How To Build a Data Culture in Your Organization

Taking full advantage of data isn’t just about creating the right analytics and having the right team – it often boils down to the ability to build a data culture within your organization. Without a data culture, all the work to integrate data and analytics into the core operations goes for naught as adoption fails.  According to a recent survey of 64 key executives in large enterprises, 72% reported that they failed to establish a data culture despite investing in analytics and AI.

To learn more about what a data culture looks like and how you can create one within your business, read on.

What is a data culture?

At its core, a data culture is relatively easy to identify. An enterprise has successfully created a data culture if every employee understands the purpose of the data being collected and how their team or department will use that data.

Getting everyone, at every level, on the same page in terms of data collection and analytics use is difficult. It requires significant investment from leaders. As a result, companies should consider investing in enterprise-wide software solutions that allow employees to easily understand analytics insights and integrate that information into their work.

Invest in employee education

Data collection and analysis has a simple premise: You have a problem, and analyzing data allows you to solve it.

At the very least, all of your employees should understand what problem your data collection and analytics is solving. If the answer to that question varies from department to department, educate employees about their department-specific data while simultaneously providing an overview of the company’s overall mission.

Connecting data to business goals – i.e., “Here’s the data we’re collecting, why we think it’s essential and the improvements you’ll see in your work once we start incorporating these analytics into our processes” – is necessary.

Going the extra mile and providing employees with basic data science resources or classes will also help create a data culture. Again, employing an analytics-focused Software as a Service (SaaS) solution can help in this regard. The more your employees understand data, the more interested they’ll be in how it can help them professionally – which is why experts at Neebo are so invested in helping leaders and employees understand how to use their software.

Build knowledge around your assets

Knowledge and trust are incredibly important in building a data culture.  If the analytic results fed to information workers don’t properly pan out when taking business actions, they will lose faith in the process and the data culture fades.

The large volume of analytics assets can easily overwhelm the everyday business analyst.   What is each good for?  What problems can it solve?  What does it mean?    Can I trust it?  Without this knowledge, how does a business analyst know if they are really solving the problem correctly.

A knowledge base of information about the analytics assets that are out there helps the business analyst answer the aforementioned questions about those assets.  The more they know about the data the better they can answer the analytics questions being asked.

Knowledge around analytics assets is not just for the business analyst.   Knowledge workers and management can see and use this information to build their own understanding so they can interpret results properly and build trust in the data.  Thus, when business analysts use assets or build new ones, they need to share they have learned.

Facilitate collaboration

When enabling a data culture, everyone involved brings something to the table.  All the data, analytics and business knowledge we just discussed is shared amongst the community.

Enabling your community to collaborate will get ad-hoc analytic questions answered faster andensure you have the right answers.  The latter is particularly important as the analytic results need to be trusted by the team and acted upon.  Collaboration helps make sure all data is vetted, all angles are explored and all skills and knowledge is brought to the table.

Collaboration also needs to be encouraged.  Knowledge silos need to be broken not just within systems but with process and culture.  The more teams are encouraged and even incentivized to collaborate, the more the data culture will flourish.

An great example of collaboration is shown in the Neebo demonstration video. The main owner of the problem brings his unique knowledge of the data, then shares that work with a colleague who has unique skills in analyzing data in Excel.  The two work together to rapidly answer a question – in minutes.

Wrap Up

Building a stronger data culture within an organization is both bottom up from within the analyst community and knowledge workers, and top down from leadership who facilitates and encourages the culture.  Especially important is to sponsor education to grow the culture, and facilitate knowledge and collaboration around data.

If you want to establish a data culture at your enterprise but don’t quite know where to start, Neebo can help.  The unique knowledge building and collaboration facilities of Neebo can not only help get faster answers to new analytic questions, but also drive a shared understanding of data that fosters a deeper data culture.  To learn more visit the Neebo website or test drive Neebo by registering for a free 14-day trial.

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