Data Governance Challenges, Opportunities, and ROI During Technology Projects

Data Governance Challenges, Opportunities, and ROI During Technology Projects

StockSnap_GLWK56STOO_mountainclimber_projectchallenge_BPDuring technology projects there are many challenges as well as opportunities. And data governance and data intelligence can assist. Technology projects might include migrating to a new ERP, switching to a new reporting solution or adding a data warehouse. A technology project is a rare opportunity on its own where you need to evaluate and touch all your data and reports. In this blog post we will cover the challenges and opportunities of technology projects as well as the return on investment (ROI) of doing data governance along with these technology projects.

Examples of Projects Where Linkage with Data Governance Should be Done

  • Implementation of a new ERP solution
  • System integration project between systems
  • Migrating to a new reporting tool
  • Putting in a new operational data store (ODS) or data warehouse
  • Moving from one database to another such as a Colleague Unidata to Colleague SQL
  • Switching to a CRM solution
  • Performing a survey and reporting results


What are the challenges with major technology projects?

  • Often there are many moving people and moving parts to technology projects. And often the people involved are from different departments that have never worked together before. And sometimes they are not use to working on projects of this size or use to the project environment of communication, changing priorities and tight deadlines.
  • Data documentation and decisions on projects are often distributed and disparate versions with multiple owners. Maybe you have spreadsheets, Google docs, and SharePoint drives distributed between all the various team members and organizations in this project.
  • Training on the data and the building of the reports is often neglected to the last minute and needs to be done quickly and efficiently. It is not uncommon. If you are implementing a big system, that you are focused on getting that system live, such as making sure payroll runs, doing all that transactionally needs to be done. And oftentimes focusing on reporting and the data analysis part of it is left to the end and it is often rushed. 
  • Lack of effective reporting or data quality can undermine trust in any new system. For example, you implement a new system. But, if people are unable to get the data out that they need or they have the perception or the reality of bad data or data does not match their old system, it can undermine the trust in the new system. No matter the priority, emphasis and energy around the technology project,  if you end up suffering with bad data or lack of ability for people to get the information out of it that they need, you are going to lose trust in that new system. This is a particularly big thing with a new reporting or data warehouse project. And if they do not have transparency to how that information is generated, it is difficult for people to see trust in it.
  • If report or integration development is done by different groups, then that can lead to lots of duplicated and inconsistent work. If you hand out reports and integrations to different developers in different teams then they are going to work in their own areas with their own standards and templates.  This will lead to definition collisions and duplicated efforts. You might have two reports where some of the information is the same, but they are assigned to different people. And if they are not interacting with some centralized knowledge base around that information, there will be duplication.  The more that you can centralize the knowledge around the work that is being done, both, the decision making as you build it and what the documentation after it was done, the more efficiencies you are going to get.
  • If the reports or data do not look correct in the new system, a lack of transparency or understanding in the new process can further undermine trust. We have this black box with a bunch of reports in it. If you are not able to understand what is coming out of it, no matter how well you implemented the project from a transactional standpoint, you may get people who are not going to use it very effectively.


What are our opportunities here to tackle those technology project challenges?

  • If you go to implement a data governance solution or data government knowledge base, then maybe the first thing you do is ask people to look back and document or curate information, done in the past. You are going to have a hard time, because people do not really like to do that. The most cooperation and buy-in that you are going to get from people is if you ask people to document and curate as they build new things. This technology project is an opportunity where everything is going to be a new thing that you are building. You want to capture all that information. Documenting these decisions and specifications as you go is the best way to get a full data intelligence knowledge base that includes the purpose and explanations of the data and processes being developed. You get this powerful as-you-build curation documentation. This is happening anyway as people are making these decisions, it is just a matter of capturing it. You are not asking people to make all these decisions and to build it and then a year later, go back and refigure out what they did and document it. It must only be done once. In a fully integrated data catalog knowledge base, you get this concept of emergent content. In documenting a report that has pieces of data in it, maybe one of those pieces of data is employee status. You ask, "Does that exist in the glossary? Do we have that defined? Oh, it is not. I'm going to add it to the glossary,".  And then that gets defined in the glossary for everyone to access.  The creation of a glossary entry, data quality rule, or reference data that is often driven by report or integration development.  And connect the glossary entry to the appropriate data sytems for enhanced use in the future.
  • These technology projects also tend to involve most of the same stakeholders that would be on a data governance committee. If you do not already have a mature data governance organization, but you are about to go through this big implementation, you can often piggyback on the prioritization of bringing these people on the technology project team and say, "Let's take these people and make them data stewards,".  And taking into consideration that you do not want to present this as an extraordinary additional amount of effort over what they are trying to do, it should be supporting their current needs.
  • If you do take these people, and you identified them as empowered data stewards,  then it will help the team know who the right contact is for decisions. As you are taking these technology project team members and saying, "You are going to be the data steward. I'm empowering you through that data steward title, officially or unofficially, as being able to make decisions and approve them on your own. And also, it is going to be well known to developers if they have a question that you are the right person to go to for this." Often with these technology projects there is a lot of lost time and sometimes inaccuracies spent by people asking the wrong person or not knowing who to ask or things getting lost in that process.  Also, you need a dat governance process for escalation of conflict or collaboration when necessary.

Return on the Investment

What is the ROI if we do data governance and data intelligence during a technology project?

  • If data governance is done well, then you should be able to have more efficient work, you should reduce rework and duplicated work. With data governance there are some additional documentation steps but these steps will reduce overall project time and will have future value.
  • If data governance is done well, with greater data knowledge, you will get more accurate results.
  • Even with some additional work you are going to get more trust in whatever that output is and more use.
  • And you are setting the stage for the future.   If you miss this opportunity of documenting and capturing the knowledge of the data, of this new system, or this new data warehouse, or the new set of system integrations that you are building, then you are never going to be able to go back and document it with any level of completeness or accuracy. Individuals who are asked to document something hypothetically or something in the past do not do nearly as good a job as documenting something that you need to have built and use now.  Creating a data governance knowledge base for the future is critical and will benefit your organization.
  • There is the concept of the measure twice and cut one which fits here as well. If you are documenting and making decisions on things and you are putting a little bit of data governance, expertise, approval, and transparency to that, you get a better chance of fewer mistakes and better results.

We hope that you found this blog post useful regarding data governance and data intelligence when doing a large technology project at your organization. There are many challenges as well as many opportunities but the return on investment will be beneficial to your organization and the success of the technology project.

IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance, data intelligence, data stewardship and data quality initiatives. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.

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Jim Walery
About the Author

Jim Walery is a marketing professional who has been providing marketing services to technology companies for over 20 years and specifically those in higher education since 2010. Jim assists in getting the word out about the community via a variety of channels. Jim is knowledgeable in social media, blogging, collateral creation and website content. He is Inbound Marketing certified by HubSpot. Jim holds a B.A. from University of California, Irvine and a M.A. from Webster University. Jim can be reached at jwalery[at]

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