This content, written by Brian LaFaille, was initially posted in Looker Blog on May 18, 2020. The content is subject to limited support.
Being a “data-driven” company has become a key goal for many businesses in the last decade. Enterprises big and small want to use the vast amounts of information they collect to drive revenue and steer company resources towards future goals.
This can be easier said than done.
While most companies are amassing data at an unprecedented rate, many are struggling to a true “data-driven culture” that sticks. In this five-part blog series, we’ll explore why this is still a challenge for organizations today, as well as introduce an actionable framework for setting up a successful data program.
Defining data culture
Before going any further, let’s define what we mean by data culture.
As some of our Lookers have before, data culture can be thought of as
a community made up of data-driven individuals across all departments and levels. These communities are where everyone is empowered to use data critically, to make decisions, and start conversations rather than close them down.
The challenge with data culture
To begin understanding why building a data-driven culture is a difficult task for organizations to achieve, it seems fitting to start with data. The contains some revealing statistics about the issues companies have had with transitioning from data as a rear-view mirror tool to it becoming a proactive part of cultural growth and business strategy.
Amongst the participants in the survey were C-level technology and business executives from some of the largest corporations in the world, including: American Express, Ford Motor, General Electric, General Motors, and Johnson & Johnson. Even these mega-corporations, with all their resources and data teams, are having issues with transitioning to being data-driven.
After further examining the findings, here are some of the most revealing statistics:
As sobering as those numbers are, it gets worse.
The percentage of companies that identify as being data-driven has continued to decline over the past three years, going from
- 37.1% in 2017,
- 32.4% in 2018, and just
- 31.0% in 2019.
What makes this decline so surprising is that investments in big data and AI initiatives are actually increasing. 92% say the pace of their data and AI investments is accelerating, and 88% note an increased urgency to invest in big data. This amounts to big data and AI investments now topping $55 million, which is up 40% from 2018.
More companies are also hiring Chief Data Officers and building departments to specifically help manage and use their data effectively.
But even with all that, the data shows that adoption of initiatives, cultural resistance to change, issues with people and processes, and a lack of organization alignment around data goals are the biggest challenges companies face when trying to shift towards a culture that embraces and is driven by data.
Why cultural adoption lags
If you’ve been having trouble driving widespread self-service analytics adoption, it’s likely you are experiencing some of these same issues with your change management and processes.
A article written about the survey identifies some of the potential roadblocks companies that want to make the leap to being data-driven may encounter.
The pursuit of short-term financial goals pushing longer-term objectives like data-based cultures to the back burner is one possible roadblock. Additionally, large-scale digital transformation failures by high profile companies make executives wary to try similar transformations of their own. GE, Nike, and Procter & Gamble are just three examples of companies whose attempts at a cultural change didn’t achieve the necessary momentum to make the change stick.
However, opposite these hurdles and challenges to change are businesses with senior executives who advocate for the better and continued use of data for decision making. These leaders are invaluable to their organizations’ future relationship with data, but unfortunately, they are exceptions among their peers, not the norm.
So if leaders are failing to recognize the impact integrating data into operational workflows can have on an organization, what are some other solutions to this hurdle?
One idea is to take a more iterative, phased approach, tackling individual data initiatives within the organization rather than trying to change the overall organizational culture all at one time.
Companies can also try creating their own in-house educational programs that focus on teaching the importance and impact of using data effectively in different roles, including for front-line employees.
Establishing the right mix for change
Driving any sort of organizational change, including creating a data-driven culture, requires a mix of people, processes, and technology. By recognizing the importance of these factors and investing time in each so they can be a part of the plan for change, organizations can create a culture where everyone has the opportunity to lead with data-driven decision making throughout every part of the business.
In the next installment of this series, we’ll take a look at the foundation of a successful data-driven corporate culture: executive alignment.