The Road to Data Quality and Governance Maturity
Interview with Jill Wanless
In this interview Jill Wanless shares some of her experiences and tips for getting a data quality program off the ground and moving in the right direction.
Jill Wanless is one of the most popular and active members in the data quality and data governance community.
Her blog “Data Quality From The Ground Up” is an inspiring account of how she has helped deliver data quality and data governance initiatives, with limited funding, using innovative “guerilla tactics”.
Data Quality Pro: How did you come to be involved in data quality?
Jill Wanless: In late 2006 our organization undertook to change its business model from a product based one to a customer focused one. As a result, a business initiative began to look at potential CRM software solutions as well as to perform an assessment of the current state of data quality. I was the lead Senior Business Analyst tasked with managing the Data Quality assessment project.
As a result of the recommendations of the assessment, a team was formed to begin the establishment of a Data Quality program to support the CRM software implementation, and I applied for and was offered the job to manage the new team and program.
Data Quality Pro: What are some of the most positive steps you and your team have taken so far on the road to data quality improvement?
Jill Wanless: Getting involved with a high priority project (or program) – for us it was a CRM solution implementation. This involvement enabled us to do the following:
- Established regular profiling of the priority data – we now provide over 20 regular quality reports to engaged business stakeholders. We were able to achieve this by starting with the data that was going to be required within the CRM solution and communicating the results.
- Purchased an Enterprise Wide Data Management Tool – again, because of the data profiling for the CRM program we were able to identify that data cleansing/transformation needs would not be met without an automated solution. We now use the tool regularly to profile and cleanse data.
- Built a wiki to house data definitions – we obtained approval and sponsorship for the reconciliation and corporate communication of the: definitions, business rules, business stakeholders and business purpose for all the data within the CRM solution. This to me is our greatest achievement because this provides the creators and users of the data the means to understand the state, fitness and purpose of the data. We were able to do this by selling the idea that we would be supporting the training and change management needs of the business users of the solution. Incidentally, we use a ‘wiki’ to do this as part of our strategy to get business and IT stakeholders to easily contribute to this information thereby establishing the beginnings of data stewardship.
- Developed the scope of the Data Quality program based on the work we did for the CRM project. The success of what we accomplished during the project allowed us to achieve executive mandate and sponsorship for the program overall. A great achievement in my books!
Data Quality Pro: How are you communicating the value of data quality within your business?
Jill Wanless: We measure everything and we communicate the results at every opportunity. We measure the quality of all kinds of data, we measure the number of requests we get, we measure how many users access our wiki of corporate definitions and we measure costs/effort associated to having to manually ‘fix’ data against building governance into our processes. We post the results of our measures (and we use trend graphs) everywhere we can, beside the printers, in the washrooms (whatever works!), in the kitchens, on our internal web site and within the wiki.
Data Quality Pro: How have you structured your data quality roadmap within your business, what does the big picture look like?
Jill Wanless: We started with a big project, the CRM solution. Once we understood the business requirements for the project, we were able to establish the program: data profiling, data cleansing, data reconciliation, data definition (rules, definitions, purpose, stakeholders, quality targets etc.). I’m not sure if you could say we have a ‘roadmap’ established. It’s more like we have a program, and we can clearly show the logical ‘next steps’ that will help us achieve a higher level of data quality maturity.
Data Quality Pro: What techniques are you adopting for encouraging knowledge workers to get onboard with your data quality plan?
Jill Wanless: I’ve been told that I ‘rant’ a lot. Of course I smile when I do it J. Well, it’s not really a rant, it’s more like I’ll see opportunities to engage others and take advantage of them. First, I’m prepared. I know exactly what it costs to manage data re-actively, I know the costs associated to lost opportunities, I know where the gaps in the processes are and I know our project delivery model is delivery, not quality focused. So I have a mini business case in my head. In the course of my day I’ll meet with at least 10 different people and the conversation always includes some reference to data – and that’s my cue! I’ll make sure I know the person well enough that I know what some of their issues are, and my sales pitch for data quality will always show how managing data as an asset will solve some of their problems. Sometimes I’ll get enough interest that I’m asked to speak at a team meeting! Makes my day!
Data Quality Pro: Looking at the future, what are your goals for the project say in 1 year, 3 years and 5 years time?
Jill Wanless: Well, a lot has happened in the last few months. We have a business sponsored MDM program starting up, and that means data quality will have a much higher profile, so I’d say given this new initiative, they go something like this:
- Year 1 Data Governance is formalized for our ‘master data’
- Year 3 Information architecture processes support corporate data governance
- Year 5 Who knows! The business models and the technology change so fast, I couldn’t even guess as to what the future brings. I’d really like to see Human Resources and corporate policies established that recognize and reward creativity and innovation. I think that having people like that around you will ensure your success whatever the future holds.
Data Quality Pro: What skills do you draw upon that enable you to deliver a data quality strategy for your business?
Jill Wanless: You have to really like and care about people. This helps you remember what their needs are and model your business case to show solutions from their viewpoint.
You need to be a great sales person. Not a schmoozy in-your-face type. You need to be honest and open and firm. The firmness needs to be around continuously focusing on data quality and how improving it will ensure business goals are met. Never wander from those goals!
You must have or develop a large network. One way I do this is by socializing with co-workers on facebook. This helps you identify commonalities and is a great way to build trust and friendship.
Communicate well and often. By well I mean keep it brief, to the point and fun. People will want to hang out with you if you are an information sharer.
Lead by doing, not by talking. And keep your opportunity antennae always on!
Data Quality Pro: What things would you have done differently with the benefit of hindsight?
Jill Wanless: Tough question. This is where I got stumped and put off finishing these questions for a month!
In the last while I had started to be more assertive when questioning approaches, clarifying goals, requesting success measures and generally asking the questions that tend to make others uncomfortable.
An example would be asking who the business stakeholders are that will maintain data definitions for data to be used in a project and ensuring their accountabilities were added to a requirements document for business sign off. It’s just a small step but it makes a big difference.
Not sure if I could have behaved more assertive earlier in the game though, I might have easily put people off. It has been a fabulous ride with an amazing team and I couldn’t have had more fun if I tried, so I guess I wouldn’t change a thing!
Data Quality Pro: What advice can you offer for others with a similar role to yourself who may be starting out on the road to data quality maturity?
Jill Wanless: Surround yourself with innovative and creative people – the better the solution, results, success etc.
Here are some other key ideas:
- Have fun and laugh a lot – people don’t want to hang out with unhappy people
- Share results and communicate well – your information will be well received and eagerly anticipated
- Find some supporters and stick with them and make sure you help them whenever you can – you want them to spread the word on how great the results are that you’ve help achieve
- Make sure your business requirements, business case, business proposals and associated documentation all include data management processes, risks and accountabilities – if you can do this you are halfway there!
- Get yourself on twitter and hang out with the data quality folks – they have so much valuable information!
- Celebrate your successes loudly and often – so others can see your success!
Summary of Key Points from Interview:
- Accelerate your data quality maturity by providing direct benefits to a strategic project, as Jill’s team has done by supporting the CRM implementation
- Start with a data quality assessment to understand your current data quality state and what immediate activities are required
- Engage business stakeholders by creating data quality reports driven from profiling data, maintain engagement through reports that are meaningful and valuable to each recipient
- Wiki’s are increasingly being used as an ideal tool for managing data governance and stewardship of data assets as they help the business and IT sides collaborate more effectively
- Communicate the value of your data quality efforts in real terms that everyone can understand and in locations that are highly visible
- Focus on data quality as a program, look beyond localized small term gains and focus on building a platform for future growth
- Look for opportunities to promote your achievements by having solid figures and a simple business case on where you can add value to other data-driven parts of the business
- By demonstrating value and creating a platform for growth, greater opportunities will follow (Jill is now heavily involved in a new MDM program)
- To take your data quality aspirations forward you must learn how to “soft-sell” data quality, network proactively, communicate succinctly, lead effectively and identify new opportunities regularly
- Lead by example and create a fun environment of creative and forward-thinking team-mates within your team
- Leverage social media and share stories and experiences with other organizations and specialists
- Don’t be afraid to blow your own trumpet – be vocal about your successes
Jill is currently leading the implementation of a Data Governance program at Export Development Canada; working with business leaders and business and IT stakeholders to identify core information needs, develop common definitions, and recommend organizational owners for Company data.