The Data Value Equation: Your Business Guide To Surviving Protracted Disruption
“Revenue is vanity, profit is sanity, but cash is king.” It’s an old saying but it could be the 2020 strapline for just about every business globally. 2020’s ripples of volatility and ongoing disruption reach far and wide. Businesses have slammed the brakes on spending, and we’ve all felt the sudden jolt of the corporate seat belt tightening around us, forcing us into the back of our seats. Financial liquidity is now a top priority. Cutting costs, optimizing working capital and deferring non-urgent projects and investments are the new norm.
Going through a downturn and making tough decisions to keep your company afloat is hard – even harder if you’re the one who’s been tasked with cutting costs across your department. We wanted to use our own expertise to find a way to make things easier.
A great place to start is by looking at the Data Value Equation (data value = cost reduction x increased revenues x reduced risk).
I created this four step business survival guide that focuses on bottom line improvements and risk reductions, that would get your company and your department through the critical stages of an economic crisis:
- The Here and Now – sharp focus on finding bottom line cost reduction.
- The Short Term – optimizing and automating business processes to maximize short term savings.
- Mid and Long Term – analytics help to create operational transparency, analyse your risks, as well as to predict the continued impact of the crisis to your business and your best next steps.
- Recovery – accelerate growth, identify areas of innovation and opportunity to leap-frog competitors coming out of the crisis.
In this blog, I’m going to talk about how your data can help you in the Here and Now. The bottom line has never been in sharper focus, and if you’re a line of business leader, that’s put you under pressure.
Less mature management teams tasked with cutting costs, typically just cut people. Not because they want to, they simply can’t see where else they can find savings. This not only bleeds good talent, damaging future recovery and ongoing employee morale, it also fails to address the hidden inefficiencies, leaving you to operate with the same systemic overheads as before but with fewer people.
Data may not be your first port of call when told you must cut costs by twenty or thirty percent. That’s because most data costs are hidden. They’re systemic or invisible which companies tolerate in good times, but now you’re in the quagmire, eliminating them is critical.
Let me give you an example of what data quality can do. I recently worked with a large multi-national chemicals company with 6,000 different payment terms in one ERP system, such as payment within 25 days with a two percent discount. If you’re dealing with global customers but have different and non-harmonized payment terms on the local subsidiaries that you’re shipping and billing to, it’s impossible to optimize KPIs like Days Sales Outstanding.
Likewise, duplicate materials in ERP systems make it impossible to rationalize and optimize inventories. We recently worked with a company that provides spare parts to oil and gas customers. After two weeks, we found they had a duplication rate of 30 percent in their product catalogue, eliminating hundreds of thousands of dollars in unnecessary inventory.
Addressing something as basic as data quality can reduce annual supplier spend by two percent, optimize inventory carrying cost in the supply chain by ten to fifteen percent, reduce the cost of financial closing up to twenty percent and better manage the number of Days Sales Outstanding by ten percent.
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 (watch the short overview video for the details DCAAS Part I ) with a fixed timeline, guaranteed success, zero CAPEX investment and no long-term commitment.
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.
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.
To find out more about Data Cleansing-as-a-Service, watch out for my next video on how Data Cleansing-as-a-Service is being delivered, or contact your local SAP representative.
In my next blog I will be looking at Navigating The Way To Savings In The Short-Term by optimizing and automating your business processes.
Gerd Danner, Vice President Data Management, EMEA-N Center of Excellence