If your colleagues and you were given all of the wood, nails, plumbing, electrical writing, and more that you needed to build a house and told to have it finished by the end of the month, no one would blame you if you failed.
But, if you were given a bunch of pieces that fit neatly together like connecting blocks, instructions, and a community of support, you could probably do it. Not only that, but everyone on your team would be able to participate, get on board, and feel capable of contributing. Building a house might actually be fun.
The same is true of transformation and building a culture of analytics. (Yes, even the part about it being fun.) You can’t do it without a team that’s on board. It takes a combination of organizational, procedural, and technological strategies for it to be successful. Not only that, but the strategies you implement must encourage growth and organizational adoption.
A recent white paper by Radiant Advisors looked at how different organizations worked on their digital transformation efforts, what drives a successful digital transformation, and how you can achieve it, too.
What they found is this: The organizations that succeed are the ones that build a culture of analytics through the convergence of people, processes, and data.
Put another way, they’re building the right mindset.
Organizations that succeed in digital transformation build a culture of analytics by changing the mindset of the organization.
While there are many approaches your organization can take in changing the mindset, each successful transformation includes three specific steps:
- Implementing a self-service data analytics platform
- Reimagining the data analytics processes within an organization
- Developing a culture of analytics through communities and self-paced learning
Here’s a quick overview of each.
Adopting a Self-Service Data Analytics Platform
What good is a digital transformation that builds up to a culture of analytics if you can’t get everyone on board? This means everyone who needs access to analytics should be able to use the platform. Executives. Directors. Managers. Data Scientists. IT. Human Resources. Everyone.
Whether they’re well-versed in Python and R or have little to no programming knowledge, a good self-service analytics platform should be built to serve everyone — no matter their skill level. Not only that, it should integrate with other services across your organization, make sharing and collaboration easy and scalable.
To effectively drive digital transformation, you need a platform that’s both code-free and code-friendly.
Reimagining the Data Analytics Process
You can’t have growth within the organization without changing the data analytics process. The old-school waterfall approach doesn’t cut it. You need to shift to an agile, individualized approach.
It’s not that IT shouldn’t be involved anymore. They absolutely should. It’s more that the data analytics process shouldn’t fall squarely on their shoulders.
As you change your process, here are three areas where you should focus your efforts:
- Governing the data to ensure it’s used properly
- Managing the output of the data and the models developed
- Deciding which metrics to use when determining growth for the company and employees
Make sure to pay attention to that last one, especially the part about your employees. You shouldn’t only see progress in terms of efficiency gains, top-line growth, and bottom-line return, but also in the training, engagement, and empowerment of your workforce.
Building a Culture of Analytics Through Communities
As your organization changes, you must support your employees. Your data analysts shouldn’t struggle too much with the initial changes. If anything, a self-service analytics platform that automates their processes will make their lives far easier. However, the managers and directors might struggle a bit at first.
But that’s okay. It just means you’ll have people at different parts of the data analytics journey, each needing different types of support. As you build your culture of analytics, you’ll need a community that supports them.
You don’t have to support this completely on your own. Support can come from both internal and external communities. Alteryx has one with hundreds of thousands of users that are all ready to help people solve any type of data problem.
Of course, the more you can do to help your employees, including the adoption of self-service analytics, funding for data analytics classes, and training, the better you’ll be able to help your company grow. But it’s not always feasible for everyone.
For employees new to data and analytics, you should focus on the following to give them a good start:
- Data formats
- Relational databases and SQL
- Data visualization
- Data storytelling
The most important part to remember is that a complete digital transformation isn’t possible without all three of these parts working together to change the mindset from the top down. However, if implemented successfully, they can lead to immediate outcomes.
Organizations that are dedicated to a culture of analytics and a willingness to reimagine processes will lead the way in driving enterprise adoption.