Roadblocks to Decision-making: Symptoms of Poor Data Management

The proliferation of high quality, low cost, and even sometimes free information management systems is something that has introduced major efficiencies to businesses across every single industry. This has provided small business a great leg up when competing with big business, too.

But this has also contributed to a major headache for many organizations: different specialist systems that mange various processes or parts of an organization are commonly siloed. Despite the fact we have more decision-making data available to us than ever before, it remains under-utilized – and in some cases, unused all together – because reporting from these systems is slow and complex. Considerable manual work may be required to stitch data together into one picture of your business situation.

I once worked at a company with one of the most common information management problems: it took two days to get a financial report from the accounts department upstairs. So, every month:

  • I didn’t have access to automated reports, or the data I needed to do my job without manually requesting it;
  • I would have to request the finance report at least two workdays ahead of when I needed it;
  • If the person who generated the report was unavailable, it was even slower or impossible to get the information so sometimes, I had to wait even longer, and my to-do list became delayed;
  • The report, despite being a regular task took considerable manual work every time;
  • The information was obviously at least two days old by the time I received it;
  • Once received, the data often required almost half a day of tweaking before it was at a point where I could use it.

Within each report there was at least a couple of days’ work extracting data, a half a day of manual work to make sense of it – and this was to get to information that was already at least three days old! It’s not too hard to do the math; depending on how large your organization is, imagine if you could extract 2.5 more days out of every 1.5 staff each month.

This is an example of where a very simple regular reporting requirement was contributing to some business inefficiencies and data quality issues that can start to snowball into poor decision-making. You can see data quality was also an issue due to the fact it took time to compile reports, and the fact that manual intervention was required by two parties to extract and arrange the information for analysis allows human error to creep into reports that will be used for decision-making.

Wonder if you’ve got a situation that could be addressed by the application of Business Intelligence or an analytics solution? In addition to the last scenario, see if any of the following scenarios apply to you:

  • You or your team often receive data that is meant to report the same figures, but they don’t match, or are incorrect.
  • It’s difficult to distribute information to others in your organization in an efficient, automated fashion. E.g. There’s no automated monthly email, or one-click button that shoots reports out to a pre-defined group of recipients.
  • Is the analysis you or your team perform flexible, and capable of keeping up with business demand?
  • Can you perform analysis on real-time metrics and compare this information with historical trends?

In my case, when we got an analytics solution in, I could immediately access the information I required without interrupting anyone’s day, and without their workload interrupting mine. In one click, I could access information that was timelier and more reliable, formatted to make sense at a glance. Each month, the organization saved at least 2.5 days in productivity. I felt empowered to do my work. I could reallocate time from reporting to other projects. And with this clarity, decision-making was not only more efficient, but I was confident it was effective – based on information that was timely, and accurate.

Common myths around Business Intelligence go way back to when BI was new: when it was horrendously technical, difficult to implement and thus, expensive. It was completely unattainable for anyone but enterprise-scale organizations.

These days, BI is now much more refined. While every businesses’ information needs are unique, the process of integration and presenting information is much more efficient, making BI a valuable competitive or strategic planning and administrative tool for any organization – big or small.

One critical difference between a good and a bad implementation today is to ensure the solution is “business built”, rather than “IT built”. BI was traditionally something that was owned by the IT department. As such, it was typically overly technical, and unusable by anyone outside the technical support team. These days, it’s important to ensure all of your user groups are empowered to use some of the fantastic self-service features that are out there in modern BI products so they can feel as I did once we got our analytics solution: empowered, interested in the metrics and confident in their decision-making; focused on doing my job.

The next blog will talk about how you can demonstrate the function and the value of BI to your stakeholders so you get sign off on a project. In the meantime, share this blog with a friend and tell them to subscribe to our updates to receive the next blog!

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