Are you still struggling with your data?

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Data-centric companies are becoming the ones to beat in today's marketplace. Are you prepared for the shift?

Data can help you find, understand and address underlying organizational issues. The first step is understanding the data.

The struggle is real

Many companies are struggling with the transition to data-centricity as the need to do so grows by the day. Data-centric companies understand that their businesses generate data from customer and internal interactions and that they can leverage that data to spot trends, to take proactive actions and meet customer and internal needs before people realize they need it.

Some data-centric companies philosophically view themselves as much a technology company as they do the specialty that they perform. Ask yourself, are you a tire retailer or a technology company that sells tires? The answer can change your perspective as to how you approach data analytics and how you invest in those capabilities.

Got groceries?

Let’s look at a simple example. Today, grocery stores like Walmart, Safeway, Kroger and others can aggregate and leverage data from the check-out registers and your frequent shopper cards to adjust store level inventory mix at the macro level.

This is just the beginning of what’s possible with the data collected. Imagine a day where they are able to customize your shopping experience just in time for your shopping needs.

For example, using analytic tools, they could spot those customers that typically buy birthday candles and a cake at the beginning of April every year at a given store. This could signal a special recurring event, so they could proactively offer you a party catering proposal or a phone-based offer for related party supplies.

The promise of data analysis in this case is to be able to anticipate the needs of your customer well so that they don’t have to shop around. First mover advantage gets the business. Data analytics and automated workflows can be used to create these external feedback loops.

Internal uses

Data can enable the same type of capabilities internally. Imagine that you are able to find out and address a project schedule slip, long before the status meeting. Your data analytics tell you that the number of hours booked against the project are only 50 percent of what was planned for the week. Every day you gain in advance notice, the cost, time and impact to recognize, analyze and react to the specific condition is reduced.

How do I become data-centric?

The first and hardest change is an insistence on using data as a basis for decision making. Management by wishful thinking or screaming loudest has to become a thing of the past. If management isn’t comfortable asking “what does the data say?” then no one else will. Initially the data quality will be bad, may not exist or may show you things you don’t want to face. However, if you push through and address these challenges, you will be better served in the long run.

Secondly, you have to invest in your employee’s skills in digital storytelling, basic analytics and data structure. The intent is not to make them Excel experts or DBAs but rather give them the basic tools to understand how to do analysis and how to structure data in a way that allows for analysis. Simple guidance on the best visualization for the type of need would go far to ensuring you get better visualizations. Many companies also waste time getting data out of simple spreadsheets due to improperly designed data layouts. These skills are core to you and your company’s success in the coming years.

Lastly, your employees should have proper access and training for analytical tools. Everyone uses spreadsheets because we all have the software. However, spreadsheets are often the worst tool possible to tell the story. The rise of tools like Microsoft Power BI, Tableau and QlikView point to a capability to analyze and present data stories with a more rapid pace.

Please like this article if you liked the content. I look forward to reading your viewpoints and experiences in the comments below.

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