How Your Organization can Effectively Utilize Data
It is no secret that the currency of the day is data and information. Organizations are looking to best use the vast amounts of data they are sourcing and producing.
The COVID-19 pandemic showed organizations just how they were using this data, and many realized they were coming up short.
As economies around the world shut down and businesses had to grapple with the unforeseen economic impact that quickly became a part of life, it became clear that organizations needed to use data to help stem the tide.
There was only one problem: organizations were not prepared to be truly data-driven. What caused this?
As organizations looked to utilize data to make decisions, they realized pretty quickly that they were not ready.
Was it the data that wasn't ready? Was the technology not adequate to handle their data needs and help organizations find success?
Neither. As data was already being sourced and the technology advancing, both were able to make a powerful impact.
A key answer is that the workforces of different organizations were not ready to utilize data in their day-to-day jobs to help them make decisions.
Large skills gaps exist in data literacy. Around 20% of people are confident in their data literacy skills (source: The Data Literacy Project). When an organization tries to democratize data (give it to the masses) but its people don't have the skills to truly utilize it, the outcome is disappointing.
This human element of data and analytics, which is forgotten when the focus is solely on technology and the data itself, may just be the most important.
Why is it that the human element is so impactful in a field and area of business and life where the data and technology are emphasized so heavily?
One quick question can help us understand this: how many people have an educational background in data and analytics? The answer to that question is not as many as we would hope.
This lack of experience with utilizing data, coupled with the impact of good salespeople who emphasize just how powerful their tools and technology are, can lead to a lack of success within data and analytics.
With an emphasis on tools and technology, the workforce becomes forgotten whilst an emphasis on upskilling employees becomes even more essential. How did this impact organizations during the pandemic?
With the lack of understanding within data and analytics, individuals were not prepared or ready to make data-driven decisions.
As organizations looked to the workforce for decision-making with data, the tiny gaps and holes in the organization's data and analytical capabilities began to open up and show themselves.
One area where this became very apparent was in organizations' inability to understand the four levels of analytics: descriptive, diagnostic, predictive, and prescriptive. The analytical puzzle pieces that the four levels of analytics make up were not fitting together.
First, most organizations found they were stuck in the first level, descriptive analytics, which tells us what happened. They were not able to find out "why" things happened in the second level, which of course can then lead to failed predictions and prescriptive analytics. Organizations need to turn this around and determine how they truly want to proceed, but how can they do it?
I am often asked this question, the answer always comes back to a certain framework I was able to be a part of through the Data Literacy Project, which I have modified it to fit the needs of organizations all around the world. The 5-step process can help any organization succeed with data when implemented. Here are the steps:
- Set your outcome - define what it is you want to accomplish
- Set your strategy - what strategy should you put in place to achieve your outcome
- Set your tools - what technology and tools do you need to ensure steps 1 & 2 are successful
- Set your learning - up-skill and reskill the organization in data literacy
- Set your culture - establish a culture rich with data, and utilize it for decisions
These 5 steps make up a skeleton, a backbone for success when it comes to data and analytics. If they are implemented correctly, organizations can start to close the gaps that were found during the pandemic and have potentially been in place for a while.
For organizations to succeed in the future, such a change may cease to be a luxury, and become a necessity.