Many companies begin their data efforts hoping to benefit from the information they collect, and they pay a hefty price to do it. Data infrastructure carries expensive costs like employee salaries, data collection methods, hosting and cybersecurity vulnerability, among various other expenditures.
These companies have gone all out for data, but they haven’t gone all in. They’re stuck in the process of turning data into good information, or information into insights. But either way, data is not moving to the ultimate data goal: action.
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According to Forrester, 74 percent of firms want to be data-driven but just 29 percent say they’re good at connecting analytics to action. This isn’t surprising, there’s a lot involved in weaving data into everyday workflows, and it starts with building a more transparent data culture.
Here are some key things companies can do to build more transparent data cultures.
A central way to make a company’s data culture more transparent is to get employees to buy into data endeavors. As employees interact with data and experience how it can improve their daily workflows and aid in their decision-making, the more they’ll look to data any time a question or idea surfaces that they want to investigate further. User-friendly search analytics tools help make this happen. Through AI and machine learning, these tools offer the ability to search a massive database in natural language and receive informative, easy-to-digest data visualizations.
You can invest heavily in data collection, storage and the right data professionals to make sure that data quality is high, but if you want data to work for your entire organization and keep metrics and perspectives clear, you’ll want to develop a data lexicon. Having one document that lists various data definitions, metrics and clear explanations of those metrics, ensures everyone stays on the same page when communicating about data. There’s also less chance of confusion or disputes when teams and departments cross-collaborate on data.
Data Analysis Training
It’s unreasonable to expect all employees to be adept at data or able to analyze robust information to form insights without data analyzation training. User-friendly tools and a comprehensive data lexicon contribute to employees’ data aptitude, but companies need to go further. One way is to offer regular trainings on how teams can interact with their data in meaningful ways. Per TechCrunch, even low-level training to enhance basic skills in descriptive statistics can make a big difference. This could involve introductions to descriptive statistics, which help employees understand how to summarize data through means, percentiles, range and standard deviation — but also to understand when each are necessary given the scope of the data.
Breaking Down Data Silos
You’re undoubtedly collecting a lot of data, and from different sources. But it doesn’t need to stay that way. Integrating all the data you’re collecting under one hood is the only way to break down data silos and get teams working off the same information. Like with a data lexicon, decisions can be made easier and more objectively when everyone’s working off the same information. One overall view usually means more accessible and organized data, which increases the chances that employees will look to it daily to inform their next move. On the data team’s side, consolidating multiple data sources in one place makes it much easier to perform quality checks and cleanse data.
Habitualizing Evidence-Based Decision Making
We’re humans and we’re all guilty of falling into less-than-stellar habits; companies are the same way. Especially so when they’ve made their decisions and crafted strategy plans based on anecdotal evidence, hunches and business experience. When data is more transparent in an organization instead of left in the hands of a capable few, data activities move faster and slowly carve a place in company workflows.
As Brent Dykes writes for Forbes, “Most companies recognize data in the hands of a few data experts can be powerful, but data at the fingertips of many is what will be truly transformational.”
Transitioning to a more transparent data culture isn’t easy, but the potential benefits make the efforts more than worthwhile. Just remember: the answer to a company’s problems usually isn’t more data. Instead, it’s processes that drive insight. Whether that’s implementing the right tech and systems to cull data, developing a shared data language to communicate within or improving employees’ aptitude for data analyzation through training and user-friendly tools — the more interactive, clear and transparent a company makes data, the greater they stand to benefit.