4 Best Practices for BI leaders to get advanced analytics initiatives off the ground: Gartner

4 Best Practices for BI leaders to get advanced analytics initiatives off the ground: Gartner

 

Getting started with advanced analytics is as much about changing mindsets and culture as it is about acquiring tools and skills, according to Gartner, Inc. Failure to make these changes can be fatal to success. Gartner predicts that, through 2017, 60 percent of big data projects will fail to go beyond piloting and experimentation, and will be abandoned.

"Many business intelligence (BI) and analytics leaders are unsure how to get started with advanced analytics, and many organizations feel they must make a significant investment in new tools and skills," said Lisa Kart, research director at Gartner. "But a successful advanced analytics strategy is about more than simply acquiring the right tools. It's also important to change mindsets and culture, and to be creative in search of success."Data Gartner has identified four best practices that BI and analytics leaders can use to get advanced analytics initiatives off the ground:

1. Choose a Business Problem That Offers an Initial Win

BI and analytics leaders need to work with business leaders to identify problems to tackle. Review with them the outcomes that drive the business and identify the decisions that could provide the biggest impact or, in many cases, the quickest payback. These may include day-to-day operational decisions, tactical decisions (such as planning), or infrequent strategic decisions (such as whether and when to enter new geographies). Wherever there is a lot of data, uncertainty and complexity, there is opportunity.

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2. Use Outsourcing and Buy Packaged Apps When You Lack Advanced Analytics Expertise

Many organizations assume they must continue on their current path with a centralized BI team and tools, and therefore build advanced analytics capabilities themselves. However, there are other options that are better suited to quick wins. Organizations that don't themselves have the skills to build advanced analytics can use external service providers who do, or buy advanced analytics applications to show the value of advanced analytics expertise for a particular problem.

3. Identify the Stakeholders in Your Organization That Need to Be Convinced of the Value of Advanced Analytics

It's essential to identify the internal stakeholders who need to be convinced. These are the naysayers, the skeptics, and perhaps the decision makers or those who carry out the actions. Not having them on board can derail any project. Having a business case that demonstrates the value is, of course, necessary, but it may not be enough on its own. The hardest task is to change people's beliefs and how they see the world — to get them to understand why they need to think or act differently. "Frequently, the success of advanced analytics initiatives comes down to the ability not only to deliver the analytics or communicate their value, but also to create a data-driven culture," said Kart.

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4. Decide If You Want to Build the Skills and Tools Internally

Businesses that achieve best-in-class advanced analytics solutions typically do so through a build strategy. However, building the skills and tools internally isn't for everyone, and it's often not the best way to start.

It makes sense for an organization to build advanced analytics internally if (a) analytics is a critical differentiator in its industry or if the area is of strategic importance, (b) a high level of agility and granularity of control is required, and (c) there are many opportunities across the organization to apply analytics in multiple use cases or lines of business.

BI and analytics leaders that do decide to build must have the three core skills needed for advanced analytics: Business skills: Apply analytics to the right problems and ask the right questions. IT skills: Access the data, identify the required infrastructure and execute the insights. Data science and quantitative skills: Take the right analytic approach to the data.

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Unfortunately, this skill set is rarely found in one person, but it's essential to have all three skills within a team.



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