7 keys to self-service BI success

Self-service business intelligence empowers business users to glean valuable insights from data — without IT intervention. Here’s how to make the most of this growing trend.

7 keys to self-service BI success
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Self-service business intelligence (BI) is becoming more popular, as organizations look for ways to make it easier for business users at all levels to glean insights from growing volumes of data.

Research firm Gartner in a January 2018 report predicted that by 2019, the analytics output of business users with self-service capabilities will surpass that of professional data scientists.

The firm’s survey of more than 3,000 CIOs shows that the IT executives ranked analytics and BI as the top differentiating technology for their organizations, and Gartner says data and analytics leaders are increasingly implementing self-service capabilities to create a data-driven culture throughout their organization.

“Self-service BI is an important capability of organizations today; it enables IT to put the power of data in the hands of employees every day,” says Michelle Vercellino, CIO at financial services firm IMA Financial Group. “Employees can ‘choose their own adventure’ based on the problems they are trying to solve, and have the ability to create individualized reports.”

Self-service can also increase IT efficiency and scalability by decreasing the amount of requests that come into the BI team for report generation, Vercellino says. “Additionally, it allows business users to conduct real-time analysis on information for client needs,” she says.

For food and agriculture company Cargill, one of the biggest benefits of self-service analytics is that those closest to the data can quickly ask and answer their own questions.

“A centralized IT group may struggle to uncover insights at the pace of the business,” says Mitchell Grewer, coaching lead for self-service analytics at Cargill, which uses a BI system from Tableau Software. “With self-service, the power is distributed to those who know the data best. Self-service [BI] helps close the loop between data creation and action, and those acting on the insights are much closer to those producing the data.”

That creates increased accountability, higher quality data, and people who are invested in and care about their data, Grewer says.

Launching a self-service BI strategy is not without challenges. Here are some best practices to help ensure success with these initiatives.

Start by setting priorities

What is the organization actually trying to achieve with self-service BI? Without knowing this, achieving success becomes elusive.

“In our case, we wanted to make it easier for county employees to do their jobs, and also allow citizens to help themselves to information about county services,” says Rafael Mena, CIO of Orange County, Fla.

The county depends on a self-service BI environment to help residents and visitors stay connected with government services. Its analytic portal saves time for government workers, supplies critical information during hurricanes and other emergencies, and increases government efficiency, Mena says.

The county used Information Builders’ WebFocus BI platform to create an intranet portal that allows county employees to view data through real-time dashboards. They can issue queries through pull-down menus and drill into interactive charts and graphs.

The BI environment is based around “simple analytic apps that help users at the point of decision,” Mena says. “Unlike traditional tabular summaries and columnar reports, [the platform provides] a virtually unlimited number of ways to ask questions and get answers within specific business areas.”

Define the value of self-service BI — in business terms

Companies need to define the benefit or value of self-service BI in business terms, not IT terms, says Josh de la Cuesta, vice president of IT and CIO at lighting products provider Lumileds.

“For example, the number of users of a new BI tool does not establish or define value for the business,” de la Cuesta says. “The definition of benefit and/or value should be in business terms: faster response to a customer, [reduced] cost of new product development, time saved across the business, etc.”

If a company can’t define the benefit or value of a new system or method in business terms, it might want challenge the assumptions that are driving the need for the new system or method, de la Cuesta says.

Once the benefits are defined, IT needs to communicate the capabilities of self-service BI and manage expectations. “In addition to communicating to the business what self-service BI can accomplish, there should also be clear messaging about the limitations of self-service BI, including the definition of ‘self-service,’” de la Cuesta says.

Assess the needs and capabilities of business users and departments

Companies should evaluate their business users’ needs and technical abilities before moving forward with setting up self-service BI, Vercellino says. You can’t assume everyone will be at the same level of ability or acceptance of self-service, and an assessment will help in creating a roadmap for deploying tools and initiating a program.

Just like with individuals, departments or lines of business will vary in terms of where they are at with the need for self-service BI.

“Start with business units that request a large volume of reports that could easily be generated if self-service existed,” Vercellino says. “Identify technically savvy super users to be early adopters of self-service, and who will be a champion of the overall BI efforts.”

Look for the problems with reporting that cost the organization time and money and determine how self-service could increase productivity.

Implement a solid training program

Give every employee involved in BI a hands-on walkthrough of a self-service BI application.

“In a self-service model, training can make the difference of success vs. failure,” de la Cuesta says. “By definition, a self-service model is going to rely more on the user of the application to be more independent and proficient with a new tool. Getting to the optimal level of proficiency will take training and time.”

“If self-service is important enough to invest in, it is important enough to train for as well,” adds Hyoun Park, principal analyst at consulting firm Amalgam Insights. “This doesn't have to be long, but even 15 to 30 minutes spent on having each employee understand how to start accessing data is important.”

Build short training modules for key challenges in each department, Park says. “This means that departmental managers need to commit to recording, say, two to three short videos that will cover the basics for self-service,” he says. “Service managers might be looking for missed SLAs [service-level agreements], while sales managers look for close rates and marketing managers look for different categories of pipeline.” But across these areas, the point is to provide a basic "how-to," so users can start looking for the right answers.

Along with training, drive a culture of curiosity, Park says. “Self-service BI is only as good as the questions that people ask,” he says. “In a company where employees are either set in their ways [or] not focused on continuous improvement, self-service BI just becomes another layer of shelfware.”

Take advantage of low-code tools

Low-code tools, with interactive and intuitive design that enable virtually any user with minimal or no training to generate insights from data, can play a significant role in enabling self-service BI at organizations.

“As a company moves up the maturity curve of digital transformation, low-code tools can be an effective way to support BI,” Vercellino says. These products “can remove the technical complexities that exist with traditional development time, and allow business users to create on-demand reporting,” she says.

The tools also allow for changes to visualization and displaying of data, based on the business user and client needs. “Low-code tools ultimately accelerate delivery [of benefits] to the business,” Vercellino says.

“The average person doesn’t know how to code, but the average person has access to data that contains powerful insights,” Grewer says. “Instead of our colleagues investing in coding skills, they are able to focus on asking powerful questions, distilling potent insights, and taking action.”

The self-service analytics team at Cargill “can help eliminate the binary classification between data people and non-data people,” Grewer says. “Instead of data people, we’re able to create a data culture. Low-code tools make data-driven decision making accessible to everyone, allowing the masses to see and understand their data.”

Don’t neglect data management or security

Self-service BI does not mean there is no longer a need for data management. Organizations need to take steps to ensure that the right data is being accessed by the right people, and that policies governing proper use of data are being followed.

“It all begins with marshaling the data,” Mena says. “You need a sophisticated data-management environment and security architecture to make this type of system effective. Our BI tools uphold organizational security by agency and role, with complete data integrity.”

The WebFocus platform Orange County uses can integrate different databases, retrieve the data, run computations, and provide it in a way that users can easily view and understand, Mena says. “It also delivers alerts,” he says. “When we receive a request, the system creates a work order that’s delivered to the proper department, so we can address the issue immediately.”

Focus on community

Many organizations establish centers of expertise for areas such as data analytics. But that might not be the best way to share experience broadly throughout the enterprise.

“I argue that you don’t want a center of expertise, but rather a community of expertise,” Grewer says. “By creating a self-sustaining community, knowledge is distributed across your enterprise, removing dependence on a single organization and creating a powerful network of masters.”

As part of the community-building effort, organizations should give users more latitude so that there’s a greater likelihood they can feel empowered and enjoy what they’re doing as well as be productive.

“Make it fun,” Grewer says. “Data and technology aren’t enough. Empower people to experiment, find quick wins, and change the way they work. This is critical to building a data culture.”

Cargill enables everyone in the organization to be “citizen analysts,” because it makes more sense to teach domain experts how to use an analytics platform than it does to expect a handful of IT staffers to master every business domain in which the company is involved.

These citizen analysts, over time, also become the subject matter experts (SMEs) on the analytics platforms, tools, and methodologies they use to explore data, says David Walker, platforms lead for self-service analytics at Cargill. That, in turn, reduces the reliance on IT for support.

“Somewhere along your analytic roadmap — sometime soon — you will realize that [the] citizen analysts making data-driven decisions from self-served analytics have become ubiquitous,” Walker says. “And you will realize that you have succeeded in establishing self-service analytics as an integral part of your company’s culture.”

Copyright © 2018 IDG Communications, Inc.

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