It’s not a lack of wanting or trying that’s holding back organizations from becoming data driven as quickly and thoroughly as they would like. Quite the contrary; many companies are investing more resources toward their data analytics strategy than ever before.
So, what is holding back businesses from actualizing their goal of becoming driven by data? Here are three common challenges companies may encounter on the road to doing so.
Making Data Accessible to Users
With more advanced business intelligence software available on the market today than perhaps ever before, one might think it’d be easy to pick a vendor, deploy the tools and wait for the return on investment (ROI) to stack up. But it’s important to remember that there’s a big gulf between making technology available to employees and having them embrace it.
In other words, a leading challenge in the quest to become data driven is boosting user adoption rates of BI tools. Harvard Business Review cites a recent study in which 77 percent of executives report business adoption of data analytics initiatives is a major challenge. This is even higher than the previous response of 65 percent.
Further, most of these executives cited people and processes as the issue — as opposed to technology. Having the right tools in place to facilitate self-service analytics for all is a strong first step, but there’s more to consider when it comes to adoption — like helping users get comfortable with the tech and getting buy-in from every team rather than just data and IT.
Bottom line: Users will only adopt accessible, easy-to-operate tools into their regular workflows. Remove hurdles standing between employees and data insights and you’ll see adoption rise.
Overcoming Cultural Resistance
This brings us to another challenge standing between organizations and becoming data driven: Lack of a data-focused company culture. This can manifest itself in a few forms, ranging from stakeholder indifference to outright resistance to embracing a new way of thinking and making decisions powered by data.
Just how difficult are businesses finding it to forge a culture supportive of data initiatives? A recent survey found 72 percent of large companies report “they haven’t been able to create a data-driven culture.” As TechCrunch notes, 69 percent of respondents also say they’ve failed to create a data-driven organization, because “it would seem these two metrics would be closely aligned.”
A company’s data strategy is only going to be as successful as users’ attitudes toward BI and analytics allows it to be. For instance, trying to forge ahead without buy-in from executives tends to be extremely counterproductive. These attitudes trickle down to affect employees throughout an organization, too. If leaders don’t go the extra mile to prove they value data and factor it into their business decisions, there’s a slim chance workers will.
Another facet of company culture is whether or not it encourages people at every level to ask questions, experiment with data and act based on what they find. Organizations must ultimately consider whether they’re encouraging employees to keep their heads down and proceed with business as usual, or whether they’re empowering them to stay curious and share their insights. How managers and leaders receive employee suggestions plays a big part in whether cultural communication encourages people to incorporate data.
Drowning in Data
Another challenge companies face is missing out on valuable data insights simply because nobody has the time or inclination to search for them yet. Search-driven analytics tools can answer users’ questions in seconds — but users must first have a specific question in mind.
The other half of the equation is taking advantage of artificial intelligence (AI) and machine learning (ML) to uncover insights lurking within millions of stored data sets. These algorithms can uncover trends, outliers and business drivers automatically — no specific query required — then push them directly to the right people so they can act. The more valuable insights an organization is able to mine from data, the more data-driven their decision making can become. AI helps users find proverbial needles in the haystack without having to spend weeks and weeks hoping to stumble upon them the hard way.
These are just three of the challenges businesses face on their quest to become increasingly data driven. They’re formidable, but it is possible to overcome them with the right mindset and resources.
