Economics, Cloud Economics, Cost of Information, Information Economics, Price of Information, Value of Information

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Big Data As Defined By Constraints: "Camel Meets Eye Of Needle", Or, "Surviving Your First Week On The Job"

Needle-And-ThreadCamelIf you are an executive charged with a "big data project", here's a prediction. On your first week on the job you'll likely be surprised. And the surprise concerns what you'll actually spend your time doing.

What might be the surprise on your first week on the job? The surprise is that your biggest responsibility won't concern what you thought you signed up for, which is likely something like "generating analytical insights". Rather, your biggest responsibility is almost the opposite, which is focusing on everything but generating analytical insights.

And if you've been dreaming of fishing in sea of data, with a big net to scoop up any of the myriad insights just swimming by your boat, your surprise might even be one of disappointment. Because this blue ocean metaphor, lovely to imagine, is also seriously misleading about the nature of the world of big data. It's more likely that your ocean will consist of nothing but fish, all of which have three eyes and which are inedible! You'll have lots of data but nothing to take home that you can call a great insight.

Here's the problem, which could define the basis of your surprise, your job responsibility and the sort of metaphor that you should use to describe the world of big data. The problem with big data concerns the very definition of big data, which is that it is "big" -- but although big is subjective, there's a very practical and non-trivial definition of "big". Your set of big data is defined as such if it is too big for any of your machines to process in one chunk in a reasonable amount of time. In other words, the world of big data is defined by the system capacity constraints.
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Value Of Information: Three Decision Criteria -- And Applicability To Cloud Services

Would you like to learn a secret about how to be more successful in the coming year? Either personally, or as a manager or professional?
 
OK, this trashy "come-on"  is only justified because it's almost year end (2012), and time for lots of management how-tos, especially "how to cope with information overload".  Most of the advice is common sense, and if we are very disciplined, might even help us to be more effective.
 
But how about some advice that might actually work?  
 
This blog post is about managing more effectively by considering the cost and utility of information.  So much of our work every day is spent wrestling with information management,  And information has a whole lifecycle, from identification of need, to acquisition, usage, curation and even secure destruction.  In fact, much of common sense management advice is about better information management.  (It's not for nothing that computers and software are collectively known as "information technology".)

A Three-Part Business Case For Business Process In The Cloud

Stork-At-Sunset-Over-WavesNo business person really cares about technology except insofar as that technology helps get the job done. But there's one technology that's different.

Unlike most or all other technologies, BPM software technology directly and explicitly concerns the work of business and can be therefore directly of concern to business-side executives. Ultimately, business process management software (BPM) is THE technology for getting work done.

Let's explore this proposition in more detail, and then see why the question of BPM is exciting in the context cloud technology. (This posting was originally featured on the Canadian LinkedIn discussion group Cloudfingr.)

There are many important business-enabling technologies, including technologies "further down the stack" (e.g. "SOA") or which hard-code business semantics (most "ERP" systems and purpose-built applications).

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No More "Wait States" -- BPM Opportunity Puts Pressure On Business Executives

Waiting In Line GraphicOn his ebizQ blog, Peter Schooff, asks (September 2012) "what is the number one reason a BPM project fails?"

Asking this question is audacious. But important.

Here's the short answer: BPM projects fail at a rate higher than tolerable (thus the question) because BPM projects, being fundamentally different than all other IT projects, are not yet sufficiently supported culturally, organizationally and economically.  

In particular, a BPM projects puts pressure on business executives for detailed process leadership, a time-based pressure without precedent and for which many or even most executives are not ready.

The first response to ebizQ's question, from Emiel Kelly, alludes to these issues with the statement that BPM is seen as "a project, not as daily business". Subsequent comments by other contributors elaborate in worthwhile ways. But it's worth making Kelly's "not as daily business" explanation more explicit.

Specifically, from the original answer above, what does it mean that BPM projects are "fundamentally different", and why is this difference important? And what is "cultural, organizational and economic" support?

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Gorillas On A Slimming Plan - Five Limits To Bigness - Including A New "Deficit of Trust"

Geoffrey Moore of "Crossing The Chasm" fame, asked a question on his LinkedIn page concerning possible limitations to the growth of market gorillas ("Why Gorillas Don't Rule Everything").  Understanding the effect of corporate size and concentration is important for both individuals and organizations that must operate in a world defined by monster organizations.   The purpose of this note is to identify the top five factors limiting the optimum size of organizations.

Note that that your host is not making any assumption that corporate size is necessarily a bad thing.  Although it's a separate topic, and acknowledging that there are clearly many downsides to large organizations, there are all also examples, supported by research, showing that large organzations can also have many positive attributes, and that by

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Zachman @ IRMAC – Charisma Versus Chaos

 Is it possible to more completely grasp the idea of “enterprise”? 

And thereby submit that enterprise to the will of executive leadership?

John Zachman, well-known evangelist for enterprise architecture and originator of the Zachman “Framework for Enterprise Architecture”, says “yes”.

Canada’s DAMA affiliate IRMAC scored a coup last week by hosting Mr. Zachman on his road show for an update of the famous Zachman Framework.   Mr. Zachman gave a comprehensive tour of the Framework, the reasoning behind it and the advantages that adopting organizations might enjoy.

Mr. Zachman’s key message was that the application of normalization and ontological modeling to low-order, high-entropy organizations – i.e. organizations which are failing due to high cost structures and sclerotic inflexibility -- would reverse that state.  The sciences of organizational normalization and ontological modeling, defined by the Zachman Framework, unlock enormous benefits for organizational stakeholders

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McKinsey On Sales Process Failures -- Also, John's Comment -- "Ironic Lack Of Theory"

Unused PhoneThe boffins at McKinsey have just issued a stirring call to "free the reps"!

According to the consulting company, at one representative global firm, 75% of inside sales reps' time was spent not selling!

This frustrating sales situation is not uncommon, despite what McKinsey says is "the guiding principle of all sales operations", which is "to maximize time for selling and relationship building".  Of course sales people and sales executives, and probably even general management, all know that sales people should be selling.  But given that sales people everywhere are facing similar issues, it's helpful to have a spotlight on the situation.

As a professional B2B sales person focused on BPM, your host is naturally interested in the subject of the McKinsey article -- and how BPM is one point of leverage for improving sales operations.  The McKinsey article also raises larger questions about sales management; your host has now commented on these issues in the letter below. 

You can read the whole McKinsey Quarterly article and follow up reader comments including your hosts' comment, at the following URL. (Please note you will need to register, although there is no charge.)

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Software, Ontologies & "The Semantic Ceiling"

Is it possible that even with today's excitement and real achievement in software and technology, especially around mobile, M2M ("machine-to-machine"), the IOT ("Internet of Things"), analytics, so-called "big data" and machine learning, just to name a few hot topics du jour, that there is a major roadblock to further easy progress in technology?

After decades of achievement in the development of software technologies and software engineering, the software industry is rightly acknowledged as having contributed enormously to every aspect of business, social and personal life.  It is a general belief, fostered by both science and culture that a "long revolution" based on IT will continue on, bringing ever more amazing, delightful and useful innovations.

This expectation of progress can probably be depicted as a linear function with a nice upward slope.  While "Whiggish" expectations of continual progress are nice, the reality of software engineering is less rosy.  The realization of future progress based on software technology may not be so easily achieved and the immediate future of software development may be disappointing.

Why is there a potential for disappointment?

The current state of software engineering and data management is characterized by what could be called a "semantic ceiling".  On the software engineering side, the newest software products and software development are, while often quite wonderful, still rather limited in what they accomplish:  mashups, social applications, situational applications, modeling tools, more SOA, point business applications etcThe scope of these new applications is typically either siloed or trivial in some sense

Especially on the data management side, the growth of data resources has exacerbated the data chaos that confronts both business and individual trying to make use of technology.  For this reason, it is not surprising that master data management (MDM) is a hot area in the software business.

The idea of a semantic ceiling is the idea that further progress in software engineering will only be possible with the development and deployment of a new layer of semantic technology.

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