How to become a data-driven organization

Big data, machine learning, AI. These are not new buzzwords by any means... but recently things have changed dramatically which has left organizations scrambling to catch up to a world that is quickly outpacing their capabilities. In short, we've seen three things that are driving this acceleration:

1. Volume - The volume of data being collected has exceeded our capacity to comprehend it. In the last two years alone we've generated more data than all of the recorded data in human history. We're just getting started too, as IoT and "smart" devices permeate our environment.
2. Velocity - We have the connectivity and processing power that data velocity is effectively real time. With the cloud, we can spin up new servers and storage on demand.
3. Variety - It's not just your internal data anymore, we can collect data from a variety of sources including social media, GPS, sensors, open data feeds, and more.

All of this is leading to a big problem. Companies are sitting on mountains of data, and they aren't using it. Data in and of itself is useless, it must be mined, analyzed, and transformed into information to provide value to your business. How big of a problem is this?

Gartner predicts by 2020 that 80% of organizations will initiate deliberate competency development in the field of data literacy, acknowledging their extreme deficiency.

This is a problem IT cannot solve

When talking to business leaders, the kneejerk reaction is to look to IT to solve their data challenges. This is entirely the wrong approach! IT does not interact with your customers, the industry, and exist in the cross cutting processes of your organization. These types of interactions and responsibilities are owned by the business. Marketing, Finance, Operations, from leadership to people working in the call center. This is where the chatter happens, where the opportunity lives.

IT's role in the data-driven organization is to collect and democratize the data. Once the data is shared, it is up to the business to embrace the shared language of data literacy and the shared context that leads to data-driven business. Future looking leaders realize this and the job descriptions are beginning to adjust accordingly:

There is a 4.3X demand for analytical skills in non-IT job descriptions than in IT. (CEB, 2016)

Why Data Literacy is Strategically Important

McKinsey put out an interview a while back that really resonated with me. For a business to be successful, there's basically two pathways they can take. The first is to invent your way to success. This is what many of your big name, high tech, brands like Microsoft, Amazon, and Google do. They have legions of talented workers and piles of money to spend on forward looking R&D, new products and experiments. Most companies don't have the talent, capital, or culture to pull this off.

The second pathway to success is more achievable. It's to exploit some change in your environment and ride that change with quickness and skill. I call this the sense and adapt strategy. A workforce that is data literate, who has been empowered by IT with democratized data is able to sense these changes faster than the competition, and adapt more effectively by leveraging data to build new capabilities and iterate them. The data literate workforce has strong opinions that are loosely held, meaning that they are engaged in continuous improvement and new opportunities, but that they allow data to overrule their bias.

An organization without data literacy is basically playing roulette. Your leadership may have good instincts, but betting on red will eventually fail you as a strategy.

Capitalizing on the Data Opportunity

Becoming a data-driven organization is a significant shift, but it is not impossible. First, you need to assess your organization's data literacy. Don't worry if most of the people in the business have no idea what it is, you're in the norm. People are going to need re-skilled for this to happen.

Second, in order for effective re-skilling, you need to enable a culture of learning. This means identifying the people in your organization who are eager to learn, empowering them, and celebrating them. Get these people into data literacy training ASAP. It's organization-wide, so paint a broad brush.

Third, of these initial re-skilled workers, some of them are really going to take to data literacy. They will find it fun and natural to incorporate good data principles into their day to day decision making and activities. These people are your data champions and a forward looking organization needs to move them into more impactful roles. These are also the people you want to take to the next level and move towards predictive analytics and data science. Frankly, the demand for predictive analytics and data science will far outpace supply in the coming years, so if you have data champions that have the talent and inclination, you need to build these resources internally instead of trying to buy them on the open market.

Finally, and most importantly, you have to lead by example. If your goal is to become a data-driven organization, that means all your leaders must allow themselves to be overruled by data. It also means asking the right questions when making decisions with your team:

• What does the data say?
• Where did the data come from?
• What kind of analysis was conducted?
• How confident are we in the results?

I cannot stress this enough: you must allow yourself as a leader to be overruled by the data. Saying you want to be data-driven and then ignoring the data sends a very clear message to your team and will do exceptional damage to the culture shift you are trying to make!

Eric Wise is the CEO of DriveIT, an experiential learning organization that assists with re-skilling business and IT professionals in data literacy, data science, and app modernization.