Make no mistake, the future lies with automation of white-collar work. Fewer and fewer business problems these days focus on manufacturing and production processes, i.e., the nothing-but-widgets category. For all the non-widget-centric business activity in the world – which includes just about all every conceivable form of white-collar work – the following needs become paramount.
Ensuring the quality of meta-data.
Demonstrating compliance based actual rules, rather than the artifacts and effects that IT systems produce.
Retaining, teaching and repurposing intellectual capital.
What would I do to correct the shortcomings of BPM for non-widget-centric business activity? Our answer is to become more why-centric, as opposed to narrowly how-centric.[1] You should focus on business capabilities, not just business processes. That shift has several essential features:
Understanding business strategy as something distinct from business processes (and BPM). Business goals and business risks should be drivers of business process design – not the other way around. You need to be strategy-driven, not simply process-driven.
Designing core metrics around business goals and business risks – the things that concern C-suite executives the most.
Realizing that for white-collar work the 3-D world of widgets has vanished, and that tolerances and quality can be expressed only in terms of business rules.
Treating business rules as a first-class citizen, externalized from process models.[2]
Identifying operational business decisions (based on encoded business rules) as a crucial focal point in re-engineering business processes.
Including a Why Button as part of every business solution. Pressing the Why Button leads immediately to the business rules that produced the results you see from any process.
BPM often overreaches. Understanding, modeling and managing a business capability effectively requires a balanced view of six basic questions, not just one, as given in the table below. I follow Zachman in these matters, so yes, the table is Zachmanesque.
Interrogative
Basic Business Question
Kind of Model
1.
What
What inventory of things needs to be managed to support business activity?
structural model (e.g., concept model[1], data model)
2.
How
How do transforms of things in business activity need to take place to add value?
process model
3.
Where
Where does business activity occur?
network model
4.
Who
Who collaborates with whom to undertake business activity?
interaction model (e.g., organizational chart, use case)
5.
When
When does business activity take place?
temporal model (e.g., schedule, event model, milestone model)
6.
Why
Why are results of business activity deemed appropriate or not?
strategy model (e.g., Policy Charter[2], constraint model)
If your business does nothing but manufacture or produce physical widgets (forget all the meta-data about those widgets), you will probably emphasize question 2 (i.e., process) above the others. Your overall approach and architecture will reflect that. You will naturally gravitate toward BPM.
That tendency has at least three basic risks, even for organizations that do fall into the nothing-but-widgets category:
Your metrics will largely focus on process productivity (e.g., throughput, bottlenecks, latency), rather than strategic goals and alerts centered on external risks. E-suite executives tend to be much more focused on the latter.
Your mindset will be procedural, rather than declarative, which can cause you to embed business rules in process flows rather than externalize them. As a result your process models will be unnecessarily complex and your overall solutions un-agile.
You approach will fall woefully short in addressing the intellectual capital that underlies your processes. Such operation business knowledge ranges from simple meta-data, to the business logic that underlies operational business decisions.
Fewer and fewer business problems these days fall into nothing-but-widgets category. Even for widget-centric businesses, at least three needs are increasingly urgent:
Ensuring the quality of meta-data.
Demonstrating compliance based actual rules, rather than the artifacts and effects that IT systems produce.
Retaining, teaching and repurposing intellectual capital.
[1] Refer to Refer to Business Rule Concepts: Getting to the Point of Knowledge (4th ed), by Ronald G. Ross, 2013, Chapter 1 and Part 2. http://www.brsolutions.com/b_concepts.php
Richard Welke, Professor and Director at Georgia State University, commented[1]:
Any process improvement or change process is a metaprocess of the process it’s targeted at. And, of course, it in turn can have a metaprocess (the process for deciding when and how to change the process improvement, or more generally BPM process). Hence it is a meta-meta-process relative to the specific organization process or “routine” being examined/managed.
My reply: Yes, which leads to the questions of …
Meta-meta-data. A similar argument can be made for “data”. Any data that describes other data is metadata. Metadata, in turn, can have metadata (the data that describes metadata, or more generally a repository model). Hence it is meta-meta-data relative to specific business data being managed.
Meta-meta-meta? I don’t think any ‘meta-” above meta-meta-process or meta-meta-data would be meaningful (add value). I could be wrong I suppose.
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[1] This series of point/counterpoint replies is a follow-up to my post “Meta Here. Meta There. Meta Everywhere?” (March 31, 2014), which generated a surprising amount of great discussion. (Thanks all!) Refer to: http://www.brsolutions.com/2014/03/31/meta-here-meta-there-meta-everywhere/The definition I’m using for meta- is from Merriam-Webster’s Unabridged Dictionary [3b]:
3b: of a higher logical type – in nouns formed from names of disciplines and designating new but related disciplines such as can deal critically with the nature, structure, or behavior of the original ones *metalanguage* *metatheory* *metasystem*
Kevin Smith, www.PragmaticEA.com, commented[1]:I am not sure why you have asked about what is meta. You know the word ‘meta’ means “information about” and so to quizzically ask what other meta things exist rather than just metadata is a bit odd.
The answer (which I am sure you already know) is, of course, that you can apply the word ‘meta’ to anything you like so long as there is some benefit/reason for doing so.
Perhaps you are asking so people begin to talk generally about it?My reply: Many people think they know what meta means, but I find that’s not the case. The relevant definitions for meta- from Merriam-Webster’s Unabridged Dictionary(MWUD) are:
3a: beyond : transcending *metaphysics* … I would avoid this definition because it takes you to neverneverland.
3b: of a higher logical type – in nouns formed from names of disciplines and designating new but related disciplines such as can deal critically with the nature, structure, or behavior of the original ones *metalanguage* *metatheory* *metasystem* … I believe this is the useful definition.
There’s much more to meta- than simply “information about”. That usage probably arises from metadata, but meta- does not generalize to other nouns besides “data” in the sense of “information about”. There are at least two things wrong with that line of thinking:
1. It violates the basic definition (3b) of meta-. Any use of meta- must be based on the same noun. So “information about data” is disallowed in defining metadata. Instead you must say “data about data”. Change the noun and all bets are off. (The assumption here of course is you don’t mean “data” and “information” as synonyms. I certainly wouldn’t go there.)
2. It violates my additional rule for defining meta- as follows: You must always use a verb, not just a preposition. Prepositions hide meaning. So instead of “about” I would say “describes”. That way metadata becomes “data that describes other data”. The chosen verb must be intrinsic to the meaning or purpose of the thing – in this case, data. Data always describes – no exceptions, no reasonable dissent. (It should also be an active verb.)
Introducing a verb to the core meaning of a meta- forces you to put a semantic stake in the ground. So use of meta- is not at all limited to just “information about”. The MWUD definition does not require that, or even suggest it.
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As a young database professional in the mid-1970s I grew up on metadata – data that describes and defines other data. In fact, I wrote one of the first books explaining it from a data-as-corporate-resource point of view in 1980.[1]
Who knew that in the 21st century there would ever be such a thing as big data, more dependent on metadata (if that’s possible) than even ‘regular’ (transaction) data?! Or that the metadata of phone conversations would become a central artifact in the struggle over civil liberties?!
Back then it never much occurred to me that there could be other kinds of “meta”. Well, except maybe metaphysics. But you don’t want to go there. That’s some realm beyond physics where physics isn’t physics any more.[2]
Anyway, I was wrong about there not being other important kinds of “meta”.
Other Meta’s
In the 1990s I learned there was such a thing as meta-rules – rules that govern rules. That led to RuleSpeak® – rules for expressing rules in structured natural language.[3] It also more recently ledto new thinking about the engineering of governance – rules guiding the creation, approval and dissemination of business policies in an organization. (Think rulebook management as governance infrastructure.)
I’m also pretty sure there could be metaprocesses – processes that orchestrate or transform other processes. It seems to me that one goal of intelligent agents is exactly that. What else? I’m no expert on that.
What other meaningful kinds of “meta” are there? It’s fun to play with the question words where, who, and when, but I don’t think there are any real “meta’s” to those. I could be be wrong. Thoughts?
I do have one strict rule for judging when you have something truly “meta”. Here’s my rule:
Some meaningful verb(s), not a preposition, must be used in defining a “meta” thing.
Examples we’ve already discussed:
Metadata – data that describes anddefines data. (You should not say just “data about data”.)
Meta-rule – rule that governs rules. (You should not say just “rules about rules”.)
Metaprocess – process that orchestrates or transforms other processes. (You should not say just “processes about processes”.)
Where else could you look for “meta’s”? Merriam-Webster UnabridgedDictionary (MWUD) defines the kind of “meta” we’re discussing here as follows[4]:
3b: of a higher logical type – in nouns formed from names of disciplines and designating new but related disciplines such as can deal critically with the nature, structure, or behavior of the original ones
MWUD gives these examples (the verbs are mine):
metalanguage – language for discussing languages.
metatheory– theory for structuring theories.
metasystem – system for organizing systems.
In science & research literature these days you commonly read about meta-analysis. An article in The Economist recently defined meta-analysis as “a technique which uses entire studies as single data points in an overarching statistical analysis”. In other words, an analysis that analyzes other analyses.
I wonder if there is such a thing as meta-architecture – architecture for designing architectures? That’s certainly an interesting question, and I’m not certain I know the answer. Thoughts?
I do know there’s meta-vocabulary – vocabulary that enables communication about vocabularies. That’s a central feature of the OMG standard SBVR (Semantics of Business Vocabulary and Business Rules).[5] I can tell you with great certainty that a meta-vocabulary is not the same thing as metadata – not by a long shot! I can also tell you that in a knowledge economy, meta-vocabulary will ultimately prove more important than metadata.
The Ultimate Metas
I believe there’s also such a thing as meta-knowhow – knowhow that enables the organizing of other knowhow. Unfortunately, as few business practitioners today know how important meta-knowhow is as knew how important metadata was in the mid-1970s.
That will change. And it won’t take long.
Meta-knowhow for organizing core operational business knowhow[6] is essential not only to play in the knowledge economy, but simply to contain the costs of operating as we do today. Best practices already exist for the area. Companies are paying a huge (and unsustainable) price for not engaging with them. I will have much more to say about meta-knowhow in the near future.
The most interesting and powerful “meta” of all, however, has to be meta-idea – an idea that enables the birthing (ideation[7]) of (other) ideas. These are the things that bootstrap whole cultures to a new level of intellectual empowerment. Examples: (the ideas of) libraries, encyclopedias and universal education.
In The Second Machine Age[8] the authors argue convincingly that with the internet’s true coming of age we’re living the next big meta-idea right now. It’s hard to argue the point. You (the reader) are experiencing it at this very moment. After all, how likely is it that we would be conceptualizing “meta” together here if it weren’t for the internet?!
P.S. The concept “meta” is itself actually a meta-idea. Now there’s a good brain teaser if you want to play with it!
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[1]Data Dictionaries and Data Administration: Concepts and Practices for Data Resources Management, by Ronald G. Ross, AMACOM (American Management Association), New York, 1981, 454pp. The definition of metadata in the preceding sentence is straight from the glossary, pp. 432.
[2] I mean the Merriam-Webster’s Unabridged Dictionary definition 1b(1): something that deals with what is beyond the physical or the experiential.
[4] MWUD’s meaning for metaphysics is different: 3a: beyond : transcending. It lists examples as metapsychosis, metageometry, metabiological, and metempirics(meta-empirics). Let’s not go there(!). The “meta” I mean (definition 3b) is far more specific and useful, even if highly abstract.
[7] MWUD definition: the process of entertaining and relating ideas.
[8]The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies, by Erik Brynjolfsson and Andrew McAfee, W.W. Norton & Company, New York, 2014, pp. 306.
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