The New Data Playbook: Automation, Mass Data Literacy

How will enterprise organizations scale Agile data and analytics programs in the future? Gartner says trust, diversity, and data literacy all will contribute to mastering tomorrow's complexity.

Jessica Davis, Senior Editor

March 8, 2018

4 Min Read

What do crowdsourcing, automation, and collaboration have to do with your enterprise IT organization?

These trends may be factors in the successful strategy of the future, according to three Gartner executives delivering a keynote address at the Gartner Data & Analytics Summit in Grapevine, Texas this week. They may help enterprises move beyond bimodal IT.

"For the last 3 years we've come on this stage and recommended a bimodal strategy," Research VP Kurt Schlegel said.

"...But we've hit a wall. Yes, we can do Mode 1 and we can do Mode 2 separately. Where we are having trouble is with the integration of Mode 1 and Mode 2."

Schlegel shared the keynote stage with Gartner Research Director Carlie Idoine and Gartner Research VP Rita Sallam.

Bimodal IT's history

Gartner introduced the concept of bimodal IT in 2014 -- essentially a system of two technology practices inside a single organization, one traditional IT services and the other one Agile, responsive, and fast. At the time it marked a way for non-digital native companies to compete in a new era.

Digital native startups like Uber and Dollar Shave Club didn't have to worry about their traditional IT holding them back because they never had that traditional IT. They were built on data-driven close-to-the-customer technology infrastructure that incorporated a customer feedback loop into their development programs.

Traditional organizations were still operating in the old model. Data was in CRM and other enterprise software systems. IT organizations serviced workers' desktop computers, networks, and servers; maintained and updated systems like ERP; operated years-long deployments and waterfall development programs.

Traditional companies couldn't just flip a switch to turn their old-line IT organizations into modern, fast-moving DevOps groups. The traditional IT organizations served an important purpose. These organizations didn't have a whole other budget to invest in emerging technology. But they still faced competition from digital native market disruptors like Uber and others.

Gartner said the answer was bimodal IT, defined as the practice of managing two separate styles of work: one focused on predictability and the other on exploration. Bimodal IT was the answer for organizations looking to compete in this new era.

The concept was embraced by some, and critiqued by others.

What now?

When it comes to data and analytics, enterprises are facing the following four challenges to become successful information organizations, according to Gartner VP Sallam: establishing trust, promoting a culture of diversity, mastering the complexity of running a digital business, and building the data literacy of the workforce.

In terms of trust, Sallam said that forces in the outside world became more relevant to data and analytics practitioners in 2017 as "fake news became a viable political weapon. Make no mistake, fake news is fake data, which makes it our problem. Ensuring data quality and providing a foundation of trust just became job number one for everyone in this room," she said.

Promoting diversity applies both to the workforce and to the data itself. "Creating a diverse and inclusive workforce is not just the right thing to do," Sallam said. "It's critical for data and analytics programs to flourish. Study after study shows [diversity] is critical to business performance and it's critical to innovation," Sallam said. It's also important to blend disparate data sources from inside and outside the organization and to mitigate bias of algorithms that are increasingly making our decisions, she said.

In terms of complexity, Sallam said that the self-service model is starting to show its limitations. "We've been so enamored in empowering the individual through data discovery that we haven't realized how manual that process can be," she said. Scaling self-service analytics through competitions and crowdsourcing can play a role in attacking the problems of complexity.

Finally, in terms of data literacy, Sallam noted that throughout history, knowledge has always started out being confined to an elite class such as nobles and lords and monks. When it came to reading and writing, mass education and literacy came later.

"As data and analytics become more pervasive, the ability to communicate in this language is a new must-have skill for the digital enterprise," said Gartner's Idoine

Organizations will need to address these challenges achieve success with their data and analytics programs. Once they do they will be able to shift from manual processes done by the few to automated processes done by the many, and they will be able to crowdsource their problems to a more empowered workforce, according to Sallam.

Empowering the workforce through diversity and data literacy will lead to more robust data and analytics programs.

So what will the data and analytics playbook of the future look like?

"We need to dump our original data and analytics playbook established by big ERP," said Schlegel said. "We need a playbook that scales from bottom up, based on work of many artisans -- small teams working on complex problems, each building low-risk prototypes."

About the Author(s)

Jessica Davis

Senior Editor

Jessica Davis is a Senior Editor at InformationWeek. She covers enterprise IT leadership, careers, artificial intelligence, data and analytics, and enterprise software. She has spent a career covering the intersection of business and technology. Follow her on twitter: @jessicadavis.

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