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Exceedra Byte:
Data Harmonization Strategy


Watch the fourth episode of our new Exceedra Byte mini-series focused on the basics of Retail Execution. This week, Andres Jejen, VP of Solutions Engineering breaks down the key components for successfully executing your data harmonization strategy and the importance of automating your processes to maximize the value of your data assets.

In today’s digital world, where information is the most asset, we have unprecedented volumes and sources of data at our disposal, available day in and day out. And I am pretty sure you have heard of the concept of a “Data Lake” through which, in theory, you can put all your assets, build relationships, and start consuming information for any purpose you can imagine. Sounds simple enough, right? But the reality is a bit more complex than this. Our “Data Lake” most of the times looks like a “Data Swamp”, in which:

  • Sources are Disparaged
  • References and relationships are not obvious
  • It takes a tremendous amount of man-hours to obtain insights.

For consumer goods companies, this challenge is not new. Every single day, our customers have to deal with syndicated information, ePOS data, retailer planograms, external, distributor and multichannel sales… and this is without considering that very few companies are tapping into social feeds and digital interactions to complement their landscape. In a past episode of the Exceedra Byte, we discussed how important it is to choose the right information to be placed in the hands of our field sales personnel; the data points that help them to make the right decision at the right time. But today we will be focusing on the other side of the problem: How can we orchestrate, organize and in general harmonize this information for it to be productive for your retail execution strategy?

Let’s be clear here: data harmonization can be a really daunting task, especially when you try to do it manually, without any level of logic or automation behind it. You have no idea how many times we have seen our customers dealing with enormous Excel files, trying to match codes, and creating catalogs and databases that are only useful in the computer of the analyst. Considering this, there are some key components for a proper Data Harmonization strategy to work:



You will invest in harmonizing the data intensely for the first time – and then you can focus only on the maintenance since everything you have harmonized already you don’t have to do it again.


You will use reference catalogs to match the data against, in a way that every single data point can be traced back and forth from the source. And no matter how much the data changes, you can still rely on your reference catalogs to create unique data points.


You want to have your data at the same level and compare apples to apples all the time. In that sense, your catalogs should contain the data at the lowest level of granularity possible, and from there, you can build whatever hierarchy or classification you want.

Let’s apply this to a real-life example: You have in your hands Retailer Point of Sale data, telling you what your average demand is, product rotation, inventory levels, etc. down to the level of the individual outlet and product. On top, you have your distributor sales, per geographical region and by product. And you have your own in-store execution data, giving you field based insights about Out of Stocks, Assortment and promotional compliance, and product distribution. Your first challenge is to create the necessary reusable catalogs to cross-reference the data according to their level. In that way, you will know that Retailer SKU code 123 matches the EAN code ABC and the distributor ID XYZ. Then, consistently you will be able to match all these codes back to your ERP and slice them to be analyzed by any categorization you would require. Once you have achieved that level, you can isolate your data points in the context that is useful for your field people – whether it is to make predictions on future sales, issue recommendations on new exhibitions, validate your store performance vs. their cluster, etc.  Once you have your data cleansed up, its value becomes extremely apparent, and you will uncover opportunities that otherwise could have remained hidden.

Automating these processes is key to avoid diluting the value of the data harmonization. And here’s where Exceedra can help: Our data harmonization solutions provide you with value on both ends of the chain: On one hand, we create repeatable, consistent, and homologated processes to clean and orchestrate your information and maximize the value of your data assets, in a way that you don’t have to worry about any manual labor. And on the other hand, we use the cleansed data in deep analysis to be consumed by any of our products, creating a connected landscape that leverages any of the available assets to issue recommendations, prescribe actions, forecast, and increase your revenue opportunities.

The potential behind a proper Data Harmonization process applied to Retail Execution is enormous, particularly if you consider that all latest generation solutions for field success are based on proper usage of information and interconnection with the ecosystem in which they live. Here at Exceedra we have the right set of solutions and people to fulfil your data harmonization and Retail Execution needs.

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Exceedra Byte is a weekly vlog series where we take complex trade and revenue growth management topics and break them down into byte-sized pieces. Stay tuned every Thursday for new episodes.

Watch the previous episode of Exceedra Byte – Retail Execution in the Metaverse


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