The difference between running live and running behind: a shift from a federated to an enterprise-wide analytics approach

Jayne Landry,
Global VP and GM of Business Intelligence at SAP

Few things are as popular as a competitive differentiator as analytics is, especially in this age of disruption and breakneck competition. Advanced analytics can make the difference between which businesses are running live and which ones are running behind. Not all enterprises that use data and analytics to inform business decisions see the kind of success enjoyed by the high performers in this area. Less-mature analytics practitioners experience breakdowns at critical stages of the business initiative process, starting when they identify new business opportunities and model ways to act on insights to measuring the outcomes of their data-driven strategies. Incentives to correcting these problems are big — significant gains can be achieved in operating margins and revenues, and by improving risk profiles.

The democratization of predictive analytics
Traditional analytics has been successful in telling us what happens, but not so in showing us the reasons behind these events. Thanks to predictive analytics, this has started to change. Companies can now understand why something is happening and also what should be done to improve performance.

Traditionally, predictive analytics has been the data scientists’ forte. Now, however, it is embedded within traditional business intelligence applications, making it available to a broader set of business users. This is part of a larger trend — the blurring of lines between business intelligence, planning and predictive applications. Let’s take the example of planning. Once we create a plan, the next step is measuring that against actuals. In the past, this required a separate business intelligence tool. But today, capabilities have come together and end-to-end scenarios can be completed without having to switch tools.

In spite of the obvious benefits of analytics that have been discussed by many authors on this blog, it is surprising that many executives still rely on their gut instincts instead of data and analytics. But companies that use analytics extensively are outperforming their peers in terms of revenue generation, profits and market valuation. This makes it clear that our attitudes towards analytics need revisiting.

The journey to analytics success
One of the most important ways to achieve analytics maturity and success is to combine an enterprise-wide approach to data with resources that serve the unique needs of individual business units. Often, analytics starts at the business unit’s level – that is, when a department or team is trying to address a specific problem. It is important to address immediate department-level needs, but it is also important to ensure the approach can be scaled across the organization safely. Thus, the key to analytics maturity is moving from a federated approach to one that is organization-wide and benefits all business units.

Organizations also need close collaboration among business and technology leaders, and an enterprise strategy that is embraced by employees at all levels and departments. This enterprise strategy requires a portfolio of data and analytics technologies – for planning, data discovery and dashboards, predictive analytics, etc. It is also ideal if all of these components run on a single platform, so there is agility for individual use cases and also the trust in the data that comes from consistent management, security and governance.

To drive wider consumption and use of analytics for decision-making, a culture around analytics should be created. This starts with executive sponsorship and a business intelligence strategy that focuses on the objectives of the organization, the business needs and the desired business benefits. Once business priorities are defined, determine what KPIs are required to help you realize those goals, and the technology and organizational structures that will be needed to support it. And finally, measure everything to ensure you are on track and to help you “course correct” as needed.

For organizations aiming to achieve better analytics outcomes, here are five tips:

  • Combine an enterprise-wide analytics strategy with resources for individual business units
  • Bring together business and technical resources to define high-value analytics initiatives and develop project road maps
  • Delineate clear milestones and track KPIs on the basis of business requirements, then continuously measure the success of analytics investments
  • Choose integrated analytics platforms that address local and enterprise-wide requirements versus collections of point solutions
  • Evaluate the cost-savings and advanced capabilities possible with cloud-based analytics options

To learn more about SAP’s alliance with EY and how you could use analytics to solve your most complex questions, visit EY at SAPPHIRENOW in Orlando. From 16–18 May, EY can be found in booth 511 and helps you to answer the question — “Is your business running live or running behind?” Learn more on or follow @EY_SAP.

Legal disclaimer: The views expressed are those of the author only and do not represent the views of any of the member firms of Ernst & Young Global Limited.

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