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Data-related challenges in demand planning and how to solve them.

November 5, 2019


In the retail supply chain, technology alone is not enough to solve data-related challenges of acquisition, synchronization and validation. You need clear processes, ably supported by technology.

For centuries, demand planners have looked into ‘historical data’ to forecast future demand. In today’s digital economy—what with its countless choices and the need of instant gratification—this approach might feel dated. To serve your customers when, where and how they want to be served, you need a radically different approach.

You need visibility into your sales and supply chain in real time.

Unlike all the centuries that have gone by, such real-time visibility is possible today. As and when a customer pays for one of your products in a remote corner of the world, your demand planners at the headquarters can get instant updates at their fingertips. You no longer have to rely on a wholesaler, or a distributor give you an unreliable spreadsheet report – weeks after the sale. You can get notified when an end-customer buys the product in real time.

If, and this is a big if, you have the processes and the technology to enable such visibility.

The data acquisition problem: Data can be captured, doesn’t mean it will

One of the biggest challenges our customers face, even in mature markets globally, is the incomplete / inaccurate capture of sales data. Today, retailers sell their products through myriad channels—for instance, wholesalers, distributors, direct-to-retailers, tele-shopping, your own website / mobile app, online retailers like Amazon and e-bay, online shops of traditional retailers like Walmart and BestBuy, the list goes on.

For starters, how do you make sure you have data from everywhere? Even if your channel partners truly wish to collaborate with you on data acquisition—which itself is a rare feat today—collecting, collating and transferring data from the ground to the dashboards of a demand planner is the fundamental problem any supply chain professional faces today.

The data synchronization problem: You need to have your data and understand it too

Let’s assume you’re one of the few lucky ones and every one of your channel partners has the data you want. Even then, across different POS systems, inventory management mechanisms, and reporting apparatus, the data you receive from them can range from pure gold to utter gibberish.

Now, imagine each of your channel partners giving you disparate data points in different structures / formats, your ability to draw insights from this data relies solely on your superpower to harmonize all this information—and present them in context.

The data validation problem: Who says the data is right?

By its very nature, retail is a widespread business, with a tall hierarchy of large teams managing operations—covering great distances from the start of demand planning to the finish line of actual sales. Without distinctly fail-proof processes and active monitoring, there is no guarantee that the data collected is timely, reliable or even accurate.

Given the scale of the retail business, the inaccuracies of data can multiply, undermining the very intent of collecting such data. It’s not without reason that many demand planners, even to this day, remain skeptical of artificial intelligence and other such ‘data-driven’ initiatives.

Solving data challenges in supply chain

From our experience, to solve the data-related challenges in your supply chain, you need two things: Processes and technology. The technology aspect of this is the easier part—there are plenty of tools in the market you can adapt and customize for your specific needs.

For instance, our own TradeEdge Market Connect has helped global retailers and Fortune 100 companies get better visibility of their supply chain. In fact, we helped a multi-national sports apparel conglomerate gain 60% increase in partner network and brand visibility with TradeEdge Market Connect. Covering 325+ retailers, covering 32,000+ stores across 30+ countries, we helped delivery inventory turn increase by up to 30%. You can read the whole story here.

In spite of the pretty picture that success story paints, we must warn you that technology is only half the solution. The other half is in your own data-related processes. Without the right set of processes—and the meta-processes in place to ensure your data processes are followed—your data-driven initiatives are destined to fail.

For instance, with the aforementioned client, even before we implemented any technology, the first thing we did was: process definition and data standardization. We aligned each retailer’s processes with our client’s processes, without losing sight of local and market-specific needs. We defined standard file specifications (SFS) for data acquisition. And thankfully, our client ensured all vendors and partners working on this initiative adopted these SFS to ensure common standards. In parallel, our client also began the development of their new POS system according to these specifications.

Taking a holistic view of their supply chain, and by aligning their processes with the new technology they’re adopting, our client was able to overcome their data challenges. So can you.

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