5 Greatest Pitfalls Of Data Management Programs


Reshaping the traditional Data Management Programs for Better Results

The Data Management field is novel and practitioners are struggling to architect programs that drive operational integrity, give organizational credence, and enable program sustainability.

Nine out of ten data management executives interviewed by us revealed that the full value of their programs is not well understood in their companies. Inability to connect with thestrategic valueis hampering the adoption of the programs and the growth potential of the field. After nearly a decade of achieving mixed results, there are now fresh insights into how to reshape the existing programs or design new ones.

Nearly all of the existing programs have now run into the same brickwall. To truly achieve their full potential, almost all of the existing programs would now need an overhaul. The early stage programs can avoid the same fate by learning from others. The body of knowledge and other guidelines were developed to introduce the field and don’t provide guidance on how to implement and structure your programs. Not many examples of successful programs are available.The absence of practical solutions often leads tocritical failures.

Specifically, five areas need complete overhaul: 1) Connecting the programs with demonstrable, hardcore business value; 2) Going beyond the governance mindset; 3) Modularizing the program; 4) Deploy an integrated end-to-end software solution; and 5) Making the program scalable, consistent, permanent, and sustainable. These areas impact the credibility, legitimacy, and sustainability of the Data Management programs. The solutions proposed in this article are practical, based upon real world experiences, and designed to address the above critical failures.

A friend (who is the CEO of a Fortune 100 company) jokingly commented that “it is impossible to measure the performance of data management professionals without having a deep sense of compassion and sympathy”. They work hard, they know that what they are doing is extremely important, they try to overcome budget and change management hurdles – and yet every time they meet with senior executives they have to resell and reintroduce their programsall over again – even if they gave the same exact pitch to the executives hundred times before. When marketing, sales, supply chain, or operations departments seek funding, they don’t have to explain who they are and what they do. But when it comes to data management, it is as if you are talking to the wall. And then after spending millions of dollars and implementing the programs for many years, you find out that only a few people are actually benefiting from your years of hard work.

We specialize in launching enterprise level successful data management, business intelligence, and big data programs – and while we do feel both sympathy and compassion, we know that solutions exist to address the overall existential and legitimacy issues of the data programs. The problem is that data management professionals have not addressed the five greatest critical failures of the data management programs.

Pitfall 1: Where is the Business Value?

Sales and Marketing increase the revenue line,while operations and supply chain focus on cost management and operational excellence. Both contribute directly to the bottom line. But when it comes to Data Management programs, we often fail to connect our scope of work with the bottom line. As a consequence, we are often perceived as a department comparable to legal, internal audit, accounting, procurement or HR – departments that were once viewed as overheads. In order to prove their value to the business, audit took over the responsibility of business process improvement in addition to regular financial audits; accounting redeemed itself by focusing on management accounting and cost management, in addition to the traditional bean counting; procurement transformed itself into strategic sourcing and supply chain management and saved billions of dollars; and HR introduced metrics such as return on investment on talent. The problem is that Data Management organizations have completely failed to connect their services with the bottom line centric business value. Several data management programs were born as a response to waves of new compliance and regulatory swings. While compliance centric programs are necessary, the real contribution of true information management comes when it creates real strategic value.

Solution: Don’t focus on what Data Management is;focus on what Data Management does. Link it with revenues, costs, and risks and apply measures to evaluate the actual impact on shareholder or other stakeholder value creation. We have developed and successfully applied a methodology to determine the value impact of Data Management and Business Intelligence programs. Make this the first step of the program. Don’t do it as an afterthought. There is a scientific way to do this and if you do it right, it will give instant credibility to your program.

Pitfall 2: Are you still trapped in the governance mindset?

Your presentations regarding data management’s value keep falling on deaf ears. You receive these blank stares and even when people get what you are trying to do, they gently smile and shake their heads as if saying “ok, another one of those compliance activities.” They are not mistaken. The problem is ours and of the body of knowledge that has made the entire field of data management academic, overly complex, and compliance centric. We are viewed more as a big brother than a co-value creator. Use the word governance and you have already lost respect in the eyes of all those who contribute to the bottom line of the business. Do you really expect key executives and leaders to stop doing their day jobs and become custodians, trustees, and stewards of data without giving them anything tangible in return? Let’s get real here. You can only expect people to participate in your programs if you can clearly demonstrate what is in it for them.

Solution: Your job is not to be a big brother, carry a whip, and seek compliance. If you want to be successful, you need to make your programs such that businesses and departments in your company naturally gravitate towards you. Instead of calling them “Governance Programs” when we implement these programs we ask our clients to call them “Operational Integrity Improvement Programs”.We design the programs in such a manner where they are tightly integrated with business processes and outcomes. It goes back to the first point, focus on what data management does, not what it is.

Pitfall 3: Is your program structured and modularized?

Developed by the academics and adopted by newly founded organizations, the body of knowledge and the data management bibles address every possible avenue of data management activities. Even though they are as detailed as encyclopedias and phone directories, when it comes to applying a practical, pragmatic methodology – there is nothing to guide us. So while you get a universe of information – you don’t find out where to start or what would be step 1, step 2, and so on. You don’t get answers to how to prioritize and get insights into functional and activity interdependencies. This is analogous to you asking someone on how to bake a cake and they give you a comprehensive encyclopedia of the food industry. By referring to the encyclopedia you can learn a lot about the food industry, but what you would not learn is how to bake a cake. As a practitioner you need to know how to launch a program in a systematic and programmatic manner.

Solution: We have designed a five step program that can be used to implement a comprehensive, end-to-end program for Data Management. This program has the following steps: 1) Link to Value; 2) Discovery; 3) Shielding; 4) Monitoring; 5) Innovating. While all the “under the hood” parts such as governance, master data management, metadata management, data quality etc. are included in the program – our unique program focuses on “what data management does, not what it is”. It prioritizes and implements the program efficiently in such a manner that the activity interdependencies are understood. Again, your customers don’t need to know about the details under the hood – they only need to get the driving pleasure.

Pitfall 4: Are you using end-to-end automation?

Ask for a Customer Relationship Management (CRM), or Enterprise Resource Planning (ERP), or Supply Chain Management (SCM) program and you get standard software in terms of functionality and business process. Regardless of which vendor you call, the fundamental functionality would be very similar. Now try implementing Data Management software and you would hear hundred different stories. Middleware suppliers would call their data access tools as Data Management software. Knowledge and Document management systems would classify their tools as Data Management systems. And the list goes on and on. The problem is that no one has been able to build and deploy integratedend-to-end Data Management software. The reason no software has emerged in the field is because software can only be developed when a business process materializes – and data management processes as presented in the body of knowledge encyclopedic styles don’t lend themselves to be programmed into software.

Solution: We have designed and implemented a product that can achieve the end-to-end goals of a Data Management program. It goes hand in hand with the program and follows the exact 5 steps of the Data Management program presented in Pitfall 3. The software accomplishes total automation of the processes and has the power to demonstrate business value on an ongoing and consistent basis.

Pitfall 5: Achieving Consistency, Scalability, and Permanency

Is Data Management a fad? Would it disappear into the folds of corporate overhead augmenting programs or would it emerge as a value added business function that is there to stay? Given the manner in which data management programs are implemented at present, clearly the answer to this question is uncertain. But that can change! We need to figure out how to achieve scalability and permanency of the programs.

Solution: If you follow the program steps as indicated in the first four critical failures, the program will become both scalable and sustainable. In addition, you must innovate and expand the program to include business intelligence and Big Data projects. This would imply going a step farther than any program has gone to date. We have a comprehensive plan that links the successful data management programs of today with the vision for tomorrow. This plan is being used by some of the world’s leading organizations.

In summary, the greatest critical failures of Data Management are common and across the board. They impact both the credibility and legitimacy of the programs. The core problem is that as a field we have focused on what “Data Management Is” and not on what “Data Management Does”. By implementing the above five solutions and our product – you can power your programs to achieve what every data management program must be designed to achieve: delivering measurable business value, a significant reduction in time-to-value and tangible return on investment.