Information is Power: How a Global Consumer Goods Manufacturer is Using Software Usage Data to Optimize its License Spend

by Amy Konary

IN THIS EXCERPT

This Excerpt is taken directly from the IDC Document, Information Is Power: How a Global Consumer Goods Manufacturer is Using Software Usage Data to Optimize its License Spend, by Amy Konary (doc# 222864). All or part of these sections are included in the Excerpt: Situation Overview.

SITUATION OVERVIEW

Case Study: Consumer Goods Manufacturer

The Company

For over 100 years, the subject of this case study (which wishes not to be named) has been a global provider of trusted brands across a wide range of consumer goods. The company has many trusted brands with $500 million or more in annual sales.

Like most large global enterprises, the company's business is complex. The company operates in 140 countries and has 148,000 software users worldwide. Around 12,000 employees come into or leave the organization every year. The company also participates in mergers and acquisitions every year.

The Business Challenge

Like many large enterprises, the software license landscape within the company is very complex. This is made more complicated by both the sheer number of contracts to manage (the company does business with around 1,500 software organizations for 2,000 applications) and the different types of licenses that must be administered, including node-locked, network licenses, and so forth.

The company already has an IT asset management solution that provides the services needed for regulatory compliance. However, the ITAM solution does not address the question, "How are employees using the software that is being deployed?" The answer to this question is the crux of software optimization at the company. Essentially, the company needed tools that could pull usage data from across the enterprise on a mass scale to help drive real-time analysis. The company initially tried to build its own, but the result was a patchwork solution that was difficult to industrialize and did not produce actionable information.

The Objective

As with most enterprises, driving inefficiencies out of the organization is a key objective of senior management at the company. Inefficiencies in the software supply chain resulting from a lack of visibility into software usage can often lead to overspending or spending in the wrong areas.

The company has already made a large investment in software, and it is focused on making sure its employees are getting the most out of the software that they have available to them and driving adoption of existing applications.

To address these requirements, the company needed to determine how its employees were using software, map this with the total capabilities that were available, and analyze the gap between the two. It was also important that the system obtain information to help drive business outcomes, including:

  • Maximization of existing software assets, and the establishment of an intelligent path for growth
  • Identification of stop-spend opportunities where pockets of complete underutilization exist

The company wanted to make sure that the systems and processes in place for obtaining this actionable information were institutionalized and repeatable so that usage could be tracked and managed on an ongoing basis. In addition, the company decided to focus initially on the enterprise agreements they have with large software vendors, including SAP and Oracle.

The Solution

There are two components to the solution. The first is designed to help analyze usage and identify pockets of underutilization and opportunity and is based on technology from Flexera Software. The second is structured to help make sure that optimization is an ongoing, sustainable activity and is led by business process expertise provided by Flexera and Accenture.

The Results

Before Flexera, the concept of "license optimization" did not exist. The way the company would manage licenses for SAP, as an example, is that every two years the company would spend three to four months collecting data on SAP licenses deployed on a base of 140,000 global users. An analysis would take place, and then the company would agree with SAP on what the license count and types should be. SAP offers seven different categories of users based on activity levels. It is easy to see how complex it would be to map 140,000 users to seven different license categories without having access to detailed usage information.In addition, since this process was not automated or institutionalized, the information gained during the audit was not useful to the company on an ongoing basis.