What's Next after Data Sharing Programs?

Downstream data sharing has been around for more than two decades. As retailers have grown more open with sharing their operational data with suppliers, consumer goods manufacturers (CGs) have been empowered to deliver analysis and recommendations that have helped both sides of the partnership attain important goals.
 

But there are still major opportunities for improvement in the daily business of introducing new products, maintaining stock levels, synchronizing inventory with promotions, and so on. Those improvements would result in billions of dollars of added revenue for both retailers and CGs and as importantly avoid disappointing shoppers.
 

The data is readily available to avoid these losses; what’s lacking are the analytics, business processes, linkages, and most important, the collaborative mindset necessary to identify and address them.
 

The next generation of data sharing programs must go beyond sharing toward true collaboration, embracing end-to-end cross enterprise processes and use cases that enable both parties to unlock significantly more value for everyone - the retailer, supplier and shopper.
 

When retailers and consumer goods companies collaborate on data sharing, they decide together how to act on the data they’re sharing, and define what steps each will take to find and address problems. They’re making data actionable.
 

Several research studies have determined that consumer goods companies’ most significant challenge with leveraging retailer data is knowing what to do with it. Retailers, too, wonder what CGs do with their data. Beyond the top brands, the vast majority of CGs have a mixed record making impactful use of their retailers’ operational data.
 

What they need is a structure for collaborating with their retail partners to identify the biggest pain points and devise mutual processes to resolve them.
 

Anyone in the consumer goods-retailer supply chain will recognize the everyday scenarios that stem from a lack of visibility or process:
 

·         Inventory is allocated for all 3,800 stores to support a new product promotion, but 241 stores don’t receive their shipments. How does this get detected? If the consumer goods company’s staff notices it, what steps do they take to resolve the issue?
 

·         A store’s item inventory count is inaccurate. Who will detect the issue? If the supplier detects the problem – do they notify the store directly, send in a merchandiser or contact their buyer?

Today, these issues are typically resolved in a haphazard, difficult and time-consuming way — when they’re resolved at all. Often, the resolution involves considerable labor on both sides; store associates can’t always detect the problem, so store managers and district managers, or CG field personnel, are rolling up their sleeves to get involved in inventory issues instead of attending to other tasks.
 

In collaborative data sharing, retailers and CGs work together to identify their mutual goals. These might include reducing inventory levels and/ or unsaleables, lowering out-of-stocks, improving assortments with better localization, and so on. Out-of-stocks and promotional allocations are typically the low-hanging fruit use cases of data sharing 2.0.
 

Then they build a set of processes around the use cases associated with these goals, considering key questions such as:
 

·         What metrics will we use to measure this activity?
 

·         What appropriate data do we have to share?
 

·         What end-to-end process will we implement?
 

·         What is each party’s responsibility in this process?
 

Finally, they create a scorecard so they can track their progress and set incrementally progressive goals.
 

Grocery retailer Ahold USA has led the way in designing a next generation vendor collaboration initiative to improve product availability and customer satisfaction. They discussed it publically earlier this year in a presentation at the Supply Chain Conference in Orlando, sponsored by the Food Marketing Institute and the Grocery Manufacturer’s Association.
 

The retailer and several key suppliers have set up a joint, executive-level steering committee for the program, which has created collaborative business processes for 18 uses cases and a scorecard to measure results. Ultimately, the program could be rolled out to 200 suppliers.
 

In the first stage of the initiative, Ahold is making data feeds of POS, supply chain and merchandising data available to CPG suppliers through Retail Solutions. As discussed at FMI/GMA the program is targeting improvements in on-shelf availability, inventory management, unsaleables reduction and promotional execution. Subsequent phases will address collaborative forecasting and assortment clustering, shelf optimization and flow optimization, and then optimization across the whole value chain.
 

Other nascent collaborative data sharing programs are underway today across North America, Europe, China, Australia and Mexico. In Europe, , where historically there has been less data sharing outside of the UK, retailers are skipping the first-generation approach and moving right to data sharing 2.0.

Two tenets underlie Data Sharing 2.0:
 

1)      Data should be free. CGs should only pay for third party analysis services that use the data.
 

2)      Suppliers should not be forced to use any particular system to participate.
 

However, CGs without their own systems may need the appropriate software to implement the collaborative processes. Some retailers will need to upgrade their enterprise systems to collect and share daily sales for every store, every day.
 

Ideally, collaborative processes devised by the retailer and CG will be heavily automated: The retailer furnishes data to the supplier, the supplier’s software detects any irregularities, someone on that retailer team verifies the issue —such as inventory is missing, or an out-of-stock — and then once verified a message is automatically generated to the retailers’ systems to replenish the store. Or, the retailer and CG could agree on a promotional allocation, and the CG’s system automatically submits that plan to the retailer’s store replenishment systems. Integration into the retailer workflow systems ensures that the processes that involve store personnel can also be supported.
 

Even better, CG’s systems can learn from the exceptions. So if a promotional allocation results in excess inventory in some stores and out-of-stocks in others, it uses that information to ensure more accurate allocations next time, reducing the need for resolutions. The algorithms parameters grow more refined over time.
 

Scorecards are a key part of the collaborative process and ensure return on investment is on plan and that processes are working. As goals are reached, the steering committee can set new ones, gaining progressive improvement to some of their key challenges. As time goes on, they can also add more difficult use cases that require more complex responses.
 

These are early days in collaborative data sharing, so retailer-CG partners typically aren’t ready to share improvement metrics. We can expect to start seeing success stories from early adopters in the next six to 12 months.
 

But we already know that when these sorts of fixes are performed manually — say by sending a merchandiser into the store to solve a problem — CGs typically add one-half to one percent additional revenue per retailer. So when that process becomes pre-defined and automated, the return is faster and greater. That substantially decreases costs on both sides and creates rapid return on investment — as much as two to four times the investment.
 

CG and retailer alike can realize their goals for increasing customer satisfaction because shoppers are finding what they’re looking for in stock. And that, of course, drives revenue and loyalty.
 

These are challenging times for consumer goods companies and retailers. The world is undergoing significant change: new mobile paradigms, an increasingly empowered and demanding shopper, the transition to data-driven marketing. That makes this the perfect time to reconsider time-worn business processes and look at new technology to address their flaws. The promise of a collaborative data sharing program is to actually reduce operational costs while improving in store performance and the shopper experience.