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Developing a High Performing Data Management Organization

These days, the hot analogy in the analytics industry is that “data is the new oil.” Like oil, data must be found, extracted, refined and distributed. More companies are investing heavily in cutting-edge technologies like machine learning, artificial intelligence and big data processing to help them harvest, groom and apply data to the correct use case for maximum value. So why, then, in the midst of this prospectors’ rush, do studies of business intelligence (BI) implementations repeatedly indicate that 60 to 85 percent of BI projects fail?

While tech is changing rapidly, the nature of most data management efforts has stagnated. Traditionally, the IT team has been seen as an all-knowing and all-capable “data priest,” producing the exact report requested by the business. We’ve seen businesses put a lot of focus on acquiring and storing data as cheaply as possible, while neglecting the equally important business use case and governance aspects. Because of this, we often see that data management organizations (DMOs) are not able to withstand the waves of change from sources such as new technology, organizational drivers and government regulations like the General Data Protection Regulation (GDPR).

Armed with that historical knowledge, I want to offer a few considerations for organizations to take into account when analyzing their DMOs.

Click here to read the full blog post.

Don Loden

ICYMI: Protiviti’s Brian Jordan Talks Data Mining

In case you missed it, click here to listen to a recent episode of the “Coffee Break with Game Changers” radio show, presented by SAP.

In this episode, Protiviti Managing Director Brian Jordan joined Marc Kinast from Celonis and SAP’s John Santic to discuss “Digital Footprints: Mining the Data in Your Operations.” Tune in to learn why Brian’s favorite movie quote is from Clint Eastwood: A man’s got to know his limitations.”

You’ll also learn why process mining is one of the hot trends in business intelligence today.

  Brian Jordan

Want to Increase User Adoption? Try This Simple FRA2MEwork

For as long as Business Intelligence (BI) has existed, organizations have made significant investments in high-performing platforms – only to find no one will use the solution. Why? For one, end users cannot find information quickly, or at all. Two, the information they do find isn’t relevant. Three, they expect their BI systems to work as effortlessly as popular search engines and social media, which yield results within seconds of a query, and the systems often don’t. So users drift away, the system goes stale, and the effort the organization has put into building the system goes to waste.

Getting the right information to the right people at the right time is intrinsically valuable to any organization. The ROI is not in how you drive your BI program, but in how effortlessly your organization can achieve a “nirvana-like” state where collaboration really happens.

To alleviate the user adoption issue, the Protiviti Data and Analytics group has devised a simple, six-step process that can be easily put in place to ensure organizations can maximize use of their data. The FRA2ME methodology adds the foundational elements organizations need to ensure that end-user adoption is not lost in the hubbub of building a state-of-the-art BI solution.

The FRA2ME Methodology

FRA2ME focuses on the importance of understanding end-user workflow and use cases to drive relevance, in turn ensuring usefulness and adoption. To understand the methodology, it helps to explain what the FRA2ME acronym represents:

Foundation

  • Creating a BI program that is trustworthy, performs well and is accessible when and where the end user needs it is essential to user adoption. Strong foundational elements, such as governance, speed, security and reliability, create user trust in the data.

Relevancy

  • A BI solution should focus on the business user, the use case and the desired outcome. The final solution put in place must be relevant for the purpose it was built to serve, or it will fall out of use.

Agility

  • We have learned that organizations need to build, adapt and perform outreach to achieve that nirvana state of collaboration. With an eye to the cadence of change, continuous improvement should be delivered incrementally to support end-user engagement. And, the technology required to support an agile BI team must be agile, too.

Advocacy

  • Gaining and promoting advocacy is a very important step in the FRA2ME methodology, accomplished through creative, well-defined efforts. One client internally branded their BI program to gain visibility, in turn generating advocates while growing adoption of the system. The client’s success was solidified by activities such as social media posts, competitions among users, and other promotions that encouraged users to try the new system. The goal: A scenario in which users say, “I can’t imagine my life before this solution” or “I can’t imagine living without this solution.”

Monitoring/Measuring

  • Keeping an eye on user activity and data usage is essential to establishing a positive track record for reliable data, in turn building the trust of business users.

Education

  • Training on new solutions should be situational, contextual and personal, which means using the kinds of training tools users relate to best.

At the end of the day, what organizations need is to delineate between information and insights. Information is, by its very definition, informative, and some information might be useful. But insights are actionable, adaptive and help achieve the desired objectives.

There are many areas where a methodology like FRA2ME can help organizations achieve insight, including:

  • Process optimization (“How will we anticipate and reduce costs?”)
  • Operational efficiency (“How can we increase sales and improve customer satisfaction?”)
  • Financial visibility (“How can we better understand and improve profitability?”)
  • Sales effectiveness (“What steps are needed to increase sales and improve supplier service level agreements?”)
  • Consumer behavior (“How can we engage our customers more effectively? What consumer trends are developing in our industry?”)

One Size Does Not Fit All

What BI solution is right for one organization may not be appropriate for another, and that’s where the FRA2ME methodology is particularly useful, as it helps pinpoint where to focus. One of our clients, for example, used the methodology to cut through the distractions of an upcoming IPO to quickly implement a real-time, interactive and highly intuitive dashboard providing visibility across 50 metrics and their related tolerances, all while launching a new manufacturing facility. The client saw 100 percent effectiveness in its first 90 days of operation at the new plant.

Another client, the fastest growing optical retailer in the U.S., needed to understand how to best segment and target customers while also determining when and where to open new markets. The FRA2ME methodology allowed us to identify how this client could effectively build a trusted data platform and implement customer analysis models that provided greater visibility into customer behavior for targeted sales and marketing campaigns, improved customer retention and optimized site selection for new stores.

A healthy, profitable company is in a constant state of change. And the cadence of change, at least from a BI perspective is this: Build, adapt, outreach. Build the solution that is best for current needs and resources. Adapt the solution and  the organization, as monitoring and measuring will define how well the solution is working and how the organization is responding to it. Outreach, by developing those advocates or “raving fans” who drive user adoption at the grassroots level.

To learn more about FRA2ME, download our white paper.

About Steve Freeman

Steve is a Managing Director – Protiviti’s Data Management and Advanced Analytics Practice. He developed the FRA2ME methodology to help clients generate “raving fans” among end users. Steve is also responsible for Protiviti’s SAP Analytics practice. He serves on the firm’s Financial Services practice leadership team. Steve has held numerous roles in sales and executive management in the Business Intelligence and Analytics space including: SAP BusinessObjects, Oracle, Verint and Cognos. A thought leader in analytics and end user adoption, Steve’s expertise also centers on Customer Insight Analytics, Sales & Financial Forecasting, and Organizational Optimization.

Categories: Data Strategy