Experience the Organizational Advantages of AI with Daisy's Change Management Journey

At Daisy, our AI system leverages the Halo Effect - the relationships between products - to deliver unique leading indicators that are 100% accurate at the level of retail decision-making. We’ve created a decision indicator that ranks the quality of retail decisions (e.g., promotional item selections) and scores them using a simple green, yellow, red stoplight; with green representing profitable decisions, yellow representing zero profit, and red representing negative profit (Fig. 1).

Ultimately, our green decisions outperform yellow decisions outperform red decisions every week. If retailers only considered logic, they would consistently follow our green decisions as they are always worth more than yellow and red. If this is true 100% of the time, why doesn’t this happen? Because AI, even with proven value, will not be tolerated until change management concerns are effectively addressed.

Change management is the largest limiting factor in terms of successful AI implementation in retail. Changing core business processes is daunting, especially when it involves handing over human-led tasks to automated systems that there is a fundamental distrust of. By taking our clients on the right change management journey, we can unlock the value AI offers.

Fig. 1 shows Daisy’s stoplight scoring for promotional item selections.

Primarily, there is a fear of being replaced. If 50% of a merchant’s current role involves manual decision-making, then having technology take over feels like being ousted - even if that is not the case. As such, merchants will resist the change even if they intuitively understand the benefit of AI. However, it is important to note that AI only takes on manual tasks - leaving merchants to focus on higher value, and often more fulfilling, strategic roles.

We also see concerns regarding compensation. Merchants are often compensated on category growth. However, Daisy’s objective is to grow total store. Since green items are not evenly distributed across categories, Daisy may recommend more promotional items from one category and less from another. As such, some categories may grow while others shrink. This creates resistance as merchants don’t want to lose their bonus. However, this challenge can be eased by altering the merchant compensation model.

Another common challenge is a distrust of AI and disbelief in its capabilities. Our clients believe that their capabilities are on par with AI and that it is not needed. While there is no doubt that retailers are excellent at their jobs - evidenced by the fact that retail organizations are incredibly successful - there is also no doubt that AI eclipses human ability. AI simulates millions of decisions in real time. It sees product relationships and finds opportunities that human beings simply cannot. Daisy builds the use case for AI by providing explainability to develop trust and help retailers understand what makes AI so impactful.

Industry challenges have made AI technology critical for continued success. Cost pressure due to inflation and a looming recession, supply chain challenges due to ongoing global conflicts, and increased ecommerce presence post-pandemic are all challenges that greatly impact profitability. Handling these challenges while maintaining daily operations is incredibly difficult without AI. However, AI implementation will never be successful until change management challenges are properly addressed. At Daisy, we support change management with a proven implementation journey refined over 20+ years working with our retail clients.

For one client, that journey began with taking two years of promotional data to compare what they did with what Daisy would have done. We demonstrated the difference item by item for every single week and explained why their selections were outperformed by Daisy’s with real product examples. For instance, one product selection generated an associated sales lift of $100,000. However, had they promoted a green Daisy recommendation, they would have achieved a lift of $200,000. Without altering their plans, we demonstrated all the missed financial opportunities AI could have leveraged.

From there, we augmented their plans for the next 8 weeks. Their merchants would create the plan, our AI would score it, and we would present the learnings and offer substitutions for sub-optimal decisions. For example, mangoes weren’t performing as well as carrots, steaks weren’t as impactful as ground beef, one brand of cereal should’ve been replaced with another. We presented all these learnings and encouraged the retailer to alter their previous selections where possible. Post promotion, the retailer saw improved year-over-year results and championed a scope increase of our AI in effect.

Change management is a process of trust building to overcome user apprehension. Explainability is critical and every week you must repeatedly show financial value with tangible facts to gain acceptance. AI is the future of retail, and the right journey encourages retailers to participate in that future.

Daisy has a proven track record of delivering verifiable financial results. Retailers leveraging our solution can increase total company sales by 5 to 10% (Fig. 2). Again, this is achieved by using AI to augment decision-making - replacing underperforming decisions with more impactful ones. This may look like swapping out ineffective promotional items with higher performing counterparts, setting optimal prices (often not so deeply discounted), and ordering item stock using higher accuracy forecasts.

For example, our client intended to promote a fish that sold 50,000 incremental dollars per week. This was far less than their highest selling fish, salmon, which sold one million incremental dollars per week. The client didn’t want to promote salmon due to limited supplier availability. However, even at 20% availability, the retailer would see $200,000 in sales with the salmon on promotion - four times more than the other fish at 100% supply. We advised the client that satisfying 20% of their entire customer base is far more profitable than satisfying the minority of customers that would buy the other fish.

Through no fault of their own, merchants don't have all the facts necessary to consistently execute impactful decisioning. Leveraging AI to support their decision-making uncovers opportunities to drive sales and subsequently increase profits. Daisy helps our clients tangibly understand what makes AI so impactful, making its value accessible in effect.

Fig 2. - For one client, changing only 50% of red and yellow recommendations to green resulted in $500 million in increased annual sales - representing about 5% of total company revenue.

The successful use of AI in the retail industry is contingent on addressing the challenges of change management. Until change management concerns are effectively addressed, AI implementation will never be successful. At Daisy, we take our clients on a proven change management journey intended to build the use case for AI and build trust at all levels of the organization. In doing so, we can effectively augment retail decision-making to deliver verifiable financial outcomes of 5 to 10% incremental total company sales growth.