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Five Characteristics of a Data-Driven Company
The availability of big data, lightning-fast development of data analytics software, and increasingly inexpensive computing power have further heightened the importance of data-driven strategies for competitive differentiation.
In fact, Forrester's report indicates that data-driven companies that harness insights across their organization and implement them to create competitive advantage are growing at an average of more than 30 percent annually and are on track to earn $1.8 trillion by 2021.
Although many organizations have adopted business intelligence and hired data scientists, they still have considerable work ahead of them to become data-driven.
There isn't a single correct path to becoming a data-driven company, but there are common features and best practices shared by those who get it right. I've spoken to industry experts, including data leaders from General Electric, PandaDoc, FriendlyData, and SiliconAngle, to find these similarities. Here are the insights they shared with me.
#1. Creative executives who run their businesses with passion and curiosity
"Data-driven organizations are led by open-minded, creative executives who run their businesses with passion and curiosity," says Sergey Patsko, Engagement Leader, Data Science Services at General Electric. "I have the pleasure of working at GE with Fortune 500 companies advising them on data science and its role in a digital transformation.
"When they visit our GE Digital design center in California, we organize design thinking workshops and talk about challenges and opportunities in their industrial markets. What I observed during such interactions is that being data-driven is not the same as being metrics-driven. The majority of companies are metrics-driven; they have key performance indicators defined and they track them.
"Being data-driven is different. It requires a bit of a researcher's mindset -- the curiosity to dig into the data and glean insights from it that can be of use for the business. Not all leaders have this streak of keenness, but those who do are the ones who innovate with data-driven and outcome-based business models. They define how their verticals will look in the future, with data-first applications. Such executives are not waiting for incumbents to challenge them; they are disrupting their own markets with AI and data-driven processes.
"Look at what South32 is doing in mining, Schindler in elevators, Rosneft in Oil & Gas, or Exelon in power and you'll see very similar traits. Senior executives are personally involved in starting and leading digital transformations of their companies. They are willing to make bold moves and invest in IoT platforms to create an infrastructure that enables data-driven processes, and not just set the list of KPIs to look after. They are curious to learn from the data, and they challenge traditional, often empirical, approaches that exist within their own organizations."
#2. Data democratization
Michael Rumiancau, CEO at FriendlyData, says data-driven organizations emphasize the importance of broad data access for all employees. [Full disclosure: the author works at FriendlyData.]
"A data-driven company enables all members of the organization to have instant access to needed information in order to make data-driven decisions in a matter of seconds, not days," he says, - Today, people are hungry for information, and data-driven organizations understand the potential of data and feed their people by giving them access to the organizational data.
"At FriendlyData, we believe that all members of an organization, no matter their level of technical expertise, should be able to easily access data."
#3. Data literacy
An organization's ability to succeed in the digital era is heavily dependent on its employees' data literacy: the ability to read, work, analyze, and argue with data.
The brightest example of how a company can respond to a data literacy problem is Data University at Airbnb. At the beginning of Q3 2016, only about 30 percent of Airbnb employees were weekly active users of their data platform, 70 percent of employees were being held back. Airbnb could not have a data scientist in every room to inform every decision with data. They needed a solution that could scale to their 22 offices internationally.
To address this challenge, Airbnb started its Data University, data education for everyone in the company. Engineers, product managers, designers -- every employee regardless of role had a chance to learn how to use insights in decision making and how to analyze and visualize data using Airbnb's toolset.
Data University was a great success. Data education has completely transformed Airbnb's data culture. Employees learned how to handle ad hoc data requests themselves, and within a year, Airbnb almost doubled the engagement on its data platform.
#4. Automation of data management workloads
For James Kobielus, lead analyst for data science and deep learning at SiliconAngle, the core criterion for a data-driven organization is "whether it has taken steps to automate the distillation of data-driven insights and the incorporation of those insights into business processes."
"This is not a matter of getting everybody using manual approaches such as traditional business intelligence reports, dashboards, query accelerators, etc." James Kobielus says, "Manual touchpoints throughout the data management life cycle impede many companies' ability to ingest, aggregate, store, process, analyze, consume, and otherwise make the most of their data resources.
"You can't fully accelerate and optimize data-driven business processes if you don't comprehensively automate data management workloads. Automating the data pipeline can help companies execute transactions, make decisions, rethink strategies, and seize competitive opportunities better and faster."
#5. A companywide, data-driven culture
Becoming data-driven involves more than technology and tools. It also requires a shift in the enterprise's mindset and culture. Culture plays a central role in setting expectations about the extent to which data is democratized, how data is viewed across the organization, and how it is positioned among the company's strategic assets.
Richard Bray, VP of finance and operations at PandaDoc, shared how the company successfully built data culture into its corporate culture.
"PandaDoc's culture revolves around empowering everyone who works here to make an impact and to learn. We believe that having transparent access to data is one of the most powerful tools for our employees to make an impact and to learn."
PandaDoc has a team of six engineers and two analysts who built a sophisticated data infrastructure that is shared throughout the organization and provides easy access to data for everyone in the company.
"We have a website that any employee can go to at any time at their own desk so they can slice and dice the data however they need. Nearly every single aspect of our business is on that site so employees can see how their activities are driving change in the company," Bray says.
"They can analyze how the business is doing and if they don't understand something, one of two things can happen: they can learn how that particular aspect of the business works or they can discover something entirely new and bring it up, which gives them an opportunity to make an impact and change something for the better.
"Data-driven culture is intrinsically tied to PandaDoc's culture of making an impact and learning. What we are trying to create is an understanding of how the company works and the correlations between everyone's activities and the company's results. If you can see that by doing XYZ you are moving the company closer to its goals, you feel more connected to these goals. The work then becomes more fun because you understand how your activities are influencing the results. That's very powerful.
"If you want to build a data-driven organization, a data-driven culture has to be pervasive, the data has to be transparent, and everyone in an organization has to have the ability to understand how the business works and the ability to make an impact."
About the Author
Irina Peregud is the marketing director at FriendlyData where she is responsible for go-to-market strategy, messaging, positioning, content marketing, and sales enablement. Her professional mission is to help organizations become more data-driven through the use of innovative technology products. You can reach the author via email or LinkedIn.