TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Making Every Employee an Analytics Expert

Widen BI adoption and use with these steps that won't disrupt your environment.

• By Lyndsay Wise
• January 8, 2019

Investment in BI and analytics technology is at an all-time high, yet its end-user adoption rate hovers around 30 percent. According to Gartner, 91 percent of companies say they still haven't reached a "transformational" level in data and analytics use. Although the intention is there, organizations still struggle to fully implement and derive value from their analytics deployments. To ensure businesses are making the most out of their data, they must break through existing barriers to boost adoption across the enterprise.

For Further Reading: Q&A: Simpler Analytics Can Reach More Users 3 Best Practices for Becoming More Self-Sufficient with Self-Service Multiplying Your Analytics Insights

Your business can take these steps today so employees can become analytics experts without adding lengthy training to their schedule or requiring an overhaul of their day-to-day workflow. After all, when intuitive access to data isn't limited, intelligent outcomes become unlimited.

One common hurdle with data adoption within organizations is data silos. Why, some ask, is this an issue if users are already leveraging data? The answer is that it makes widespread adoption across the enterprise difficult. I am a firm believer that you need to build a centralized analytics platform and a strong data management framework. Otherwise, you're going to encounter a situation where customer, product, patient, supplier, other data entities, and basic data inputs mean very different things across the organization, within different user groups. This makes it difficult to promote overall strategic goals, creates disjointed onboarding practices, and can hinder overall adoption.

Establish clear, actionable business goals. Is your analytics platform another solution being rolled out haphazardly, or is it a key component of your business plan? If the latter, then you need to treat it as such. A critical aspect of the education and onboarding process needs to be communicating your intended value and how this is going to benefit the enterprise. Be passionate about the ROI in data and it'll ignite your employees' passion as well.

A well-developed data strategy should empower employees -- even those with limited technical expertise -- to feel comfortable interacting with and utilizing data. One turnkey way to do this is to make the data visually appealing and match data access to overall comfort with technology. Accomplish this by using creative assets such as infographics to better display information. Forget the complicated charts of our predecessors for everyday users and embrace an immersive and visually pleasing data experience. This makes the information easier to digest and fosters everyday use cases.

Maintain awareness. It is not enough to introduce a data strategy, coordinate training, and then expect adoption to flourish. Business leaders need to continually find new ways to draw awareness to the analytics program and demand that managers engage users in their department. Do this by sharing interesting findings, presenting case studies, and discussing long-term goals. For instance, do you plan on creating new business opportunities through your information? If so, data monetization will be a tangible topic for employee feedback. It's all about sustaining interest and expanding the conversation as your data program becomes more sophisticated.

A Final Word

We have arrived at a point in the enterprise data journey where data assets should be managed and accessible by different stakeholders within the organization, not just the analytics and IT departments. To build a truly valuable data culture, adoption and analytical insights need to be widespread. Fortunately, solutions exist that are intuitive and user-friendly.

One final point that cannot be stressed enough: do not get discouraged by slow adoption. Sometimes initial analytics adoption is slow, but when an organization remains consistent in its approach to creating self-service intuitive environments and provides ongoing, interactive training support, overall momentum will grow over time.