Successful data management strategies start with quality control

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There seems to be some confusion between the data container and the data content, which appear to get lumped together and called a database.

In my experience IT takes ownership of the container and the user community - perhaps marketing, sales, manufacturing etc. - take ownership (or not, as the case may be) of the content. Neither collaborates as - to each other - they appear to speak completely different languages.

So whose problem is it anyway? Data and information quality is actually a business problem, not an IT, marketing or any other silo’d department’s problem. And it’s a business problem because poor quality data bites deeply into your bottom line.

So why should CEO's care? Firstly, the Introduction of the new GDPR compliance regulation in May, will mean that business data is very much on the agenda for organizations. With fines of up to 20 millions euros or 4 percent of global annual turnover for noncompliance, businesses need to make data a priority.

There is the obvious waste in data – duplications, mailing waste etc, but data integrity and data quality reaches far deeper than that. It’s the bad decisions - when based upon false data - made with a high degree of certainty that do the real damage.

Many studies have shown that companies spend 20 to 40 percent of their turnover on data-related purchases and business processes, but few have accurate financial measures for this huge area of expenditure.

We measure our capital expenditure (CAPEX) as a matter of course, but do you have a measure of your expenditure on data (DATEX)? If you did, the chances are you’d find it's around 10 times bigger than CAPEX.

No one questions the need to measure return on investment (ROI) or return on capital employed (ROCE), but what about return on capital invested in data (ROCID)? As we don't measure it, we shouldn't be surprised to see how poorly we manage it.

Without a clearly thought out strategy and processes for data lifecycle management, (creation, maintenance and destruction) companies will continue to rack up huge, unrecorded and largely unrecognized costs arising from inefficiency, rework and duplication of effort, whilst remaining exposed to negative business impact of poor decisions and the damage to customer relationships.

As companies increase the volume of data they hold in the search for better results, the processes required for audit, control and management become more expensive and simultaneously less effective. Hidden costs associated with inefficiency, rework and duplication expand rapidly with data quality and leverage falling even further. Beyond a certain point, competitive positioning goes into reverse, while spending continues to rise.

Breakout from this situation requires a re-examination of how the business manages data and a clearly thought out master data management strategy. This needs to be supported with appropriate business processes and tools, so that leverage is re-gained and competitive positioning advances with a smaller, easier to manage, overall volume of higher quality, reliable data.

Resources released from inefficiencies, duplicated and irrelevant effort, reworking data-related problems, and repairing customer relationship damage, become available to drive the business forward and improve results across the board.

Data is without doubt one of the cornerstones of industry. It is the foundation from which information, then knowledge, then wisdom is derived. The paradox is that many businesses have masses of data and little information, whilst their employees have masses of information and very little data.

By following a few simple steps towards better data, companies can be assured that they are in the best position to target the right customers, maximize opportunities to gain new customers and grow existing customers.

Take ownership. Take action. Do it now.

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