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Big data, bigger challenges: The two biggest data sins in the enterprise

Big Data: the most overused and ill-defined buzzword in business today. Companies are investing time, money and valuable resources behind their efforts to be more data driven. But, is bigger data always better data?

The benefits of data are widespread. It helps businesses understand their customers - who they are, their shopping habits, and their lifetime value. It helps inform marketing efforts - where to best reach those customers, what messaging resonates with them, how to best drive purchase behaviour.

It even helps companies understand what’s happening right in their own organisations, from tracking efficiency and productivity to identifying challenge areas and untapped opportunities.

But when it comes to effectively leveraging data in the enterprise, companies are often taking the wrong approach and, ultimately, limiting the impacts of their efforts.

Companies are good at collecting data, but not so good at actually using it

Just as the term Big Data suggests, companies are often too focused on collecting a large volume of data, instead of collecting the right data - information that will really move the needle in the business. The result? Companies go into information overload and end up with decision paralysis. They have tons of information and no idea how to use it.

So what’s the better approach? Think backwards when it comes to determining your data needs. Where could data help drive behaviour changes within your organisation? What data points would be needed, by whom, and at what point in time in order to drive that behaviour change? Working in this way will help you determine the data needed to solve for business challenges, instead of force fitting your business needs to match the available data.

When it comes to data, don’t forget the softer stuff. Companies are often great at digging up numbers, and great at getting anecdotal feedback. Where they fall short is in their ability bring the quantitative and qualitative information together effectively to drive action.

Connecting your information dots will highlight cause and effect situations within the organisation, and help you better tie the data to action. At Square Root, we see a 60 per cent improvement in tasks being completed when data and text come together in action plans.

Companies are limiting their data impact by focusing on the wrong end of the organisation

When you look at the big pitfalls of how enterprises are using Big Data tools today, a few key missteps emerge.

They’re limiting the use of data tools to a small segment within the organisation, usually the senior management team or a small team data team. But the value of data comes when it’s used beyond the boardroom, and put into the hands of those “front line” employees who have the ability to drive incremental improvements every day. Take retail chains for example. Is it the executive team member in the corner office or the store employee who could use that information to increase sales on a daily basis?

Many companies have a myriad of tools being used, typically segmented by department. Today, most existing data tools are built to address the needs of one type of user. For example, your sales team probably employs a CRM tool of some sort, while your marketing team or customer service team relies on their own respective tools and systems.

This segmentation - with companies piecing together different tools to address different needs - often means retrofitting your real business needs to fit the constraints of available tools. As a result, you get watered down data and a limited view of the business, with no ability to connect important dots or identify correlations between departments.

Instead, companies should focus on finding tools that can be leveraged across the organisation. When evaluating options, look for two key features.

First, find a tool that the majority of your employee base can both understand and utilise to do their jobs better. While not every user will utilise every feature, the tool should allow users to dig into the features that are of value to them, while still providing organisation-wide visibility and insights.

Second, look for tools that are created for the 90 per cent of business users who are not very technical, rather than the 10 per cent who are. Effective tools shouldn’t require everyone to be a data scientist. Instead, they should surface the insights for users, helping highlight the information that is most useful at that time and in that context to drive the most immediate action and impact.

Data undoubtedly has the ability to impact and amplify the success of businesses today. To make the most of this growing trend, it’s time for enterprises to go beyond the buzzwords, give actionable insights to the front lines, and drive real business impact.

Chris Taylor is Founder and CEO of Square Root, an Austin-based SaaS company whose store relationship management platform, CoEFFICIENT, helps auto and retail enterprises leverage data science to align their organisations, increase transparency, encourage collaboration and improve store performance.