Many have found out the hard way that using and visualizing data without first cleansing and enriching it is much like brushing your teeth without toothpaste – you can take the same action, but ultimately will not get the same results.
It is turning quality data into something usable and actionable which will drive insights for improved decision-making – and provide organizations with the most strategic value. High performers in analytics are rising above the pack by taking control of their data quality and data management practices and using this insight to find new ways to improve their enterprises’ control of costs.
Through a deeper understanding of their data and the role it plays in making strategic decisions, business leaders are working ever more closely with the wider business to streamline processes by actively driving information into key areas to support innovation and top-line growth.
As business leaders now know, poorly integrated, cleansed and enriched business data often leads to equally poor business decisions. This will have a significant knock-on effect, and snowballing into reduced customer satisfaction, competitive advantage and overall product and service innovation. Although most will be able to demonstrate a reasonable grasp of their internal data they all admit to facing significant data enrichment and integration challenges.
According to a poll of 291 organizations commissioned by a leading supplier of data quality management solutions, and completed by independent analyst Graham Rhind, 41% of companies surveyed have no data quality strategy implemented. This is great news for companies who are strong in their data quality initiatives, but a scary reality for companies still waiting for that elusive “data quality” black box. The longer they wait, the further behind their contemporaries they fall.
The future for these organizations is about being able to make the most of their data and ensure that they are able to make decisions using the highest quality data possible – with the right intuitive, intelligent tools.
Organizations must start thinking of the bigger picture – more data, but quality data – what they currently have is no longer rich, broad or good enough. The key challenge is figuring out how to collect it all and then connect it, and in some exciting cases create it.