Why Some Complex Data Processes Are in a Class of Their Own and Require a Different Digitization Approach
By Jeanette Mifsud on Nov 25, 2020
Analysts and business leaders agree that digital transformation is a top strategic priority in the coming years — and one where flawless execution is vital if companies are to survive in an increasingly competitive global economy. And the investment dollars are following. IDC forecasts that worldwide spending on digital transformation technologies and services will reach $2.3 trillion in 2023, a staggering 53% of technology investment.1
The pressure to go faster is acute for organizations that run their business on SAP ERP systems, which are, in many sectors, losing ground to nimbler digital-first market entrants. In a recent KPMG survey, 67% of global CEOs agreed with the statement, “acting with agility is the new currency of business; if we are too slow, we will be bankrupt.”2
In the clamor to digitize, organizations must realize that different business processes require differentiated digitization strategies and technology solutions — or risk setbacks and wasted investment. Some processes are in a class of their own — they create the master data that powers critical business operations.
These processes are complex, cross-functional, and subject to internal and external controls. We call them “strategic data processes.”
Examples of Strategic Data Processes
Launching a new product in an SAP system is a prime example of a strategic data process. Before a single machine in any plant can make a new product, manufacturers need to set up a massive amount of data. Collecting and entering this data can be a slow, tedious process that involves many departments, lots of emails and spreadsheets, and manual data entry — making this process a prime candidate for automation. But just one mistake in critical data elements, such as weight and measures, can have costly downstream consequences.
Similarly, entering customer data in an SAP system is a strategic data process. Businesses can’t take orders without first setting up customer master records in the SAP system, and that process can take days or even weeks if done manually. Mistakes or omissions in customer data
can lead to shipping and invoicing problems, increased cost, and poor customer satisfaction.
These are just two examples of strategic data processes. Others include vendor onboarding and management, the setup of plant and equipment for
maintenance purposes, and the creation of finance master data to support accounting operations.
Requirements for Digitizing Strategic Data Processes
Master data management platforms excel at enforcing business rules and syndicating a small number of data fields in a few core domains but are
not designed to streamline the complex processes associated with setting up and maintaining the data.
Traditional business process automation platforms are great at digitizing simple tasks like customer inquiries and contract reviews. They work well for
routing documents but are not designed to automate complex data processes and do little or nothing to improve data quality.
Digitizing strategic data processes takes a different class of automation software. In response to this need, we are pleased to introduce Winshuttle Evolve. With its unique combination of robust data stewardship, enterprise-grade automation, and deep SAP integration capabilities, Evolve enables organizations to get both better data and faster processes.
To learn more, check out our resources on “Evolving Digital into a Competitive Advantage:”
About the author
Jeanette leads the product marketing team at Winshuttle and has over 25 years experience helping technology companies define and market products that solve real-world problems for customers around the globe. Although based in our Bothell, WA headquarters, Jeanette hails from the UK.
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