RIS: Big data insights are the key to making informed decisions across the retail enterprise. But unfortunately, many organizations hide data from those that need it most. How can savvy retailers unlock the power of insights for all?
Keller: How do you share this data and insights with other branches or departments? Users are looking to find ways to get out of the mundane reporting to providing high value business support. Once again finding the right analytic platform is key. Finding a platform that allows analysts to automate and post on-demand reports to users enables these same analysts to focus on high value, strategic business support. In addition, we spoke about time. Time has become the biggest factor between a retailer and their customer. Bringing real-time information to a local branch or store managers, can be critical to customer acquisition. The same is true for e-commerce. Real-time analysis of your e-commerce store can make all of the difference to convert someone who is just browsing to a buyer.
RIS: How has the ability to accurately predict customer demand forever changed supply chain operations?
Keller: Demand forecasting is still very traditional. Most retailers are using sales history to anticipate future sales forecasts, but very few are actually using modern predictive capabilities. Anticipation results in a 50/50 chance, which is pretty much a GOOD educated guess. What you really want to do is become more accurate with your forecast by augmenting your methodology with predictive modeling. This increases accuracy upwards of 75%+ that you will be closer to your actual number. This requires an analytics platform that is capable of handling a variety of predictive models that best suit your business. For example, you may need to consider seasonality within your models but on the other hand, seasonality needs to be normalized, and it’s critical to most retailers to get it right. In addition, you need a modern approach to predict demand, using a platform that helps you look at external factors that directly impact demand such as weather, location and demographics which are shaping modern forecasting. This ties back to the data trifecta of physical, non-physical and psychological data. You must understand WHATis driving the behavior so you can gain that three-dimensional view of your customer.