6 tips for solving business problems with data management tooling 

Date:April 20, 2023

If there is a problem with an organisation’s data, can a data management tool always fix it? It might do. But without addressing the root cause of the problem, the solution might miss the mark entirely. The above applies not just to data management tooling, but to any business scenario. A data management tool is usually purchased based on a need to get a handle on data, but it is easy to fall into the trap of implementing a tool-based solution and relying on it alone to solve your business problems. 

We have implemented a variety of data management tools – such as those offered by Collibra and Informatica – with clients from a range of industries, and many of them had one thing in common: they had significant data challenges that were not just solved with a data management tool. This article outlines some key pieces of advice for anyone looking to solve a business challenge with data management tooling. 

Prioritise data-sharing 

A good start for solving any business problem is ensuring company-wide engagement. Solving data problems should not be the unique domain of the data management function, as there are insights from across the business that are critical to understand. There might be some people who tend to protect certain information and treat it as their own, however openness and transparency is essential if you want to use your data to its full potential. This is not just because of information security principals, but because information hoarding creates single-person dependencies which is not a beneficial for any organisation. This applies to data management, so recognising and addressing any reluctance to share information can aid the success of a data management tool. 

Provide sufficient training 

When considering data management tools, ensure the business has no barriers to entry, such as lack of access or basic training. It is important that every user has a safe proving ground to explore, make mistakes, and learn. This means an environment that is open to everyone to test activities without fear of causing problems to the business. Sandboxed environments, or new environments that can be provisioned quickly, should be used wherever possible, and the status of each environment in use should be communicated clearly. This isn’t only needed at the start of setting out on a data journey, but should be a continuous discipline throughout.  

It is important that every user has a safe proving ground to explore, make mistakes, and learn.

Embrace the good and the bad 

There is often an inclination to only document or catalogue ‘good’ information in a data management tool, however this can cause further, more significant issues because it masks problems. Tools can abstract information presentation from the detail, and different versions of a data asset can be managed so that it can be included even if it is not complete or has issues. Statuses, views, dashboards, workflow, visibility controls and permissions can all be used to help control what is presented, and it means all the catalogue information can be ingested, including that which is considered bad. 

Look to the future 

Consider designing your data model based on how you want your future state to be, not as your organisation currently is. Conway’s Law says this is instinctive for organisations, but it is possible to actively move against this instinct. An ‘inverse Conway manoeuvre’ may be performed to model according to your desired position, and this applies as much to your data model as it does to any other system in your organisation. 

Consider complexity 

When thinking about processes to adopt when using your data management tool, be sure to consider how complex you need the process to be depending on the size and number of people in your team. For example, it would not be appropriate to design a complex approval process if only a small number of people would be proposing and approving assets. Think how the process would work manually if no tool existed, and data was a physical object in the real world. Would the team need a survey? Would they be required to vote for a resolution? Or would a simple retrospective approval be sufficient? 

Keep it relevant 

A data management tool is only ever useful if it continues to solve the important problems for business users, and these are constantly changing. Fatigue can occur when an application has been implemented and routines begin to develop. Shortcuts, workarounds, and active ignorance of problems might arise. Business users therefore need to be kept engaged, and this means not only listening to their feedback, but actively seeking it out. Evolve the tool based on the real problems from business users, not from only technical desires. Retrospectives might work in some scenarios, and surveys may work in others, but the important thing is to ensure the process is kept relevant for all users at all times. 

A data management tool is only ever useful if it continues to solve the important problems for business users.

There are many factors to consider when implementing a new data management tool, but by following these important steps you can help your business make the most of your chosen solution. Speak to one of our experts today to find out more about how Projective Group can help you solve your business problems using the Power of Data. 

About Projective Group

Established in 2006, Projective Group is a leading Financial Services change specialist. With deep expertise across practices in Data, Payments, Transformation and Risk & Compliance.

We are recognised within the industry as a complete solutions provider, partnering with clients in Financial Services to provide resolutions that are both holistic and pragmatic.  We have evolved to become a trusted partner for companies that want to thrive and prosper in an ever-changing Financial Services landscape.