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Retail Data: Are you using BI tools that are struggling to keep up?


man frustrated with slow software

It’s Monday morning, you’ve got your morning coffee and you’re ready to dig into last week’s sales number to work out your focus for the week. Fire up the trusty dashboard and let’s get cracking.


Enter the spinning wheel of death! Sound familiar? It’s a story we hear all too often.


It shouldn’t be like this but with every sales, merchandise and category manager hitting the Power BI or Tableau dashboard, the system just can’t cope.


At the core of any retail business is the data. Retail is a game of numbers and data. Every SKU, store, customer or transaction creates rows and rows of data. The sheer size of the data is growing at a faster and faster rate each year.


The load times are the tip of the iceberg when it comes to retail organisations trying to use the clunky dashboards of legacy desktop BI applications. These applications were built in the early 2000’s, almost 20 years ago. It was a time when the internet was young, the volume of data was still quite small, e-commerce was in its infancy and I still had a full head of hair. Times were good…


But retail, particularly e-commerce has exploded since then and data is no longer in the thousands or even hundreds of thousands of rows. These platforms can no longer manage once the volume of data gets above a few million rows. When that happens, we start to see load times blow out to minutes.


"Using tools that struggle to cope with the volume, and your needs, is costing your business money and market share."


The solution to the scale and performance problem is to reduce the row count, and that can be done in a couple of different ways. The first is to chop off the data and only use the last few months or year and delete the older history. This can be a workable approach, but it means you lose the ability to learn from the past and compare seasonality, both of which are pretty big downsides.


Another alternate approach is to create rolled up views of the data. For example, instead of showing every individual transaction, you could roll each store up to daily sales for each article. Again, this can work but you lose a massive depth of insights. For example, knowing which individuals are your repeat or largest customers, which items are sold together, or which pack sizes are performing best. It’s like trying to watch the footy through a hole in the fence. Sure, you can see some of the game, but you don’t really have any idea of what’s really going on.



All of these “solutions” are just band aids trying to cover up the underlying problem. The BI and reporting tools that worked for us as a business 5 or even 10 years ago, have not been able to keep pace with the changes that have rippled across retail. Using tools that struggle to cope with the volume, and your needs, is costing your business money and market share.


"It’s like trying to watch the footy through a hole in the fence. Sure, you can see some of the game, but you don’t really have any idea of what’s really going on."


The good news is that the BI market is evolving to meet these changing needs. The older legacy players are being dethroned by new platforms that are leveraging the cloud, AI and machine learning to deliver tools that can handle the massive volumes of data, billions of rows with ease. Even better they are using search rather than dashboards as their main interface, enabling the everyday business user to be able to ask their own questions on the fly.​ Which means much less frustration, less waiting around and not compromising the quality and accuracy of the answers you are searching for.


Whether you generate revenue of $5 million or $500 million, get in touch with us today to discuss how we can help you maximise the value of your retail data.


Get in touch with us via email at info@pivotanalytics.com.au or calling 1300 475 510.

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