Data quality leaders often struggle to connect the dots between the businesses’ goals - increasing revenue, cutting costs, optimising performance - and managing data quality more effectively. This makes building a business case for a data quality programme difficult.
To counter this, we’ve teamed up with Dylan Jones, data quality guru, and put together a guide to walk you through some practical steps you can employ (at zero or minimal cost) to build a case for data quality investment.
The goal of this guide is to help you overcome this common dilemma by showing you how to deliver a virtually zero cost data quality pilot that drives tangible benefits to the business and demonstrates the value of further investment.
Want to know if a lean pilot is the answer to your data quality business case woes?
The conventional approach for justifying a data quality business case is to quote industry research and other historical accounts of data quality benefits. These can help in certain cases, but nothing demonstrates the value of data quality technology like tangible results that resonate with your stakeholders.
We’ve talked about it before because it works (see Dylan’s guest blog here ). And so we’ve built out a more comprehensive guide that walks you through each step in the process.
A lean pilot involves executing a small-scale version of your initiative over a short timeframe to demonstrate tangible uplift in data quality.
This approach solves the 'chicken and egg' frustration that many people experience with data quality management funding: how can you demonstrate the value of improvement without getting the budget to implement data quality in the first place?
The pilot consumes practically no capital investment at all, apart from some minor expense for the time of a handful (or less) of key staff.
Your goal is to demonstrate the value of data quality improvement by building an ROI model to support your future business case.
You might fall into one of the below categories, in which case the ‘Lean Pilot’ approach in this guide can help you:
Some practitioners use the concept of the ‘shock and awe’ approach to building a business case.
They find lots of defects, link them to issues and processes the business is concerned about, and then attempt to shock them into investing in a new product to remove the problems.
The challenge with this approach is that you’re hoping to find something ‘juicy’ and relevant enough, to motivate a senior audience. This is a ‘bottom-up’ business case strategy.
A key difference with the lean pilot approach explained in this guide is that the motivations of stakeholders are uncovered beforehand. You then work in a top-down fashion, uncovering drivers, economics, processes, data and issues, so that when issues are found, you have a compelling story to showcase back to the executives.
With the actionable tips and advice in this guide, you can start to present your business case and create a justification for running a pilot to make some immediate improvements to an area of the business that stakeholders are motivated by.
Within each of the seven steps in the guide are ‘Action Notes’ that feature questions you can follow to build the business case as well as practical examples from other organisations which have used the lean pilot approach.
Creating a defensible data quality business case is one of the most challenging undertakings you will face as a data quality professional. By implementing a ‘Lean Pilot’ approach to your data quality initiative you can overcome common obstacles and demonstrate the financial benefits of making some immediate improvements.
As Dylan points out, it’s also rewarding because if delivered successfully, it will help you realise your vision for long-term data quality maturity.