A Mid-Market Professional Services Company uses EA to govern data
- No information governance and, as a result, poor data quality
- Needed to capture the data flow between systems
- Needed an EA tool that could provide breadth, depth, and flexibility
- Established data governance and clear data lineage
- Established inventory and saved hundreds of thousands in application costs
- Created a single source of truth to strengthen EA practice
The company had no data governance and thus had dirty data
A midmarket professional services company must protect its intellectual property as its people's knowledge and skills are paramount to the revenue model. The Company decided to start at an elemental level and properly manage and govern its data. Metadata was not defined or worked across hundreds of applications, and over time, the data became very dirty and unorganized. There was no information governance, and data quality was poor and thus unreliable.
The Company decided it needed a tool that could identify which interfaces existed and capture the data flow between systems at a logical and physical level. After looking at various tools that could help with modeling and data governance, the Company felt many tools were built for larger companies and didn't fit its needs. In looking at the Gartner Magic Quadrant, the Company began considering enterprise architecture tools that could help design, define, and instill standardization and governance.
The Company met MEGA at a Gartner conference and watched a demo of the HOPEX platform. The project sponsor thought that HOPEX's ability to go to the field and physical level was beneficial. When the Company realized that HOPEX could connect not only systems but also identify their payloads, it was determined that HOPEX was the right tool for the enterprise architecture team. The platform could provide the right level of detail to help them govern their data, grow as a single source of truth with the Company as their efforts and needs evolved, and provide a substantial value for money spent.
Create a centralized EA repository to normalize and visualize data
Even though the Company's enterprise architecture team knew HOPEX was the right fit, the team needed guidance on leveraging HOPEX best to meet their objectives. To kick off the project, the MEGA team met with the main stakeholders to co-develop goals, approaches, and timelines. Based on this collaboration, the Company focused on the following:
- Started with Capability Mapping – The first thing the Company did was build a capability map so they could understand where and how technologies were supporting the business. This exercise gave the team the understanding of which applications they needed to use to standardize their IT Infrastructure Library (ITIL) portfolio.
- Reached out to Industry Peers – The lead project sponsor reached out to a network of his peers to validate the capability model the Company began to use. Together this group co-developed an industry reference model they could test and refine.
- Modeled data flow – Elemental to the success of this project, the team next focused on how information traveled across the Company so they could ensure they had some sort of interface to support the data.
- Conducted IT Portfolio Management – Once they mapped capabilities and modeled data flow, the Company could only see what applications and technology they needed to invest in and grow.
- Built internal awareness – As the enterprise architecture team built out the above, they connected with several groups and business units across the Company. As a result, when new technologies were requested, they were inserted in the approval process to validate the need.
A single source of truth that has set the foundation for data governance and IT modernization
The Company has used HOPEX for several years and has realized significant value from the completeness of the tool, including:
- Cost savings – The Company saved hundreds of thousands of dollars in technology by not buying products because they realized they already had a suitable alternative in the portfolio.
- Flexibility – One of the things that were most valuable to the Company as they could pick and choose the areas where they wanted to model at a relatively high level and those where they needed to go into deep analysis. For example, the Company is deep into application governance and using all the fields. At the same time, they are also modeling the costs of applications and only using a few areas and getting the right insights.
- Connected insights – The HOPEX platform provides flexibility to work on several areas simultaneously. The lead project sponsor says, "We are just starting an enterprise data map and now dealing with privacy legislation. We can connect these insights and do that all within HOPEX."
- Breadth of the HOPEX platform – Having all the different modules was essential, and the Company has used them incrementally. This took the risk out of purchasing the tool as it could help with many other use cases.
- Related information – The Company plans to use the interface connectors between HOPEX, ServiceNow, and Collibra, making it possible to share data without creating another silo. As the project sponsor says, "It's nice to know we have this capability in our pocket."
"It's easy to build a model but hard to understand how to build one that will drive value. Architects are tempted to go down every rabbit hole and note every interesting element in a relationship. But somebody who will give guidance on how other people have done it is paramount. MEGA's experience was critical to our success and to keep us from going overboard." Lead Project Sponsor
- HOPEX platform
- MEGA Services Team