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The Big Cost-Transparency Challenge: Data

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by Bryan Mueller

For most IT leaders with financial management responsibilities, the value of cost transparency is self-evident. But we all know the biggest obstacle to achieving cost transparency is the availability, reliability and timeliness of data. For today’s enterprise, the importance of capturing and analyzing the right data grows in direct proportion with the increasing complexity of its IT environment, especially one that has more and more as-a-service offerings.

The regular flow of financial data is often the starting point for financial management, but the systems and processes that generate this data can fail to provide the insights needed to help manage costs. When financial systems capture the cost of a particular software buy, for example, accounting rules and financial policy designate the purchase either as a depreciation, a software expense, a maintenance expense or as an outside service, depending on the specifics of the purchase. And traditional financial systems often fail to capture other valuable transactional information, such as type of license, volume purchased, volume used or benefits gained from the use of the software.

Developing a solution to achieve cost transparency requires more than simply attempting to capture better data, it requires an understanding of why the data you currently have doesn’t meet your needs and a comprehensive approach to identifying what data you do need.

Enterprises that would like to begin a cost-transparency initiative should first consider the following:

  1. Glean what insights you can from the data you already have. Begin with available financial data and identify operational data to which it can be matched, including projects, assets, service desk tickets and applications. This exercise will help you begin to discuss financial data in the context of the underlying driver of the cost, rather than the type of accounting cost identified in the financial systems.
  2. Develop a strategy to articulate how you will use information to support decisions or better understand cost in a business context. Identify where data gaps exist, such as the number of operating system instances, and understand what data is most valuable to have.
  3. Fill the gaps. Embrace technology and tools that help you find, clean, organize and transform your data. Determine the value of your missing data as part of developing a business case for investing in technology that addresses the gaps.
  4. Don’t wait for the perfect technology to be in place; create processes to immediately inject the data you have into planning and decision-making processes. Build spreadsheets that capture relevant information, ensuring this information includes both the cost and business drivers, and use these to better understand how data will improve processes like demand management, chargeback and capacity management.
  5. Ensure your operating model supports the resourcing needed to make data a focus and develop and promote skills, especially analytical skills, so you can create and use the data made available.
  6. The true power of data is in its analysis. Begin to develop key performance indicators (KPIs) that are meaningful to IT. Then benchmark your costs to the market and create a services view of IT cost so that you can drive better decision-making both within IT and across the enterprise.

ISG helps enterprises build systems and create organizational change to better capture and analyze data even in an increasingly complex IT services market. Contact me to discuss further.

About the author

Bryan is a Principal Consultant in the Banking, Financial, Services, and Insurance Vertical and contributes to the ISG TBM (Technology Business Management) Practice. He provides critical business insight to help clients develop strategies and achieve business outcomes.