Creating a Data-Driven Culture
To unleash the creativity of your company, unleash the data
One of the single most powerful steps a company can take toward the new way of work is transitioning from opinion-based to fact-based decision making.
However, many companies aren’t making that transition, at least not yet. And it’s not enough to announce a transition like that. First, the company has to adopt the practices and technologies of a data-driven culture, which also means transitioning away from earlier approaches to planning and strategy.
And of course, better technologies have to come to market, like the announcement made today by IBM about industry analytics solutions (see IBM Analytics for your industry).
Here’s some of the steps that are essential, across the dozens of case studies I’ve researched in recent months:
Metrics at the core of organizational culture — companies as disparate as Amazon and Etsy have made turning data into metrics the foundation of operations.
Etsy went through a top-to-bottom rethink of operations when they realized they had scaled up their community of buyers and sellers, but they lacked insight into what was going on. The CTO, Elliott-McCrea said,
It was a working business. It was a great community. It was making money. People loved it. But we weren’t able to support change.
They started with just five metrics, and now Etsy tracks hundreds, and manages based on the facts that emerge.
When I showed data to prove the opportunity, I had approval. Bezos told me to run a live test, and from that simple decision we found a billion dollars. Amazon Advertising now accounts for about $1 billion annually. — David Selinger
Companies should start at the core operations of their business — like supply chain data for manufacturers, or sales data for retailers — and establish a flexible business intelligence and analytics capability, that can grow across the companies total operations. This has to ultimately cut across all departments, functions, and initiatives.
Top-down and Accepting — Yes, executives have to endorse a data-driven way of business, and accept the fact that opinions — even those of very senior executives — come second to facts on the ground.
Jeff Bezos is a great example in this regard, as David Selinger relates how Bezos would put aside his gut reactions to new ideas if they were supported by data:
At Amazon, one of my proposals was to sell advertising on the homepage, and Bezos’s initial response wasn’t positive: “It is one of the stupidest ideas I’ve ever heard.” Yikes.
Nonetheless, when I showed data to prove the opportunity, I had approval. Bezos told me to run a live test, and from that simple decision we found a billion dollars. Amazon Advertising now accounts for about $1 billion annually, one of Amazon’s most profitable services and a battlefield on which they’re rumored to be taking on Google.
This is a place where the expression ‘strong opinions, loosely held’ comes into play. Like Bezos, it’s fine to have strong opinions and to voice them. But the willingness to change your opinions when confronted with new facts is critical in our fast-changing world.
Bottom-up and Open — It’s essential that data and analytics be freely available to everyone in the company, as well as tools to explore ideas about their application.
The willingness to change your opinions when confronted with new facts is critical in our fast-changing world.
Selinger’s probing at Amazon led to a billion dollar line of business, and if he hadn’t had access to the data to convince Bezos it might never have been attempted. What money is your company leaving on the table, because some front-line worker has no access to customer data, or a foreman in the factory can’t see far enough into the pipeline to propose a useful — and cost-saving — optimization?
As an added stimulus to moving toward a data-driven culture, there’s evidence that companies can keep head count low by making more data accessible. As Christopher Mims found,
Startups are nimbler than they have ever been, thanks to a fundamentally different management structure, one that pushes decision-making out to the periphery of the organization, to the people actually tasked with carrying out the daily business of the company. And what makes this relatively flat hierarchy possible is that front-line workers have essentially unlimited access to data that used to be difficult to obtain, or required more senior managers to interpret.
By breaking this data bottleneck, companies can move faster and eliminate managerial positions that were chokepoints on innovation. So we will be seeing less middle managers who gather and distribute data, because in the data-driven company everyone can do that.
This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM’s PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.
This article is crossposted at PivotPoint.