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October 9, 2017
By Bill Tennant
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For years I have been a part of what you might call the transformation of the data management space… I’ve witnessed the advent of Self-Service BI and seen it taken exponentially further than Excel could ever hope to provide, with-cloud based applications.
I have witnessed customers spending millions of dollars (or pounds) on enterprise data warehouse architectures to provide access to data across their business. And I have seen Big Data take hold, fizzle, and take hold again.
Based on this experience, the innovation and drive toward providing access to data comes from the need to drive better adoption, and provide better information to the business as a whole.
In working with customers large and small, one fundamental principle holds true. We all want to take advantage of Big Data, but what about so-called Small Data?
Harvard Business Review has recently indicated that up to 50% of a business’ structured data is not utilized. When I hear this, I consider the ramifications of taking on a Big Data initiative, that means the focus ends up diverted from maximizing the use of existing, readily available structured data.
Yes, Big Data is important to consider in each business’ long-term BI roadmap. Many businesses already employ data analysts, whose sole purpose is to deliver reports to the business, compiled from multiple areas so that the organization has a view daily, weekly, monthly into their financial and operational metrics.
In considering the risks associated with self-service BI (those of ungoverned data) and Enterprise BI (long-term implementations), I usually revert to my Finance and Accounting background and consider something that is quite simple: the analysis of how long it takes to go from cash-to-cash, i.e. the purchase of inventory and payment to the vendor, to the sale and ultimate collection of the cash from the customer. This calculation takes the form of:
“Days Inventory Outstanding” + “Days Sales Outstanding” – “Days Payables Outstanding”
Now, at the surface, this does not seem to be a complex calculation. And if you’re an organization running a single company, single country business, it may not provide too many challenges at the surface. However, when an organization begins to wonder if there are trends amongst various geographies (UAE vs Nigeria, perhaps, or Alaska vs Florida) or exceptions that should be considered when reviewing specific sales teams, vendors, or customers, these calculations become infinitely more complex and form the basis for an analytical journey…
Imagine this scenario for a moment:
To establish the cash-to-cash cycle metric these components must be added together and fields must be associated with each other to allow for common elements (dates, currency, etc.) to be established.
You also realize that creating this report—while having no knowledge of the cryptic table names associated with the potentially thousands of ERP tables—means your IT team must create the report. Thus we go back to why Harvard Business Review also indicates that 70% of analyst’s time is spent on preparing data, not analyzing!
Our solution? Software that not only provides a means to integrate these tables out-of-the-box through a natively-integrated data model, but also provides:
Would your business like to better understand how your cash-to-cash looks within, for example, “the state of Florida for only your Pharmaceuticals business”? Or to compare, for example “your top five SKUs and their cash-to-cash cycle within your top five geographies”?
Through an integrated, end-to-end data automation platform, these key elements should come as standard and be integrated and deployed within days, while also providing common table names allowing the end-user to realize the value of their self-service BI on a governed data set.
Park long-term enterprise projects, I say, and provide your organization with the ability to have this level of insight—as well as alerts if cash-to-cash rises above the industry average within days—and you can achieve true success with your business intelligence tools.
When reviewing options for the delivery of data management, industry best-practice analytics, and governed, fully-integrated data modeling, consideration must be given to those elements of the business that you may not have ever considered.
It provides the ability to harness the power of your business management systems, and rapidly achieve a true return on your BI investment.
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