Why don’t SMEs use data analytics?

With the explosion of content and its distribution, data analytics represents one of the great challenges when exploiting the potential of data. How can an SME collate and assimilate such copious amounts of data, collected from so many different channels? And how can you do it in real time? These are other questions that SMEs ask themselves when facing the implementation of data analytics.

On the other hand, small and midsize businesses are wondering how to extract the intelligence that analytics promises from a pile of structured and unstructured data. And, apply it to decision making. Without the technological means to do so, SME data can end up being just useless information.

Some obstacles that small and medium-sized companies indicate for the constant adoption of strategies based on data analytics are:

• shoestring budget

• Lack of technical knowledge

• Increasing data sources

• Analytics Development Speed

• Inability to provide end users with the tools to obtain added value

Pablo Couso, commercial director of Datisa says that “today’s companies not only need to work smarter. They must also do it faster. And, to do so, they must find ways to make the most of the knowledge derived from the data. All companies collect and store a large amount of data. Not analyzing them to make better business decisions and keep the company ahead of the competition means wasting one of its most valuable resources”

Timing is key for many SMEs to convert the value of their data into business results. Whether in logistics, retail or any other environment, access to analytics will provide companies with greater responsiveness, both on the front and back-end of their business.

The solution for SMEs could be to provide optimal information on how to start using data analytics

However, there are still several reasons why SMEs are not yet making full use of data analytics. In addition to those already mentioned, Datisa experts point out the following:

• Focus on revenue-generating activities to the detriment of analytics.

• The fear generated by the perception that data analytics requires time, resources and technical knowledge.

• The perception that getting started with data analytics requires complex systems and tools

In any case, they assure from the Spanish ERP firm for SMEs, they are logical concerns, but unfounded. Perhaps the solution could be to provide optimal information on how to start using data analytics. What resources would be needed? And design an implementation process based fundamentally on the objectives to be achieved. So if the business objective is to increase revenue, the key question would be to determine how data will help achieve this.

In this specific example, Pablo Couso defines some of the questions that should be answered through data analytics:

• What products or services generate more and less income?

• What data is collected and what should be collected in relation to income?

• Who will or should have access to that information and data analytics?

Finally, another of the obstacles that stops the full use of data in the SME universe is the lack of alignment of the teams with what Datisa calls the “single source of truth”. For everyone to harness the full potential of data in business operations and strategy, the go-to source must be trusted. That is, a single source of accurate and up-to-date data to make decisions.

In short, SMEs must take advantage of data analytics if they want to prosper in their businesses. More so in environments whose complexity goes beyond temporary situations. Information is power. And, as Pablo Couso concludes, “unless SMEs monitor the performance of their products, services and operations and what they cost in human and monetary capital, it will be impossible to know what is really working. The data can be used to track efficiency and potentially reveal new revenue streams, which is crucial for any business.”