Last year, it was estimated that the number of bytes of data in existence was greater than the number of stars in the observable universe, and this figure is set to increase exponentially with 175 zettabytes of data predicted by 2025. Deriving from this unfathomable quantity of data, the term ‘big data’ was born to describe the large volumes of information that are created and collected by businesses daily. This has led to the common myth that the more data a company has, the better, resulting in many organisations focusing their attention on the amount of data they have rather than what they should do with it! In reality, it’s not about the size of your data, it’s what that data can tell you and the value it brings to the business. Even small amounts of data can reveal valuable business insights.
Volume or value
Gartner defines big data as high volume, high-velocity, and high variety information assets that demand cost effective, innovative forms of processing to enable enhanced insight, decision making and process automation. While in some instances, organisations may derive value from having large data sets, size really doesn’t matter when it comes to data. It’s what you do with that data that counts. When harnessed effectively, it has the power to increase revenue, improve employee productivity, gain a better understanding of customers, develop new products, mitigate business risk and help businesses plan effectively for the future. Yet, surprisingly only a small percentage of organisations are actively leveraging their data successfully with research revealing that business leaders are still making decisions based on their gut instinct and experience over what their data is telling them.
What’s more, a huge 97% of data is sat in digital storage gathering dust. If left unstructured, there is a high probability that treasure troves of valuable insights are being missed, meaning that the business is not reaching its full potential, enabling more agile and informed competitors to secure an advantage. Without a solution in place, data can become extremely difficult to manage and control as it continues to grow in quantity. This not only has a ripple effect on productivity rates as employees can spend enormous amounts of time looking for information that can often be like ‘finding a needle in a haystack’, but it can also impact on overall data quality. Relying on manual processes, for example, can increase both the likelihood of data entry errors and out of date information being present within the system, meaning the truth behind the data is not being exposed. In turn, this inaccurate data can translate to poor decisions being made, lengthy validation and correction periods and slow market response times leading to loss of revenue.
How do businesses adapt to the rising tide of data regulation?
Over the past decade there has been an abundance of cases where well-known brands, which typically sit on a mammoth amount of historic data, have collapsed due to not handling it effectively. Companies including retailer Toys “R” Us, book chain Borders, and more recently, department store Debenhams, failed to optimise operations quickly enough to stay relevant in a highly competitive digital environment. Had they responded to what their data analysis was telling them, the outcome of these businesses could have been different. Adopting technology that can process and manage data as well as provide visualisations about what is happening within the organisation in real time can deliver greater insight into everything from product materials and production rates to customer shopping habits and market trends. By knowing what’s working and what’s not, businesses can make decisions based on the evidence the data shows, rather than relying on ‘gut instinct’.
The pandemic is an excellent example of how the valuable data over big data can be used to drive decisions, as many businesses were forced to accelerate their digital strategies to remain viable. Management consultancy Mckinsey reports that the crisis brought about years of change to the way all companies and sectors do business, and many have recognised the strategic importance of technology to remain competitive and economic in the new landscape. Just like the 2008 financial crash that seemingly happened overnight, the impacts of Covid-19 were unpredictable causing various scenarios for businesses; and this meant they needed to utilise their data for different end gains. On the one hand, companies in ‘survival mode’ needed to access business critical data rapidly to make quick decisions and ensure continuity. On the other, businesses who experienced significant growth (e.g., hand sanitiser manufacturers or food suppliers) needed quick access to important data assets such as product, production, and material information, so they didn’t miss out on immediate opportunities due to increased demand. This is where solutions such as business intelligence software and data analytics have the power to help businesses harness their data and unlock their full potential.
Rebuilding your data analytics capabilities in a post-Covid world
Informed decision making
Adopting best-in-class business intelligence software and analytics tools can help organisations make more data-driven decisions that bring value to the business. They have the power to collate, manage, and organise data, pulling information into charts and visuals, making it possible for ordinary business users to join the dots between different systems and uncover patterns of behaviours. Business intelligence software experts can help organisations to identify the data sets that are important to the company, reducing the time to leverage analytics capabilities faster, meaning a quicker return of investment. Yet, adopting this technology to help uncover insights is just one key element required for success.
For data to be valuable it needs to be accurate and complete as poor systems and processes result in data that is unusable in its current form to elicit any meaningful outcomes. Businesses need to invest time and resources into data cleansing methods to identify and correct inaccurate information. Part of this process requires regular introspection to ensure that poor-quality data is not working its way back into the system. Crucially, there also needs to be a synergy between the technology and the people within the organisation as ultimately, finding value from data is business-orientated; employees with a good understanding of how the company operates will know how to use its insights for strategic decision making.
Technology is accelerating at such a rapid rate that it’s creating a skills gap meaning that digital tools either need to slow down or organisations need to catch up in order to put the right processes in place to capture valuable data. Rather than overlooking data and making impulsive decisions, it’s time for business leaders to keep up by using solutions such as analytics to understand what their data can tell them. It’s not about ‘big data’ — it’s about analysing it effectively to drive value.