In part 1 of this blog series on analytics maturity, I discussed the importance of analytics maturity and the four dimensions it’s comprised of: data maturity, organizational dynamics, analytic team dynamics, and usage and technology. In this blog, I show you concrete steps you can take to move along the analytics maturity continuum developed by IIA.
How to Improve Analytics Maturity
Becoming more analytically mature requires advancing in each of the four dimensions. I’ve provided actionable steps below.
Step One: Improve Data Quality
Steps to Improve Data Maturity
The first step toward data maturity is to house your organization’s data in a centralized location, such as a data warehouse or data lake. At first, your organization will only use internal data, but you should seek scalable solutions that can incorporate external or unique data sources.
“82% of organizations with high analytics ROI say it is very or extremely easy for data workers to access data.”
The next step is automating reporting and analytic processes so there’s a fast and easy way for stakeholders to access insights. Finally, you’ll want to ensure that your analytics team has a wide range of skills and capabilities, including data science and engineering.
Step Two: Improve Organizational Dynamics
Steps to Improve Organizational Dynamics
Leading organizations must create a top-down investment in analytics. This can get muddled when CDOs face the challenge of building a proper data function while appeasing executives eager for instant results. To help build momentum, initially focus on small-scale, high-value analytic initiatives that can impress leaders and help garner buy-in from the entire organization. Once leadership sees the value in analytics, the C-Suite must make it clear that data is a core business pillar. Employees should be given access to the necessary dashboards to help drive data-driven decisions. IT should be present throughout the process to ensure proper data governance and security.
Step Three: Improve Analytic Team Dynamics
Steps to Improve Analytics Team Dynamics
To improve your team dynamics, start by assembling teams to support your early analytic projects. These teams should include multiple business units, analytic leaders, and stakeholders. Remember that your stakeholders are your customers, as they’re the ones who will be interacting with the product (dashboards) every day.
“63% of organizations with high analytics ROI say that data and analytics workers collaborate well or extremely well.”
As you target small-scale, high-value initiatives, seek out specific analytical skill sets within your organization. Offer learning opportunities, such as lunch and learns, for lean teams or skills gaps and search for solutions that scale analytical capabilities with individual advancement. Scalable platforms that provide advanced analytics, machine learning, AI, and more will make it easier to advance to higher levels of analytics maturity.
Step Four: Improve Usage and Technology
Steps to Improve Usage and Technology
Having the right analytic solutions and IT infrastructure can make all the difference in your analytics maturity. To improve this dimension, begin making plans to scale and build your analytics infrastructure. You’ll also want to explore cloud-based analytics and consider how well any platform would integrate with your tech stack.
If you haven’t already started, explore and trial predictive and prescriptive analytics options, as well as machine learning with text mining, sentiment analysis, and modeling. Seek out solutions that work well in a centralized environment and will enable model development using explainable AI (XAI) best practices.
“77% of organizations with high analytics ROI say that all five steps of the analytics process are very or extremely well integrated into a single platform.”
Also, consider the usability and accessibility of your technology. Instead of spending millions on something like a data lake that only a handful of users will use, look for options that analysts and knowledge workers across the organization can use that are more cost-effective.
Step Five: Democratize Analytics
Perhaps the most important step in improving your organization’s analytics maturity is upskilling knowledge workers across the organization — or democratizing analytics. This is the most effective way for enterprises to surpass sub-50% of data-driven decision-making.
“68% of organizations with high analytics ROI say that at least a quarter of their knowledge workers are active users of analytics software.”
The reality is small analytic teams can never hope to answer all the questions and demands of the entire organization. With the right tools and know-how, hundreds or thousands of knowledge workers could be working on smaller analytic projects that accelerate ROI while your data scientists take on the major, more complex projects.
Essentially, data democratization is a change management process. There are three steps that lead to best-in-class democratization — and they are the basics of nearly any change management journey:
- You need to make people aware of what’s possible and excited enough to want to invest in training themselves.
- You need to provide the training and tools for people to go on the journey.
- You need to support and sustain them once they’re up and running.
These strategies can leverage a myriad of tactics, including user groups, hackathons, demo days, reward and recognition programs, etc. Take a look at some sample tactics for each step in the graphic below, and pick a few to implement to start your analytics democratization process.
Change Management Strategy and Tactics for Analytic Transformation
Take the Next Step in Your Journey
I’ve discussed key ways to become more analytically mature; however, the very first step in advancing your analytics maturity is understanding where you’re at. Here’s an interactive analytics maturity assessment that takes only ten minutes to complete. It will score your company and assign one of five levels of maturity. The tool will then prescribe resources to help you progress in your analytics journey.
Success won’t happen overnight, but once you understand where you’re at and commit to change, you can only improve. Altering your organization’s ways of thinking and operating won’t be easy, but it will be more than worth it.
Start your journey with an analytics maturity assessment.