Cutting Edge Analytics Starts with Data Quality
13 October, 2022
Principal Data Scientist
at Decision Inc.
If you can’t trust your data, you can’t trust your analytics. Today’s most successful companies have data at the core of their business. That is why you should never compromise on data quality and at the heart of quality data lies a robust data governance framework.
The meaning of the data-driven organisation has changed. Today, the true value of data lies in analytics and intelligence – but without sound data governance, your data could be nothing but disparate information. McKinsey believes that there are seven characteristics defining a data-driven enterprise. The most prominent is an organisation with data embedded in every decision, interaction, and process. Thus, it is clear, companies that make the most progress towards this characteristic will be those that will experience transformative optimisation and value. However, there remain obstacles to data success, and resolving these should be a priority.
The Biggest Obstacle to Success – Data Quality
Perhaps one of the biggest hindrances to cutting edge analytics is the quality of the data. Many organisations fail to see the value from their data due to this. This is quite concerning because data is one of a company’s most important assets in our ever-advancing digital age. Don’t be mistaken, poor data comes with a price tag – Gartner has estimated that poor quality data can cost businesses around £11.6 million per year. This trickles down throughout the organisation, impacting decision making, efficiency, and data relevance. Instead of a pool of insights that can be tapped for value, your data can be a tangled mesh that offers limited visibility and value.
Data Governance: The Key to Data Quality
This is also why research has found that very few organisations actually trust their data. It is a huge concern that decision makers are still on the fence about. They don’t trust the reliability of their own data, and this can impact trust in processes and the business as a whole. Therefore, it has become critical for companies to focus on embedding quality into every aspect of data management through robust governance and processes.
You might be interested in our article: Five Key Principles of a Data Governance Framework
Where to Start with Data Quality
The first challenge to address is the source of the data. How the data is actually captured is often not governed by the right rules, which makes the point of capture a risk. This is changing as organisations recognise the value of refining the data at source. It should thus remain a priority to ensure data meets expectations around value and consistency.
Another issue common to many companies is limited data validation and monitoring on an ongoing basis. Companies need to invest in data quality validation rules and dashboards that show where the data is lacking so that steps can be taken to fix it. A key aspect of this is assigning roles and responsibilities so that each data quality issue becomes part of someone’s KPIs to fix.
How Data Governance Helps Realise Quality Data
This is why Data Governance is so critical because it is within a Data Governance strategy that policies for data quality standards and validation are defined. And processes are put in place to monitor these. It is robust data governance that ensures data is validated, policies mandated, and data continuously assessed so that it meets the highest possible standards. Rules around data quality, for example, would immediately alert the business if data drops below a minimum standard.
With a proper data governance framework and strategy in place, companies have the luxury of data transparency. Ultimately unlocking the value of data quality. They can see what their sources are, how their data benefits them, and how it delivers the kind of reliability that can be trusted in decision-making. It also allows for them to assess existing data frameworks against best practices so they can fix any problems from the outset.
Once data is in a space where it meets quality expectations, the organisation can take advantage of the competitive edge it brings. Doors are opened to applications such as artificial intelligence (AI), analytics, automation, and all the other business enablers that rely on great data to provide the organisation with sustainable results.
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Decision Inc. helps organisations develop and deliver the Technology and Digital Operating Model to support their strategy. We create the capability for clients to innovate and compete by connecting the technologies, platforms and data they need to thrive in the Modern Era.
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