By Marie Jackson, CMO of Retail Solutions Inc.
Data sharing as it exists today between retailer and supplier is not enough. The industry is changing at a rapid pace. Everyone is competing. Players that used to occupy discrete areas of retail are now overlapping and challenging one another for the same set of customers — think Wal-Mart entering the grocery business. Consumer expectations have never been greater — they want, and demand a consistent and unified experience across all channels. Many best-in-class retailers are experimenting with new and innovative ways to share data and address the competitive threat. I like to call this, the next generation of data sharing. It's where collaboration occurs on a near real-time basis and customer needs are immediately satisfied.
This next generation of data sharing begins and ends with the sharing of daily POS data and requires much collaboration and joint planning and execution in between. By sharing data daily, producers can learn what the consumer really wants, on a near-real-time basis. They can also respond more effectively, ramping up production and distribution of popular items, while cutting back on those that aren't selling so well. They can rapidly identify out-of-stocks or predict what will go out of stock and minimize their impact. It's during this process of real-time, daily data sharing and collaboration that retailers and suppliers increase the lifetime value of customers, deliver faster inventory turns in-store and create higher margins through reduced out-of-stocks or finding and correcting pricing and promotional errors.
At its core the next generation of data sharing requires turning data into action. Avoiding the gaps, variances, lags and uncertainties that have historically plagued the retailer/supplier relationship, the next generation of data sharing is rooted in real-time demand signals and not a lagged indicator like previous orders. This new form of data sharing is about tying retailer goals to daily execution and joint business planning based on a single version of the truth — which is predicated on the sharing of data on a daily, not weekly or monthly basis.
So, how do you incorporate the next generation of data sharing into your organization? First, define what data sharing means to the organization: the adoption of end-to-end collaborative processes between retailer and supplier based on a single version of the truth. Then decide on the program parameters: set strategic goals, determine collaborative business processes and agree-on rules to measure ROI and program success. Like with any new initiative, the key to success is having a good support structure and plan behind it. Here's a step-by-step guide to help get things started.
Step 1: Educate Executives and Create Advocates
Having executive champions is critical to the success of your data sharing program. It’s key to educate the C-suite about how the company can achieve major ROI and stay steps ahead of the competition through the next generation of data sharing. It also puts executives at ease to learn that the new trend in data sharing doesn't cost millions in overhaul or require a lot of IT resources to implement. In fact, it's about making better use of the resources you already have. Your data.
Step 2: Identify the Top Business Problems that Need to be Solved
Every organization has its set of problems, both big and small. But to kick off a state-of-the-art data sharing initiative, you must first identify, with your suppliers, the top two to three business problems that must be solved this year. Keep it scoped to challenges that impact the organization as a whole and, once solved, will provide measurable value across the enterprise and help with Step 1.
Step 3: Understand the Data Needed for Each Use Case and the Role of Each Party
Each use case has specific data requirements that need to be shared. For example, reducing out-of-stocks require different data elements than improving promotion allocation or reducing unsaleables. To streamline efficiencies and avoid conflict, define the role of the retailer and the supplier in each specific use case — who will take what action to bring the use case to life. If an out-of-stock condition is predicted early on in a promotion, what is the supplier supposed to do — and what does the retailer do? Does the supplier suggest an order quantity and the retailer send that order for immediate replenishment? Or does the supplier have permission to send a DC order directly? If excess inventory remains at a planogram changeover or for a seasonal item, who can authorize a temporary price reduction? Forward-looking data sharing takes the friction out of the sharing process by automating next steps, ensuring action is taken quickly and efficiently.
Step 4: Bring Suppliers on in a Phased Approach
Cutting-edge data sharing programs are best designed with a small group of key suppliers forming a joint advisory committee to ensure that collaborative business processes can be implemented and scaled by both sides. It's best that the advisory supplier group conduct pilot programs first — to both hone the processes and demonstrate ROI. With the competitive advantage proven, the program can then be rolled out to the next group of suppliers to find and fix any issues at scale. From there, it can be rolled out as quickly as desired.
Step 5: Replace Feeds/Portals with Advanced Data Sharing that Scales
Once you have all of your plans and support systems in place, nothing is stopping you from making the transition. Most retailers will find that this process can be fairly seamless, with little-to-no disruption to day-to-day operations. In time, daily data sharing will expand to include new data sets i.e., social and hyper-local data served to the in-store workforce and field operators via intra-day alerting on a mobile device. While this scenario is almost a reality, putting in place a progressive data sharing program today will help retailers be prepared for tomorrow.
In the end, the next generation of data sharing is a win/win for everyone. Suppliers optimize their product mixes and avoid excess inventories. Retailers slash out-of-stocks and avoid empty shelves. And, most importantly, shoppers get what they want — a seamless, better shopping experience.
Marie Jackson is the chief marketing officer at Retail Solutions Inc., a Mountain View, California-based company that provides big data analytics and real-time intelligence for the consumer goods industry. She can be reached at email@example.com.