailing both of them:
Step 1: Secure executive sponsorship.
To drive change, there has to be an executive at the table who’s willing to advocate for new technology that will make a difference to an organization. The right executive is not only a champion for the solution, but must be able to generate excitement, a sense of authentic urgency for change, and strategies for eliminating corporate obstacles. The executive should frame the need for adoption of the new solution in terms of overall corporate objectives.
Getting that advocacy requires a plan for communicating the impact that AI can make, or perhaps already has made, on the business. Fine-tune the message for each high-level executive based on that person’s business, priorities and individual experience.
Change doesn’t happen in just one conversation. Each AI discussion helps to plant a seed and expand thinking, enabling each individual to progress toward embracing science-informed decision making, always demonstrating the value to be delivered with the new technology. For example, the ability to process data much more quickly with new, self-serve analytical tools enables individuals to access data very quickly, build visualization layers, then help communicate valuable insights across the broader organization.
Step 2: Build buy-in across the organization.
Armed with executive sponsorship, the emotionally intelligent team can now establish a forum for stakeholders. As part of this effort, they should develop messaging that can be shared across the broader organization to educate people on the benefits of AI. That includes benefits not just from a financial perspective, but also on ways that AI can drive greater effectiveness in decision making as well as predictability in achieving business objectives.
For example, if a business unit isn't performing as planned, AI tools can help it hit margin objectives through dynamic pricing that takes into account real-time customer behavior and competitor pricing data.
Getting organizational buy-in is all about educating people on the ways that the organization and each business unit can benefit from AI tools. Show that machine learning algorithms can deliver insights that we can't see on our own and can't process quickly enough to stay relevant in our business. Bear in mind that the pace of this mind shift varies widely by individual and teams, and may require repeated education and messaging. Be prepared to accommodate different rates of understanding and evolution.
Step 3: Exercise a test and learn approach.
In less competitive, less shopper-controlled environments, there was the feeling that setting the course of a business — e.g., around pricing — happened very infrequently, perhaps only once a year. Of course, getting that strategy wrong could result in significant negative consequences.
But in today's hypercompetitive, data-driven market, we know that any price you set only has to be the right price for the moment. That moment could be six months. More likely it's a week or even a day, depending on the type of assortment a retailer wants to optimize and the pace of change in the market and among shoppers.
That leads to new opportunities to test a concept, learn from it, and then quickly adjust. The emotionally intelligent organization will reframe “mistakes” as a source of discovery, reinforcing desired change and removing the sting of perceived failure. In fact, this new way of thinking is a must for organizations to be more agile and respond more rapidly to changes. In other words, a test-and-learn approach is what’s called for in today’s retail landscape. And new AI tools make it possible.
Investing in the Organization
AI is a tool like any other in that it requires good, motivated people to use it effectively.
That’s why those retailers that I see driving the highest return on investment for AI deployments are those that also invest in developing the kind of organization, skill sets, and processes that allow them to make full use of their new tools.
AI can provide valuable returns. However, it’s only half of the AI-and-emotional-intelligence equation required for transformative results.
Sue Dale is vice president, global strategic consulting at Revionics, a provider of SaaS-based pricing, promotion, markdown and space solutions.
Related story: Using Artificial Empathy to Increase Revenue