FOCUS ON – Data Management Concepts for Sustainability (Part 1)

This article was written as an expansion of our white paper “Choosing Sustainability Management Software for your Business” published in July 2011.  If you’re looking for information on how to make your software selection, check out the full article.  If you just want to make sense of this particular topic, keep reading.  Whether you like this article or not, we want to hear from YOU so that we can continue to provide the best insight for YOU, our readers… 

Our series on Sustainability Software continues with “Data Management Concepts for Sustainability”.  In this article (Part 1 of 4), we’ll begin introducing and defining key Data Management terms.  Our end goal with this series is to enable YOU, as the Business Leader, to feel more comfortable in a technical discussion related to the various areas of Data Management, especially as related to the care and feeding of Sustainability Software packages. Being able to “talk the talk” is the best defense in the technology wilderness.  Just remember, at the basis of any technical term is a common sense business notion, and staying grounded to this notion will help keep your conversations from drifting astray.  Feel free to address any questions, corrections or concerns to john.redford@verdanthfc.com or jim.jones@verdanthfc.com.

Data Management

The definition provided in the Data Management Association (DAMA) Data Management Body of Knowledge (DAMA-DMBOK) is: "Data Management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets."  This term is the most general description of the collection of activities involved with data and broadly includes all the areas that we’ll introduce in this article.  If you’re really interested in more detail, check out the DAMA site at http://www.dama.org.

Data Processing

This is another very broad term representing the collection of plans, processes, people and technology tasked with the collection of transactional data (e.g. item sales in a company's retail outlets) and the subsequent calculation of summary data that has meaning to your business such as periodic sales reports.  This includes the routine computational work performed by your company's people and computers that generate output like your monthly customer invoices or accounting reports, for example.

Your Sustainability Software, in the ongoing state, would be supplied with data such as rigorous measurements of weights and volumes of raw materials and products (Collected Data) and the software installation will calculate the various indicators and reports for their respective uses (Calculated Data).  When discussing Data Processing, it is always a good grounding exercise to distinguish the Collected Data vs. Calculated Data being considered.  The two have different types of rules around them, which brings us to the next category of Data Management.

Data Governance

Data Governance is the management aspect of Data Management and has to do with identification and life cycle management of Business Rules connected with Data Management.  These rules might be driven by law, profit motivation, social norms or a myriad of other factors, but the establishment of definitions of terms and their existence in your company's soft assets is the foundation of Data Governance.  Examples of such rules include the following:

  • Meta-data Management is the collection of rules and definitions of the data elements used in your company.  It could be stored in a rigorous set of spreadsheets, or in an exotic, purpose-built system like Rochade from ASG Software.  Meta-data should have a dedicated team devoted to its maintenance and secure distribution to interested parties.  This team should include representation from both the technical side and the business side of your firm. 
  • Business and technical ownership of data quality standards for things like customer mailing addresses and formulae used in reporting. 
  • The clear specification of things like sales transactions and revenue classifications in the company's data streams. 
  • The identification and lifecycle management of your company's master lists such as store locations, product names and their reporting rollups, and a consolidated customer contact list across all lines of business.  This activity is referred to as "Master Data Management" and has taken on a life of its own by numerous software companies and consultancies but it is based on the common sense notion to "Keep your lists straight." 

Data Governance is like going to church, in that it is often postponed until there is enough confusion in the Business to make people desperate enough to try it.  It is definitely an endeavor that can start small, but requires the organization’s highest level of support.  Unlike some of the other topics presented here. Data Governance must be practiced within the confines of your corporate headquarters by your employees, perhaps augmented by technical consultants from time to time.

(TO BE CONTINUED…)

Now that you’ve read this article, tell us what you think!  And be sure to check out the full white paper.

ABOUT THE AUTHOR:  SSC and Verdant HFC are pleased to introduce our guest blogger and data expert, John Redford.  John has been involved with data, data management and data architecture for more than 25 years at companies large and small.  When not figuring out which database to put things in, he’s working to make birds happy – Wingdow.com, managed by Aleta Redford is the marketing channel for John’s latest in a string of inventions that he’s designed through the years, so he can relate directly to the challenges faced by YOUR business.