“How should we structure our data quality team?”. This is one of the most common questions organisations typically face as they attempt to mature their approach to data quality management.
As companies move from data quality denial, to fire-fighting and eventually onto a governed strategy they will continuously face the problem of how to shape and scale their data quality resources.
The simplest way I’ve found of answering this challenge is to apply the concept of an “internal data quality business”
Steps to Building Your Internal Data Quality “Business”
Step 1: Defining the Data Quality Vision
All businesses must start with a vision that sets a course for the future and your data quality team should be no different. A useful technique is to invite everyone to share what vision they hold for the team. Perhaps the vision is to create information that routinely wins awards as the highest quality data in your industry. Whatever the vision, it must be something clear and empowering.
For example, Tele-Tech enlisted data quality guru Tom Redman and together their vision was cemented around “unparalleled quality”, i.e. no-one in their industry would have better quality. They went public with this goal and their whole website explains their passion and vision around data quality.
Some aspects to consider during this step are:
- What is the goal of the business?
- What are we trying to achieve?
- What does future success look like?
- How do we know we’ve reached our objectives?
This is equally applicable to your internal data quality “business” because without a clearly defined, publicly accessible vision it can often be difficult to foster change that everyone can get motivated behind.
Some real honesty is required here. If the vision of senior management is to cut staffing levels by reducing scrap and rework waste then your fledgling data quality business is off to a shaky start.
Also, I would advise that the vision does not just focus on data but on the most important asset of your business – the customer. Tele-Tech were obsessed around improving the quality of data because they knew this would instantly benefit their customers and make a definitive statement in the marketplace.
How will working towards your data quality vision impact your customers? Make sure this is a key component of your vision for your internal “data quality business”
We also need to work out what our mission is going to be for the business, Steve Sarsfield recently provides a neat article on how to do exactly that.
Next we need to assign some leadership roles to our “data quality business”.
Step 2: Take Me To Your Data Quality Leader
The “CEO” role is an obvious starting point. Who is the captain of your data quality ship?
Importantly, note that your leader does not necessarily need to be a “data quality guru”. I meet many data quality leaders who openly admit to having had basic training in data quality. The successful ones however all share one trait, passion. They are passionate and committed to delivering positive change. Look for this in your appointments because data quality techniques can obviously be learned but passion is mandatory.
Tip: We talked in the past about the need for more data quality change agents. These people can make excellent Data Quality leaders as they have can deliver passion, drive and vision to set the business in the right direction.
Step 3: Creating The Data Quality Business Case
Next we have the Finance Director of your data quality team. These people are responsible for monitoring and reporting the financial performance of our business and helping the leader devise tactics and strategy.
In a data quality team this function is one of the most important roles but so often ignored. A good data quality “CFO” will ensure that any service offered by the business is routinely monitored for bottom line gains so that the “shareholders” (i.e. the sponsors and project customers) are receiving ongoing value for their investment.
Regardless of whether your sponsor asked for a business case, I always advise teams to create one anyway. A business case provides a “guiding light” for you to determine whether your efforts are still aligning with the business.
Plus, you never know when you might get dragged into a budget meeting to justify your existence!
Step 4: Managing Data Quality Operations
Next we have the “COO” of our internal data quality business. These folks are tasked with ensuring smooth delivery of service so this includes the initial fulfilment and ongoing service assurance.
This may typically be someone from a more senior data quality background, a person who can lay down training procedures, coaching/mentoring frameworks, service designs, methodology structures and manage the individual service delivery units.
It’s vital that these people actively look for ways to extricate themselves from “doing data quality” by mentoring and bringing on other people to learn the essentials and take more responsibility. I once took on this role early in my career and it took me months to realise I was the cause of failure within the team to grow and “cross-sell” data quality into other units of the business. I was too busy focusing on doing data quality instead of scaling data quality. Once I grasped this we quickly grew the capability and success of the team.
Step 5: Marketing and Selling Data Quality
This is one of the most interesting roles – “Head of Sales & Marketing”.
This person must spread the word and cross-sell the value of your data quality business to the wider organisation. This is really an educational role in many ways. Most sales people in the data quality sector will tell you that they need to provide an element of education before they can make a sale and if you’re looking to expand your data quality business internally then you will have to develop a capable marketing, education and sales plan.
Need some ideas for tools? These 7 Productivity Tools for Innovative Data Quality Leader may be useful to you.
Step 6: Selecting Appropriate Data Quality Technology
The “CTO” will be responsible for matching the operational needs of the team with the appropriate technology. They may have to provision custom built solutions or buy COTS products from the marketplace in order to help the business scale up and deliver the same level of high quality service.
Remember that it’s not just about data profiling, cleansing and matching. Your data quality business may require additional technology to cope with areas such as data governance, stewardship, information chain management, modelling business functions and logical models, demonstrating ROI and any other number of innovations that will help you expand the reach of your data quality business.
Tip: In many cases the organisation is forced to simply adapt current technologies (e.g. ETL tools) into a fully functional data quality technology solution. Many have witnessed considerable success with this technique alone.
Step 7: Investing in Data Quality Skills
The “Head of Human Resources” will be responsible for provisioning training and hiring suitable team members. They will be instrumental in attracting and retaining the best data quality professionals.
In addition, this person will play a key role in identifying the career path recruits to the team will follow. Having worked in several companies with internal data quality teams or centres of excellence, one of the key differentiators between successful and unsuccessful teams was the provision of a solid data quality career roadmap. Without one it is hard to retain and motivate staff to remain within your “data quality business”.
Benefits of “Data Quality Business Thinking”
I use the analogy of your data quality capability as a business quite a lot these days and I guess it’s driven by the credit-crunch and the need to demonstrate value and a professional approach.
I still witness data quality teams being disbanded and projects shelved because of a lack of perceived or realised value. I really believe that if you view your data quality team as a business in its own right then it forces the agenda that you have to deliver value for money, every day.
What if your team only has one or two people?
It doesn’t matter, you still need to assign the appropriate roles. For example, my personal data quality business has a small team but I still map out the various functions either to myself, my partner or other assistants that we hire.
Even if your data quality team is just you, by thinking of “you” as a business that has to market, sell, deliver and sustain, I think this is a far healthier approach than just thinking of yourself as the “data quality consultant”. It also forces you to think of ways to extricate yourself from the “doing” and focus more on the planning and selling, whatever it takes to grow your data quality capability into the wider organisation.
It really pays to structure your data quality team as a solid business entity that is so well organised and value driven it would be reckless to cancel it, no matter what the economic climate.
Next Steps For Your Data Quality “Business”
Think about your team and ask some of these questions:
- Who is a natural leader?
- Who can define standards and frameworks for delivery?
- Who performs well in presentations?
- Who has the patience to document training manuals?
- Who is the “tech head” who understands data quality technology?
- Who coaches new team members?
- Who calculates the value of what you deliver as a team?
- Who helps to sustain and monitor past deliverables?
Identify the strengths and weaknesses of your team and make this an empowering exercise for team members to step up and think about what each role requires. Give them a clear roadmap of where they are to where you expect them to mature.
What do you think about this approach data quality business thinking?
Please add your comments below.