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“Quality is free. It’s not a gift, but it’s free. The ‘unquality’ things are what cost money.” Author and management consultant, Philip Crosby’s ground-breaking books championed the importance of quality and the price of its absence in business. His point is that once you create and maintain a state of quality, the magnitude of benefits you reap are free. While much of his books have since passed into management best practice (think Zero Defects), they were the motherlode which helped trigger the change in mindset.

Forty years later, as businesses struggle for their very survival in what is likely to be a protracted post-pandemic global recession, the fundamentals of data quality are quietly and invisibly undermining organizations with hidden costs at a time when they can’t afford to falter. Systemic underlying issues around poor data quality are responsible for an average of $15 million per year in losses, according to Gartner.

Finance teams in particular are under more pressure than ever to secure cash and liquidity, to reduce cost, as well as to optimize working capital. But how do you trim the fat when technology is already automating the heavy lifting? Get your data in order!

Our increasing reliance on technology to perform tasks that used to be the domain of the humans means that no matter how hard we work, how clever we are or how cost efficient we become, we are ultimately at the mercy of the quality of our data. It’s not sexy, new or disruptive, but it’s worth its weight in gold – especially now.

Before the disruption and global volatility of COVID, organizations would lament and then pass bad data off as a challenge too hard to solve. But now it’s crunch time and businesses can’t afford to sweep data quality under the rug. Thankfully, they don’t have to. In fact, addressing data quality is one of the easier ways of achieving the goals of securing cash and liquidity, reducing cost, or optimizing working capital.

I know what you’re thinking. Data quality is hard (it isn’t actually), and you can’t purchase an IT solution to get rid of hidden data costs as you’ve got a spending freeze. That’s why SAP has designed a unique Data Cleansing-as-a-Service. This software plus services package, during an Explore and Prepare phase helps you understand your data quality issues and how they impact the bottom line of your organization. In a Realize phase, it supports you with fixing the identified data issues. In two short videos, I am first laying out the business benefits of Data Cleansing-as-a-Service (DCAAS Part I ), to then explain how to realize these by running a data cleansing initiative (DCAAS Part II).

By giving you a comprehensive Data Quality audit, including cleansing, continuous monitoring and improvement, you can easily address your hidden data quality issues, address them and establish a repetitive and controlled data quality improvement process – substantially cutting your bottom line costs, freeing up cash and optimizing your working capital.

Whether you need to reduce data errors and costs for operations, stock, marketing, sales, shipping or transportation and compliance, you can quickly eliminate the underlying data problems that are impacting your business efficiency.

Data cleansing as-a-Service is part of a four-step business survival guide, how data value can help you steer through times of continued disruption. If you’ve not already done so, I’d strongly urge you to familiarize yourself with the  Data Value Equation (data value = cost reduction x increased revenues x reduced risk), as well as to look at my previous blog where I outline this four-step business survival guide that focuses on bottom line improvements and risk reductions to get your company and your finance department through the critical stages of this economic crisis.

Also, watch out for my next blog where I am going to lay out how data supports you in optimizing and automating your business processes to maximize your short-term savings.

Gerd Danner, Vice President Data Management, EMEA-N Center of Excellence