All over the world, we see companies catapulting to exciting new heights by using data in innovative new ways. Ultimately, taking steps to become data-driven.
It’s true that data scientists can uncover some unremarkable insights. With the right data, and some really cool mathematics, they can run an array of analytical techniques and produce findings that the human eye would never be able to identify; even with the latest version of Excel.
And here’s the problem:
In many companies, there’s a divide between the cool cats who make the big, million-dollar business decisions, and the data experts at the coal-face; crunching the info.
“…the majority of data analysis is performed by tech-savvy nerds; people who are great at understanding data, but not necessarily at translating the data into business speak or giving it organisational relevance.”
The 5 steps you can take to become data-driven:
1. Make data accessible
It’s important to democratise your data. Break down the notion that big data is only accessible by your technical team and make it available to everyone but in a smart way. Aggregate your data into a central repository and invest time and effort in making it easy to use and interpret by everyone across your business.
2. Use the right tools
To interpret data, your people need the right tools. Make this real by providing it the support it needs:
- Open up data in a user friendly way
- Give the right tools to the right people
- Teach everyone how to access the big data
The fear in doing this, unleashing the whole organisation on to the big data platform, will result in hundreds and thousands of dashboards and visualisations that no one looks at or even needs.
But hasn’t that been the case with Excel or even MS Access for the past 20 years? How many results would you get if you searched for “Book1.xls” on your server?
But it’s only a reflection of the business’ desire to explore the data they have available to find something that’s not in a standard report. And this is the exact point of making your big data available to everyone.
Let them explore in their own way but using a much better environment, one that not only gives them the right data and the right methods but also allows them to share and collaborate. An impossible task, regardless of how many Book1.xls you have but much more probable with a proper data environment.
3. Get everyone talking
Within any organisation, the people with the best analytical skills often struggle to provide real value, unless they know what real value looks like. Encouraging everyone to work together and discuss what’s important for the business can certainly help data scientists understand what to look for.
A secondary benefit is the process of articulation. When decision makers are required to describe challenges, they may sometimes be forced to think about issues in a different way, which can uncover a whole raft of possibilities. As such, conversations can change. Legacy discussions, shackled to the old way of thinking, can fade away, and new questions and thought processes can emerge.
4. Question the need for existing reports
While most companies today have some sort of reporting framework in place, it’s smart to regularly challenge the framework. Also, ensuring that the reports are adding value and not simply being completed for reporting’s sake.
When you review your existing reports, you’ll typically find that some will stand the test of time. Others will require more of a deep-dive interrogation. And some will quickly stand out as “we do this because this is the way we’ve always done it” reports. Set these reports free, and focus on using data to fine-tune the reports that add the most value.
5. Share the love
As the big data landscape continues to evolve, businesses need to break down the notion that big data is only for the tech-savvy or key decision makers – and deliver it to the entire workforce. Already, we’re seeing a level of data analytics expertise becoming a pre-requisite for all kinds of professional positions.
The sole purpose of data analytics is to uncover new insights that provide value to the business as a whole. These insights can be new, inventive, and unlikely to have been seen by anyone in the business before. Sharing these insights into steps to become data-driven can help change how everyone in your business views big data. And you can then sit back and wait for the snowball effect to take hold.