Better data quality is good for your company, but it can be a costly objective to attain. In an environment where profit margins are shrinking, IT is being asked to control or reduce costs while technology is changing/becoming obsolete faster than ever, making investing in data quality improvements difficult to prioritize. Here are four actions you can take to improve data quality and why it should be one of your top investment priorities.
- Improved decision confidence
Business leaders and operational decision makers are becoming more and more dependent on data to provide insights into internal operations, market opportunities and competitive threats. Data-driven decision-making has become a reality in most organizations – built on assumptions that data is correct, complete and reflects real-time conditions. Without quality data, leaders are left with subjective inferences based on questionable data as the basis for their decisions.
While improving data quality will not guarantee leaders will make good business decisions, it will help them be more informed of what they do and don’t know and more confident in the decisions that they make. Improved decision confidence will lead to more decisive action, enabling a company to pursue more aggressively opportunities that were once considered too risky.
- Ask better questions
Information insights only come by asking the right questions. If business analysts and managers don’t question the quality of data, then they are not likely to ask the difficult questions that could have significant value potential. Improving data quality can provide analysts and process owners a clearer picture of what is occurring in their organization. Simple questions are easier to answer, and users have the time and opportunity for more complex exploration of the data without the fear of being misled by false information.
- Identify 3- and 4-factor relationships
Data quality isn’t just lists of values. It is how different pieces of data are interconnected and the interdependencies that exist. Most unrefined data sets only provide insights into direct, or 1- and 2-factor relationships. While these are interesting, business and technology environments are much more complex and dynamic, with multi-factor relationships and indirect dependencies impacting how a change in one place ripples through the broader landscape.
Improved data quality, both in independent source data sets and in how data from different sources integrates, can enable companies to expose more complex business dependencies. Their leaders are then able to target change and influence efforts in places that will generate the greatest impact.
- Better “what-if” modeling
The business environment is constantly changing and evolving. Companies use data to model “what-if” scenarios to predict the impacts of events, actions and environmental forces on the future performance of the business. Improved data quality, both from internal operations and the external environment, can provide scenarios and models with better inputs to improve the accuracy of projections – leading to increased competitive advantage.
Improving data quality may require investment and effort, but as you evaluate alternatives, consider the strategic and operational benefits to your organization. Data fuels modern companies; and the better the quality of input, the more value you will be able to generate. Few other investment opportunities have the impact potential of data quality improvement.
Blazent is the leader in driving data quality management for global leaders in financial services, healthcare, manufacturing and government. To learn more about our solutions, feel free to download our white paper on Ensuring Data Quality here, or contact us directly at sales@blazent.com.