Why Don’t Employees Have Access to Structured Data and Insights?
According to a study conducted by Forbes Insights and Dun & Bradstreet, up to 59 percent of companies are not using structured data to run advanced analytics and produce insights.
And even in the companies that are, access to data and insights is often limited to isolated teams.
That is odd considering that the promise and potential of data have been trumpeted for over a decade now. And most future forecasters see data playing a mission-critical role in every process imaginable.
If structured data and insights have so much to offer, why aren’t companies utilizing them as broadly as possible?
These are some of the most common explanations along with reasons those attitudes are outdated:
There is too much data involved
The size and scope of data stores have historically been challenges, and realizing the implications of the scale is important.
But data that is properly structured is easily given form and function when paired with the right tools. And structuring that data is a more seamless process than ever.
Companies are increasingly acknowledging that data silos and discreet departments are counter-productive. The solution is to give employees access to as much data as possible.
The benefits are overstated
It’s true that the potential of machine learning, analytics, and other aspects of data in general have been spoken about in hyperbolic terms.
But that potential has been realized in the last few years.
And data is now more accessible and actionable than ever, regardless of a company’s size or strength.
It is also important to remember that as data-driven insights begin to become the norm, the companies that dismiss the capability put themselves at a distinct competitive disadvantage.
Employees lack training or experience
This is a very valid concern. Investing in new tech that employees are unable to use fully puts a real damper on its ROI. And data-driven technologies are complex by their very nature.
But years of data science have revealed not only how to leverage the full value of data, but also how to interface with data intuitively. It’s now possible to conduct advanced analytics using commands, features, functions, and interfaces that every employee already understands.
The onboarding process is minimal.
The cost is prohibitive
There was once a time when only the largest enterprises could afford to invest in analytics. It required a large budget for new software, hardware, staff, and possibly even space. But as with all technologies, the cost has come down over time.
And with the advent of self-service analytics it’s possible for companies to begin leveraging data without making major changes to operations or adding significantly to the budget.
Knowing how much employees stand to gain with deep access to data, it’s difficult to continue defining it as cost-prohibitive.
The business case is lacking
Some companies have concluded that while data sounds like an exciting asset, it’s not one that is particularly relevant to their business. Maybe they are less tech-reliant, operating in a less-competitive industry, or not even involved with a for-profit enterprise.
It’s important to only invest in technologies that have a relevant impact, but structured data and analytics absolutely meet that criteria for all organizations.
Data reveals insights that it would be impossible to know otherwise. And insights lead to opportunities that no one could have anticipated. Not matter what the short- or long-term goals of an organization may be, data is poised to serve them.
Giving employees more access, more tools, and more freedom in regard to data is undoubtedly a good thing. Just imagine how much about an organization would improve if everyone was fully informed about any issue at all times.