Do you trust your data to make decisions in your business?

The adoption of data-driven technology is at an all-time high. Data-driven decision making has become the bread and butter of agile businesses that seek to remain ahead of their competitors. On a daily basis, business leaders review their company’s data and run analytics to gain insights that will guide them down a path to success. 

This process has become essential to critical decision-making in recent months, developing forecast models and assessing risks. Therefore, having access to complete, high-quality data has never been more important. 

Yet, even though business leaders understand the value and impact data can have, 77% of IT decision-makers (ITDM) do not trust their data, according to research by SnapLogic. The distrust comes from a lack of timely, accurate data insights, often resulting in missed revenue opportunities and customer dissatisfaction. 

Trust is further eroded by a lack of standardisation of data, as ITDMs reported that 84% of analytics projects had to be delayed because the data wasn’t available in the required format. All of this would make ITDMs question the point of spending so much time, effort and resources on gathering data that did not work for them. 

Let’s have a look at the root of the problem.   

To start, and this will not be a surprise — bad data is a time-waster. But just how much of a time-waster is it? SnapLogic’s research uncovered that on average, four hours is being lost per employee per week due to the need to resolve issues relating to preparing data for analysis. 

Four hours here and there may not seem like much, but let’s put that into perspective. A company with around 500 employees who had to spend four hours every week on a needless task would set a business back 2,000 hours a week. That’s about 50 employees’ full week worth of work not being done. 

No company would continue to employ such people, yet businesses continue using the same time-wasting strategies and tools when handling their data. 

Even if employees were at the height of their efficiency, inaccurate data would still undermine critical data-driven decisions. It has almost become commonplace for businesses to take on analytics projects expecting that they will encounter problems with their data that will later need to be reworked. Poor formatting is also an issue, making it challenging to perform timely analytics and deliver useful business insights that can help businesses stay competitive. 

Something needs to change. Indeed, over 90% of the ITDMs surveyed agree that a lot needs to be done to improve data analysis quality. 

The next barrier is disconnected data.