Machine Learning is Important, But So is an Intelligent, Collaborative Team

Traditionally, stocking inventory has required many systems and spreadsheets in order to place goods in stores and fulfillment centers. These outdated, manual processes are standing in the way of real progress. So how can retailers fix this? Adopting advanced technology is important, but retailers must first look to good business processes before they race to adopt machine learning (ML) capabilities. Without a solid foundation in place, ML is simply a wasted capital investment.

Fortunately, retailers can look to these five steps in order to promote collaboration and therefore use technology to its fullest potential:

1. Tear Down the Silos: Inventory placement today is controlled by three, often disconnected, plans. These plans are created by merchants when curating the assortment, planners when creating bulk orders, and allocators and replenishers when restocking stores. Therefore, this disconnection leads to lost opportunity with regards to inventory levels, in-stocks and end-of-life markdowns. Rather, a single plan available to the whole team reduces the opportunity to drop the ball.
2. Collaborate: Merchants, Planners and Allocators/Replenishers: Having one cohesive plan requires all teams to work on documents simultaneously. Therefore, tools that function like Google Docs for real-time collaboration are necessary. Some retailers may even find it beneficial to merge two of the teams, given that this may increase efficiency among employees.
3. Exist at Multiple Levels Simultaneously: Initially, the reason for the silos was so that each of the three roles could make inventory decisions at different levels of time and geography. For example, merchants handled the full lifecycle and the entire chain down to the day or store, whereas allocators and replenishers and planners were somewhere in the middle. Prioritizing the business process first, and the tools second, allows a plan that accounts for ordering, assortment and promotion decisions simultaneously and in real time.
4. Promotions and Assortment: Another reason for silos and multiple plans is the merchant must make real-time decisions with regards to pricing, promotions and assortment — without waiting for overnight batches. The business process must be built around this need to make decisions for the chain and for the store in real time. Historically, tool capability has constrained this ability. Real-time promotion and assortment analysis are a must in regard to business processes and tools.
5. Harnessing the Power of ML: Just like the calculators that we used to lug around from meeting to meeting, ML gives us a more detailed way to plan inventory and evaluate changes to the plan. However, ML is not a magic fix. ML without sound business process (not just data) will be a wasted investment. This technology gives merchants, planners, and allocators and replenishers a more powerful calculator to plan in real time and evaluate prices, promotions and assortment changes. This helps to ensure inventory is bought and placed for maximum service levels and profitability. However, retailers need to remember that ML is just that — a calculator that needs to be placed in the hands of a business-savvy user and supported by a collaborative planning process.

Final Takeaway

The better way to place inventory has more to do with business process than it does ML. Collaboration, tearing down silos and thinking in multiple dimensions with a real-time business process are the keys to better inventory placement in stores and fulfillment centers.

Matt Jones is vice president of retail strategy and product management at Infor, a global software company that builds SMB and enterprise ERP software cloud products.