Food For Thought | Enrich your internal data – improve decision making

Author: Gert-Jan van Fessem

During the past decades (since mid 90’s) organizations started to register more and more data within their ever expanding application landscape. In the early days the usage of this data was restricted, mostly for invoicing / VAT and QA reporting purposes. Over the last few years the value of data has been acknowledged as a driver for innovation and growth whilst Excel was replaced or complemented by Business Intelligence (BI) tooling. By doing so, an organization gets an abundance of new insights into their organization. However, it is based solely on their own internal data and information is presented via flat formatted values (Excel) or more graphical visualizations (Power BI).

With a focus on only internal data an organization limits itself and ends up with tunnel vision.Simply put, internal data does not tell the whole story.

Therefor we, at Food For Analytics (FFA), took it upon ourselves to identify relevant external data that enables your organization to get its decision making to a whole new level. By making our external datasets available you are able to enrich and compare internal data with external data.  Combining internal and external data enables you to truly understand the impact that macro-economic events, seasonality or sporting events have on your own business. In the next paragraphs I will elaborate a little more on this subject, which data can be added, how to enrich your internal data, and how that gets you even more valuable insights. As FFA focusses on the food industry we have pinpointed branch specific external data sources.

In the remainder of this blog I’ve identified a number of external data sources and how they are complementary and enriching your internal data:

Weather data

Weather data can be used to compare the internal sales figures with patterns in the weather, where the obvious example is correlation between sunny weather and an increase in BBQ items. See also our prior blog where our colleague Benito elaborated on this subject.

Calendar data

Embed specific calendars which consists of bank and public holidays, regular (school)vacations as well as sporting events (football championships, etc.) which most certainly have an impact on demands within a region (more demand at the coast during holidays compared to off season sales).

Demographical data

Think about data on income / age / gender / religion that enables you to to compare and align the demand and the offered assortment on a geographical basis. This demographical insights can also help to compare or identify a target audience for new product introductions and adoption of adjustments.

Market data – supply

Embed global prices on livestock and fodder in order to predict upcoming fluctuations in the prices of raw material and therefor the effect on internal cost prices as well as sales prices.

Based on the mentioned information we do provide an extended horizon in order to predict future purchase prices. Besides it is also possible to compare those with historical production / purchase / sales figures.

To emphasize, the mentioned data sources are just a few examples of what is possible. It is up to your specific demands on how to enrich your data and thereby improve your insights and improve your decision making. Food For Analytics has a vision to have relevant external data available for you in order to enable your competitive advantage!

Do you want to unlock your competitive advantage, like and we’ll contact you!

Interested to join FFA!?

Feel free to apply at and join our journey to optimize the food industry with data.