Quality Data is the Beginning, Middle, and End to True Business Intelligence

As with all industries, across multiple sectors business-wide, the Business Intelligence (BI) industry is expanding and evolving rapidly. By 2022, Reuters expects the global revenue of BI to be worth $29.48 billion. The rising volume of data available to businesses means that they are constantly evaluating their collection and understanding of data to serve customers or target markets better. Business Intelligence is constantly allowing companies to evolve, pivot, and formulate new ways to service their customers better, and perform in a more streamlined and straightforward capacity.

In a nutshell, business intelligence is the process of taking raw data and forming it into valuable business insights and information. Essentially, it acts as an aid for making most business decisions. Business Intelligence tools can offer insight and detail about the state of a business. They can then aid a leader through decision-making processes, delivering the insight and transparency to make informed decisions.

So what happens when your data is inaccurate? The common assumption is that you end up making poor and ill-informed decisions that could have catastrophic consequences for your business. However, the crux of the matter is that the worst decision you can make is not deciding at all - regardless of whether it’s the wrong or right one. Even a wrong decision, or one made utilising weak data, takes time to see the results. A lack of any kind of decision realistically shows a lack of leadership.

Your choices can affect the direction that a company takes across the long term, and you can ultimately direct your entire business in the light of insufficient data, leading to bad decisions. A Deloitte survey found that companies with CEOs that spearhead data-driven choices are 77% more likely to achieve business goals. They are also 59% more likely to derive actionable insights from analytics results.

BI needs quality data as a bare basic

The foundation to Business Intelligence has to be quality data as an absolute first step. If you don’t have quality data, you really can’t hope to implement Business Intelligence as an effective tool. A well thought through data quality strategy will lay the foundations for any business steps you take intelligence wise, and it should be respected as the most critical base to Business Intelligence.

However, you have to take several steps before you can implement a successful policy of Business Intelligence. Once your data quality is up to a good enough standard, you have to be able to refine what you’ve got.

Businesses can refine data quality by taking a full scale, almost aerial view of the data and intelligence systems that a company currently employs. Taking this overview look will help a company establish exactly what areas of their data are lacking, where the gaps are emerging, and identify any rhythmic inaccuracies that are occurring regularly.

Once your data is accurate and you’re confident that it will withstand supporting the rigors of an intelligence process, businesses can then look to employ BI measures to begin making decisions based on quality data. Without this refined data quality, businesses cannot hope for BI or any other intelligence system to be effective, and could also be highly detrimental to business decision making.

Quality vs Quantity

The mindset of data collection has changed dramatically. Previously, businesses thought that collecting as much data as possible would give them the best chance of making business decisions based on that, with a total disregard for the quality of the data in question. Quite rightly, there is a growing understanding of quality over quantity, utilising the notion that lots of data isn’t necessarily good data.In the future, we’ll see even more businesses focusing on how good their information is instead of how much data they have. They can then ensure their decisions are built fully on quality data instead of the quantity of data.

What is the future of data management and business intelligence?

The first consideration in the future of business intelligence is that it’s an up-and-coming business tool, but it isn’t being understood or utilised by enough businesses. In 2020, the global BI adoption rate was 26%. However, the same survey found that BI is something that companies are bearing in mind for the immediate future, with 54% of enterprises saying Cloud BI is either critical or very important to their ongoing and future initiatives.

Understandably, the physical future of data management lies within making the data we use more accurate, eradicating errors, and, in turn, reducing the business decisions taken off the back of weak and harmful data.

One viewpoint that is gathering momentum surrounding data management is that the future of data quality lies within a shifting mindset. Many business leaders recognise that their data is ‘unhealthy’ and inaccurate, but few are happy to do anything about it. Businesses don’t always recognise the damage that harmful data has, and they don’t know how to make it healthy. There needs to be a greater understanding of utilising business intelligence and making it work for your business. When businesses have this understanding, they can start to get the most out of their data.

Understanding the damage that bad data can have will inevitably lead to business leaders taking their data management and systems more seriously and, in doing so, learning more about how they can make data work for them.