Don’t waste your data. Make it useful

Not all data is valuable. You have to know what to measure and how to measure it. Decisive Facts can help you make your analytics work for you. By focusing on what actually makes a difference and making it useful.

Business Intelligence and data science are big business, with spending estimated at EUR57b in 2020. Data volumes are spiralling with estimates as high as 1.7MB per second. For every person around the globe! The stuff of the 1990s science fiction novel has arrived. Yet many remain disappointed by the practical results of their investment. There are often two issues – inefficiency in methods, or not pinpointing how to extract added value. Let’s take make your analytics useful…

So, you have invested time and money in data analytics. But for some reason, you’re not really getting out of it what you had hoped, or what was promised. Spotting that one big insight that will give you the competitive advantage seems a long way off. It all seems to be taking so long. Unfortunately, you seem to be stuck in the dataset trap. There IS a vast amount of data, and often there are significant gains to be made – but you have to focus on the right thing. Focus on Useful Analytics.

The challenge in making data useful

While business intelligence (BI) specialists are often active and happy to show you what they can do, it’s a point in case that pinpointing where true added value is to be gained IS tough. Often, projects simply focus on areas in which there is a lot of available data, but not necessarily on the returns. There is so much development in BI tools that people often get stuck simply discussing which tools need to be used when and for which purposes.

At the same time, staff in line and staff departments are not necessarily waiting for innovation. Especially if it changes their existing job descriptions or way of working. It’s not uncommon therefore for managers to send their BI specialists to areas where they can’t do much damage. Often because they are uncertain about their own positions and future.

The issue is that, although you may be investing in BI, you’re not necessarily getting better results. So how to solve this?

The trick is to find the correct mix of data and practical, hands-on knowledge of the issue at hand. And then to find the best possible solution. There is often either an issue from an organisational, business perspective, or an issue with one of the tools. So you need a focus on both and then to define a clearly measurable business case. Make your data useful!

Making your analytics useful

Disappointing results from data are generally either a business or process issue, or an issue with the tool itself. You could also put it like this. You may be doing the right things, but not in the right way. Or you may be doing things right, but you’re possibly doing the wrong things. The following chart shows where your issue may lie.

How we help in practice

This is one of the areas where working with Decisive Facts will make a difference to you. The fact is that data doesn’t lie, but it doesn’t tell the whole truth either. What you need is an organization that understands that solutions are a combination of people and data. We call it The Human approach to data analytics.

On a basic level, however, we distinguish between two approaches: one via a business issue and one that relates to an issue of a particular tool.

Business issues

For business issues, the major challenge is to understand how to get to grips with internal and external data. This needs to be translated into a project that has the full support of all stakeholders. This includes a thorough analysis of the business issue, including dialogue with stakeholders the operational, business-driven parameters. We initiate draft projects, which are assessed, and with the relevant stakeholders develop a long-term plan for improvement.

Issues relating to existing tools

If you have an existing tool that is not delivering as expected, we need to look at the aim of the tool, and the tool itself. What is the practical application, how does it work, and to what extent does it answer the question it was set up for? It is basically a second opinion on inputs, outputs, calculations and distributions. Again, here too The Human approach is essential as these types of projects can very easily deteriorate into purely data-driven exercises without input from the organization. We therefore discuss results with stakeholders, align on the solution and investigate potential short-term fixes. This is followed by the long-term plan for improvement.

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