Becoming a data-driven company. It is something many of us want to achieve today because it elicits thoughts of ultimate insight. One rarely thinks of data as being sexy, but the concept of being able to use data to accurately predict your company’s next move is pretty cool.
The race is on. Companies are working as quickly as possible to leverage their data assets to drive action and derive value. Terms like big data are common and the C-suite has a desire to pinpoint insight in these mass stores of data.
However, ultimate insight isn’t the reality for most companies today. Many struggle to use their data efficiently for daily operations, much less for critical business decisions. Information is coming in so fast, and from so many different sources that it is very challenging to manage. This leads to a lack of accuracy and trust surrounding most data systems today.
The majority of businesses believe their data is inaccurate in some way and globally, the average business believes a quarter of their information is inaccurate. Stakeholders believe their data is incomplete, outdated, inaccurate, and certainly doesn’t provide them with what they need to make intelligent decisions.
The inaccuracy of data stems, in most businesses, from the way information is handled and governed. Data management techniques have not progressed with the changing uses of data. Therefore, human error often plagues systems. In addition, many businesses can’t identify errors before they have a negative impact. It is only when a problem arises that a given data element is fixed.
With that degree of inaccurate information, it is very challenging to think how senior leaders can rely on this information to direct the future of their business.
The trick with any data exercise is planning and making it "small." Now when I say small, it doesn’t mean that you are not dealing with large volumes of data. What it means is picking the right data for a given task.
While we all have this dream of making sure all data is accurate, the reality is that most businesses do not have the staffing, technology and funding to make that a reality. There is a lot of work to be done, but what any business can do is prioritize, focusing on improving their data management techniques and ensuring consistency across the business.
However, organizations should figure out the data elements that are used the most. What technology can you purchase that will maximize your return on investment? What are the most important areas for your staff to focus on? How can you easily remove manual processes or centralize efforts?
Businesses need to be able to access, use and trust data. Information does not have to be perfect for us to find insight; it just has to be good enough for a given business. That means that organizations need to link data across channels and databases, put data governance practices in place and enable business users to access and manipulate data for given departmental purposes.
For more information on data quality and its relations to big data insights, be sure to read the latest blog post from Thomas Schutz, SVP and General Manager of Experian Data Quality.