by Jodee Hale-Schmid
November 16, 2010
Authored by David Kuketz, EIM Client Partner – Southeast, Utopia, Inc.
Data rules rule! You cannot manage what you cannot measure. You cannot control what you cannot manage. If you have no framework for measurement (i.e., rules) you are out of control. Business fails. Pure anarchy.Data rules, business rules … like rules of physics … they already exist, they’re everywhere – you just have to learn them, discover them. We don’t invent them. In the real world, we cannot escape the physical rules that operate – as we process through our daily lives. Some rules of physics are harder to understand than others. F=MA much easier than E=MC**2. The apple falls from a tree. Photons become energy at the speed of light and act both like particles and waves – who knew? Newton didn’t know. What happens to the apple, really? Newton had it only partly right – but in his day, they could only measure some of gravity’s effects. Newton’s original formula is replaced by Einst
ein’s General Theory of Relativity (and, even this today is thought to have a few holes in it). Today our business applications are much more sophisticated than 30 years ago. We can measure more now. We see more now. We sense more. Companies are much more highly interconnected with a lot more CPU cycles than before … we can match supply and demand much more closely and run companies at or near the efficient frontier (as fast as you can go without the wheels falling off the cart).If a company is operating on the “efficient frontier” (more on this idea later in another blog post), then it has optimized constituent relations, management approach, business processes, applications, meta data and raw data, minimized risks and maximized returns.Beyond data rules, even business rules are governed by a higher order paradigm, the rules of the economy, regulations, social pressures, etc., things external – and they are subject to change (war, elections, recessions, etc.) When those things change, the business rules change (adapt or die), the meta data changes, and the raw data requires updating and/or enrichment – in order for a company to remain on the “efficient frontier” – to keep risk levels from rising, to keep returns maximized at the optimal potential given a certain degree of risk tolerance of the stakeholders. Companies near enough to the efficient frontier may survive recessions, while the rest fade away. Enron, Worldcom, Lehman Brothers all broke their own rules, went beyond the efficient frontier, and then failed. Apple (funny), Amazon and Netflix make their own rules, create distortions, dis-intermediate and disrupt others in their industries, and redefine the way rules work in their respective markets. They create incredible value and recurring revenue streams.Some data have rules derived from the ‘real world’ of physics while simultaneously having other rules defined by the business processes pertaining to that particular businesses eco-system (price, availability, criticality, where and how used, …)Here’s where the “no-data-rules” guy’s theory falls apart … there are data rules that apply to things and they have valid, legal and range values because the thing (noun-modifier pair like bearing, round) has only so many properties. Rules exist to govern or guide that people will not enter, for example, a negative value or 1,000 meters for diameter. Simple. But there’s more.That thing just happens to exist in an eco-system (“universe”) and it inherits particular unique attributes endowed upon it by that system (where used, how used, when used, last replaced, due for replacement, safety stock, stock room, plant location, QoH, assembly, BOM, etc.) These attributes don’t belong just to the thing inherently, but to the thing when it is matched with its owner or user, conditionally. These values change over time, as the company navigates the economy and executes on new product introduction, production, new sales campaigns, changes in supply and demand, etc.Same item in a different business may have same physical rules (and attributes, in fact exactly the same, form, fit and function) yet the other rules (dynamic and configuration attributes) depend conditionally upon its eco-system, which could be vastly different than the other.Rules differ across types of data; vendor, customer, material, financial … there really are data rules, you just have to be aware of them and leverage them to YOUR competitive advantage. If you are better than your contemporaries at data and business rules, and business process optimization, you will probably be the 800 lb. gorilla in the room.
You can’t have a negative value for stock levels and you don’t want three extra zeros inadvertently added to a purchase order, or a check written to an inactive vendor, even if that’s what the business process “rule” allows for – because some smart dude might design a business process that is wrong, or there was no data rule that said “old vendors need to be archived”! Gotta have a safety net, a red flag, checks and balances.This paradox between data and business rules present a challenge, and an opportunity. While the physical data is relatively easy to define and set rules for, the other types are less easily understood and are bound by the business rules and higher order rules, which must be analyzed continuously. When companies change their eco-systems, consolidate via M&A, improve their processes, upgrade systems – it’s the not-so-easy data that has the highest profit potential and value.
An email has been sent to:
As artificial intelligence (AI) moves toward becoming a standard technology in daily business, companies increasingly need to balance the potential risks posed by AI-based software with the pursuit of growth...
When working with artificial intelligence (AI) technology, it is important to develop a set of guiding principles for digital ethics around the use of AI in software. Here we look...
ABAP platform 1809 includes optimizations that take full advantage of the underlying capabilities of SAP HANA and the features of SAP S/4HANA. Gain insight into three key optimizations that support...
Please log in to post a comment.
No comments have been submitted on this article. Be the first to comment!
Financials: Case study: How CF Industries doubled credit and A/R team productivity with SAP receivables management and native SAP automation
Financials: Case study: How Great-West Financial optimizes its accounts payable processes with limited purchasing integration
Financials: Case study: Learn how Tennant Company executed an on-time, on-budget migration to the new general ledger
See more »
SAPinsider is published by WIS Publishing, a division of Wellesley Information Services.
20 Carematrix Drive, Dedham, MA 02026 USA
Sales and Customer Service: 1(781)751-8755; firstname.lastname@example.org
© 2018 Wellesley Information Services. All rights reserved.
Online ISSN #2155-2444, Print ISSN #1537-145X
SAP and the SAP logo are trademarks or registered trademarks of SAP SE in Germany and other countries.