In today’s information-driven business world, where business intelligence and the ability to accurately conduct predictive modelling and forecasting offers a significant competitive advantage, data quality has become a business imperative.
After all, if analysis is conducted on poor quality or incorrect information, the insights derived from it will be inaccurate at best and could be detrimental to the business, says Gary Allemann, MD at Master Data Management.
Resolving issues with data quality requires changes to business processes and often to the culture of the organisation, as well as to technology that underpins business operations. This requires collaboration and cooperation across the organisation and the breaking down of traditional silos.
In order to achieve data quality transformation, buy-in from senior executives is critical, as any significant change to an organisation needs to come from the top. However, obtaining this buy-in and selling the business case to executives can prove to be a challenging task, often resulting from the well known disconnect between business and IT.
Addressing this disconnect and achieving effective and enduring engagement with senior executives requires a clear strategy to tackle the challenges and highlight the business benefits of data quality initiatives. A proven approach to achieve this goal is discussed in a whitepaper, which can be downloaded here.
Since data quality initiatives require transformation across the business and across traditional organisational boundaries, obtaining senior executive buy-in is critical. Executives need to endorse the required initiatives for data quality improvement, which requires that they clearly understand the negative impact of poor data quality as well as the potential benefits of improvement.
Since data quality improvement is also a business transformation challenge, it requires top-level support to ensure that initiatives align with business strategy and will have maximum positive business impact.
Change management also requires executive buy-in, as senior executives are effective change agents, can instruct their people to support data quality improvement efforts and are also able to mandate changes to business process when required.
Senior executives in effect are role models for the business, and by showing support for data quality improvement they are able to motivate others to do the same. However, because they are so effective at influencing change, they are also required to make decisions and support a wide range of initiatives within their business.
This often means that data quality is just one of many issues, and unless the business case for data quality improvement can be made in a clear, concise and understandable way, it will not stand out as an urgent endeavour.
Added to this challenge, data quality is also a relatively new discipline, which means that many senior executives are not accustomed to seeing it as a business issue. Since data quality has typically been seen as the domain of IT, it can also prove difficult to explain the business impact of poor data quality.
This is not aided by the proliferation of jargon such as metadata management, information architecture, data modelling, data governance, master data management and so on. Data quality professionals need to simplify the issues and explain concepts in an understandable language in order to relate data quality to the issues senior executives face on a daily basis.
Bridging the gap between business and IT in this case requires data quality concepts to be translated into a language that will elicit a positive response from executives.
Selling data quality to senior executives requires a strategy that covers the following six areas or steps:
Articulate the problem;
Create the vision;
* Demonstrate delivery;
* Prepare the ground;
Influence the outcome; and
Sustain involvement.
If data quality professionals can get all six of these aspects correct, chances for obtaining all-important buy-in are greatly enhanced, which means that the success of data quality improvement projects will be subsequently enhanced as well.
Gaining the support and commitment of senior executives is vital for the success of data quality improvement projects. Following these six steps will greatly improve data quality professionals’ chances of achieving this.