Introducing Data Architecture (DA) in your company is not an easy task. You can be extremly conviced about its positive effects on the enterprise; however, at the very beginning of such a process, you may face stakeholder incredulity and actual doubts in its actual benefits. Using long-term and complex ideas, or academic vocabulary to explain such benefits may be interpreted as an “empty talk” or “making a story bigger than it is”. Not only because of the fact that probably only part of the managemet and few experts in the field undrstands you, but for justified reason that most of the stakeholders, including other part of the management, prefers to see tangible and easy understandable benefits. This article describes business values of DA that should be understandable and tangible for most of the people or stakeholders.
Cheaper and faster implementation of the projects
Data Architecture (DA) defines development standards and provides organized and structured information about data – just like GPS maps about streets and building. It can save enormous time needed to find information about specific data, thus, consequently reducing the costs of the projects. Especially in large and international enterprises: where the most of the project time goes to the clarification and analysis of the “status quo”.
Numerous meetings concerning identification of appropriate data objects between business and IT departments, and between IT architects and developers could be avoided. And not only meetings, but other resources needed for preparation of those meetings as well. Consequently, by getting needed information faster you’ll be in the position to complete your projects faster.
I actually worked on numerous projects with very similar requirements, done in same environments, and with the same people. Those implemented with the support of Data Architecture needed about 60% less PT resources than those without it.
So, to effectively convince your management that your enterprise needs Data Architecture, just put on the paper the actual resources (for example Personal Days) you could potentially save with it in next year or five.
Cheaper enrollment and easier training of the new employees
(Cheaper and faster retraining and requalification of the existing employees)
You may ask how is this possible, but DA really helps to reduce the costs of the enrolment and training of the new employees. Especially in enterprises which main business asset are data itself.
Without appropriate and well documented DA, a new employee, a BI developer for example, has to speak with every department relevant for his role about the data structure and their interaction with other applications. For every little dilemma or a question, there is a need to have a meeting or chit-chat with experienced IT developers, business department, or other appropriate persons. In some situations, it would be even hard to identify appropriate people a new employee needs to speak with. In heterogeneous environments without common DA, every department has independent and probably superficial understanding of overall data architecture. Such situations make it difficult, complicate and prolong the acquisition of the overall data architecture picture for the new employees as well. Consequently prolonging the time when a new BI developer actually becomes “really” productive in his job.
According to my experience, an average new BI developer needs between one and six months to get the holistic and clear picture of all relevant BI data flows in specific enterprise. In addition to this time, in the first few weeks a new employee needs support and dedicated time from senior BI developer; plus, numerous meetings with same scope that include other relevant IT and business departments. So, you get the picture.
With appropriate and well documented DA, all you need to do is to explain to the new employee how to find and use relevant documentation.
With a just one look on the appropriate map we are able to understand the complexity of the trip, places or cities that it includes, main roads, the optimal places to rest, approximate time needed, etc. Can you image the effort and needed resources for the same activities without appropriate map?!
A well done DA that includes all information from top to the bottom (and vice versa) would enable a new BI developer to understand a holist perspective of data architecture in couple of minutes instead of couple months.
Same rules apply when prequalifying or retraining existing employees.
Less conflicts, less frustration, less quitting, better productivity
Appropriate and well done Data Architecture can lead to fewer conflicts between departments, less frustration during implementation of the projects, and consequently to better productivity and even to lower fluctuation of crucial employees.
How?! Most of the conflicts related to the data-relevant projects are caused because different departments or teams have different understanding of data architecture, structure, or data relevant objects. So, in that case, they have different assumptions what is necessary to be done to fulfill business requirements. Unrealistic expectations from one side are sometimes understood as degrading for the other side. Explaining why is something not possible or not feasible in the exact way as wanted, leads very often to the frustration on the other side and vice versa. Such situations lead to a decline in productivity; and I witnessed myself when good employees quit because they felt too much stressed in such situation over long period. Finding a new appropriate employee, especially IT professional, can cost huge amount of money and time.
Data Architecture provides common understanding of data at enterprise level and clear development guidelines for data relevant objects. With DA, your company would not be in situation having different departments with extremely different understanding of data architecture, or different expectations regarding implementations. Existing DA would be used as a reference. Specific conflicts would be avoided and employees would be less frustrated. Consequently, the company would experience better productivity.
Easier know-how sharing, transparency, agility
Sharing the knowledge about enterprise data and its architecture is much easier in organized, structured, and well documented environment that includes, where possible, objects that visualize and illustrate abstract concepts. We all know the phrase “pictures say more than thousand words”. In the context of DA, it means, if we visualize organized and structured “abstract data concepts” through understandable diagrams or illustrations, it would be much easier for people to understand and accept them. It would be, as well, much easier to share the knowledge across organization and thousand times more effective than having unorganized documentation all over the enterprise. Such environments as well facilitate transparency when, where, and if needed.
Data-driven companies are more resilient and more flexible to changes if they have high-quality DA. How?! Business and technical people work together more effectively as they both have same overall understanding of DA. It is much easier for business people to deliver and to convey information from development teams when they understand the concept “from the view of the other side” – vice versa as well. Proper and well done DA supports the idea of continuous delivery of data relevant applications and welcomes changes.
Better and faster legal compliance
Most of the countries legally require from the companies to manage and use their data in structured, organized, transparent and understandable way. An example of such requirement can be identified within recent introduction of EU General Data Protection Regulation (GDPR) or BCBS 239. Implementing and complying with such requirements would be much easier and much faster if a company has appropriate DA. For example, a huge amount of time resources, used separately for every single recurring activity in the scope of legal compliance, could be saved with DA.
On the other side, as we currently live in the world where the use and the management of the data play more and more important role every single day, sooner or later, in five or ten years, a DA would be definitely a legal requirement for all data-driven companies, just as any other architecture out there – before even staring with the actual business.
This is not exhaustive list of all business values enabled by having Data Architecture, but, as written at the beginning, a list that should be understandable and tangible for most of the people or stakeholders. I hope you’ll find it useful.