Assessing Your Data Quality Assessing the maturity of data quality in your organisation can be difficult. Data Quality ownership may be distributed across individuals and business units, with those responsible holding varying points of view of issues and priorities. A data quality framework can help ensure that an assessment is complete and systematic, providing coverage across multiple inter-dependent data quality dimensions. Benefits of using a Data Quality Framework A Data Quality framework can help you assess data quality confidently and objectively. For example, they can be useful in exploring:
The risk of attempting a data quality review without a framework in place include:
Dimensions of a Data Quality Framework* It is important to be mindful of the full breadth of data quality dimensions when assessing your data quality and formulating a framework. The dimensions of your data quality framework should include aspects like:
Tracking maturity over time After defining your framework, you're ready to conduct a maturity assessment. This will help to provide a baseline of where your organisation is performing well versus areas for improvement. The maturity assessment and framework dimensions can now be used in tandem to track and prioritise projects that will progress your organisation towards data quality maturity. Outcomes of your data quality strategy can be measured through identifying a small number of data quality metrics. It is helpful to narrow down to the "metrics that matter", so as not to overwhelm with analysis paralysis, choosing the key leading and lagging indicators of data quality performance. Easy visualisation and frequent inspection can be enabled through the use of out-of-the-box CRM dashboards and simple governance practices to support ongoing improvement. Collagis is committed to helping businesses like yours to optimise workforce and organisational effectiveness. We'd love to share with you how we can help you address data quality in your organisation. Contact us today *Adapted from The Practitioner’s Guide to Data Quality Improvement. By David Loshin Data Quality has a big impact on your bottom line and is a key factor that can differentiate you from your competitors. However, as the issue of data quality is complex and spans multiple business units, the impacts of data quality often go unchecked and unmeasured.
Data Quality issues are systemic across many businesses: For example:
The impacts of data quality Data Quality issues can have direct and indirect impacts on your organisation. The direct impacts are easily quantifiable, including how much money is being spent on 3rd party data, data cleansing, and manual data remediation efforts. However it is the indirect impacts that create the higher cost for many organisations. Three common in-direct impacts of data quality include:
So what is data quality costing your business? What is the opportunity cost of leaving this unchecked? No doubt, with some measurement and investigation, there is a strong business case for value creation by addressing this often overlooked and under managed issue. It takes an analysis of the direct and indirect impacts of data quality to get a true sense of why data quality is important and to understand the true cost to your business. Collagis is committed to helping businesses like yours to optimise workforce and organisational effectiveness. We'd love to share with you how we can help address data quality in your organisation. Contact us today In the age of analytics, data quality plays a critical role in helping organisations achieve better and more sustainable results. However, as it is a complex issue often with distributed ownership, many organisations fail to tackle the issue of data quality holistically. Siloed business units and individuals can have different points of view of what data quality is and where data quality issues may exist. Unconnected projects can pop up that may not tackle root causes and may not work together towards a common goal. Because data is such an intrinsic part of the way we do business today, we see data quality as a foundational element of organisational effectiveness.
What is Data Quality? Data Quality is basically the shape that all your information is in. Is your company's data fit for purpose? Is it complete, accurate and reliable? Our clients rely on data driven insights, whether it is to develop key strategic initiatives or to help improve relationships with clients via marketing and servicing. The quality of data will determine your ability or inability to solve business problems and will greatly influence your ability to make sound and accurate decisions. In short, the impacts data quality cannot be underestimated. Defining Data Quality Dimensions Data quality management is multifaceted, so when defining data quality in your organisation, it is important to create a common language and understanding of the dimensions of data quality. Here's an example of 6 dimensions of data quality that are useful in defining data quality. 1. Consistency - Is there only one version of the truth? Can you compare data across data sets reliably? 2. Completeness – Do you have all the information you need? Are your key data attributes populated for your data set? 3. Accuracy – Is your information correct? Have you a process to manage errors? 4. Uniqueness – Does the information you have uniquely describe each individual? Can you identify a unique individual across data sets? 5. Timeliness – Is the information fresh? Do you have real time access to the data? 6. Validity - Is your information in the correct format? Make sure that the data you have is user friendly and aligned to business rules. Data quality can be a very complex and challenging business problem to solve, but breaking down the problem and reaching a common understanding of what the problem is, can be a helpful first step to commencing a well designed Data Quality Management Strategy. Collagis is committed to helping businesses like yours to optimise workforce and organisational effectiveness. We'd love to share with you how we can help address data quality in your organisation. Contact us today |