It’s an understatement to say the recent COVID-19 crisis created all kinds of chaos. Organizations suddenly had dispersed their workforces across a corporate diaspora with uneven connections, had to adjust supply chains and planning to shifting realities, and even saw their sophisticated artificial intelligence systems being thrown out of whack.
If you’re involved with a virtual company — essentially with a highly distributed workforce and few directly owned physical assets — you may be weathering the storm with minimal damage — or even continuing to thrive.
If your business has been forced down the digital and data-driven path by recent events, you need a solid data foundation. A virtual business is, for all intents and purposes, a data business. However, despite advances in tools, platforms and self-service offerings, data-driven decision-making still isn’t as pervasive as it could or should be.
The time has arrived for data democracy — a term that’s come up frequently in recent years, but more on PowerPoints than in reality. In surveys I have designed and conducted in recent years, the full power of data analytics is usually available to no more than 10 percent of workforces. Data insights need to be available to everyone who needs them, regardless of where they are in the organization. On the production floor, technicians need to understand what’s going on inside machines. Call-center representatives need to understand customers’ purchasing histories. Financial managers need to understand order-to-cash dynamics.
A recent report from Constellation Research bears this out, concluding that “limited data access and complexity” still hampers the ability to thrive on data, “particularly for untrained business users more accustomed to analysis within spreadsheets.” A persistent gap between analytics and transactional applications isn’t helping things either.
What organizations need are ways to make “it easier for users without knowledge of data science or query languages to ask questions about data.” Augmented analytics — which includes AI, natural language processing, and embedded analytics may help close this gap, making data-driven insights more ubiquitous and easier for end-users to access, Doug Henschen, the report’s author, urges. “Not only will computer augmentation extend self-service to a broader base of users, it will also speed data prep, analysis and predictive work for more-advanced users.” Such applications and techniques harness heuristics, machine learning and AI technologies “to improve data access, suggest data sources and analyses, uncover latent insights, predict future outcomes and even suggest actions.”
Technology — AI, machine learning, data lakes — is important, but culture matters more than anything in establishing and running a virtual organization. “For a virtual organization to function, geographically dispersed teams need the ability to communicate effectively. But that’s only half the story,” Mike Walsh writes in a recent Harvard Business Review article. Data is the other half — and the key to successfully managing virtual businesses. “Decision-making has to be delegated and decentralized as well — and that means using data to shake up your culture.”
Just as participating in a democracy means assuming responsibility for your voting decisions, participating in a data democracy should mean actively promoting data literacy — “a hard-won skill,” Walsh says. “It does not come easily, even to a generation fluent with apps, emojis, and hashtags. To get there, organizations need to invest in dedicated training and education.” For example, companies should offer courses and coaching on topics such as machine learning and statistics across their workforces.
Thomas Davenport and Nitin Mittal agree, noting in a separate HBR piece that achieving data-driven success requires “culture that truly values data analytics capability and the superior decision making that can flow from it.” They point to a survey from Splunk of 1,300 senior executives found that more two-thirds, 67%, say “they are not comfortable accessing or using data themselves.” In addition, 73% “felt that data skills are harder to learn than other business skills, and 53% believe they are too old to learn data skills.” And these are the top executives who feel they can’t quite grasp data-driven decision-making.
Davenport and Mittal provide guidance how a data-driven culture can be built:
Emphasize hands-on training and education. “Experiential programs such as design thinking exercises, group problem-solving, and hands-on hackathons tend to be more effective than talking heads,” they state. “Position-appropriate exercises for staff at different levels — for example, executives can focus on framing the problem, and front-line employees can interpret the implications of analytics for customer relationships.”
Start at the top, but include everybody. “Cultural changes take a long time to mature, and culture is influenced over time by every leader who joins an organization,” Davenport and Mittal point out. “It’s important for someone to monitor changes in the data/analytics orientation of the leadership team.” At the same time, as Walsh points out, data democracy is essential. He quotes Wade Foster, CEO of Zapier: “You don’t need everyone to be an expert, but the real benefit starts to happen when every team has a data power user in it, which can help the team respond to new questions and challenges faster. And that increases the decision-making velocity that’s happening inside the organization.”
Encourage and incentivize data-driven decision-making. “Promotions and rewards can also encourage change. If those who make effective use of data and analytics get faster promotions and salary increases, others will notice. Of course, this approach requires leadership endorsement and sign-off and execution by human resources.”
This article originally appeared in Forbes.
