Speed, Simplicity, and Results – an equation that often doesn’t balance

How often have you heard in the context of entertainment, he or she was an overnight success? Only to find out later it only took x numbers of years to become such. In an Internet age everything, everything appears to be instant including out coffee.

The Internet brings us everything instantly, or so we think. How long did it take you to get that book from Amazon Prime? Two days, not fast enough! Get a Kindle and get it immediately! However, what are you missing with all that speed? What are the trade-offs? And yes there are tradeoffs.

Like old lessons in engineering, nothing is free, one always has tradeoffs to balance the physical equations. You may not see these or be conscious of these, but these are still there in the background being made. Which is the main point of this article.

It may seem from the start that some old guy is about to pour his heart out about how good times past were. -And yes, they were good. However, what Millennium isn’t already reminiscing about that great time they had at the club last night or even brings it up several weeks later as their friends roll their eyes having heard the story for the fourteenth time already. Good and bad times cement lessons in our memories. But I digress.

Years ago, before PMI existed, project managers latched onto the concept of the Project Management Triangle: Time, Cost, Quality -picking any two dictated the other. Heuristic Functions like this are applicable today as much as we’d wish the Internet would change these.

I’ve working on several projects over the past few years –well decades—each a part in a much larger equation. My previous article, The Virtual Situation Room, hints at such. One fragment of that equation involves Business Intelligence as it’s called today. That is having not only data but information for decision makers to make effective investment decisions within the business. I consider N. Dean Meyer’s Internal Market Economics as a data point in the growing digitization of business.

As such any resource decision –Capital, Intellectual Property, Human, Equipment, etc.—is a statement of internal investment priority to address what Milton Friedman stated as business’s primary if not sole justification: maximizing shareholder value. [While I disagree with the total adherence to economics of selfishness, it is the current trend in business, but I see the pendulum swinging in other direction, hopefully to some middle ground.]

Current Internal Economics aside slightly, I come back to the engineering premise that tradeoffs are made in any decision to balance an equation, often unstated. A brilliant colleague of mine Dr. David Ullman, out of the Oregon academic society, attempted to explicate much of those tradeoffs using an application of Bayesian Analysis. Only to end in frustration. The Business World was not ready for such ideas 10+ years ago, nor the work involved to get those “simple answers”.

Speed is a relative term in Business. What is fast one day, is tortuously slow the next.

Simplicity is also relative and is based upon context. What I see readily apparent, maybe intricate and complex to you.

 

Thus we’re left with Results as the great common ground, or so one would think. However, results are based upon expectations, experience, and context. I order a meal at a restaurant. They serve me my food within a ten minutes, I eat it and don’t get food poisoning. Is that the result I was looking for? Was it satisfactory? Before you answer consider these two scenarios both fit the facts above. First I was at a Fast Food place, the second I was at a 5 Star restaurant.

If all my expectation was to get a quick meal and move on, then a Fast Food experience was adequate. If, however, I was with others and make this also a social experience the above maybe lacking.

So what does this have to do with internal business projects you’re asking now?

Consider the nature of questions leadership has to address. These are often boiled down to quick decisions: Go, no-Go, and Redirect to consider later. They are often looking for simplicity to enable speed in decision making. However; first simplicity often hides important information, and second I’ve always found it takes time to create simplicity. Boiling data and information down to its essence means understanding the truth nature of the decisions to be made and the interactions of variables in that decision.

This morning I am on the 10^th iteration of a Portfolio Management initiative I came up with in ’95. I am using writing this article to reflect and document lessons learned for these activities for an upcoming paper for a June Business Architecture conference in DC.

A few insights I’ve come up with this morning as I look back on the various version of this initiative are:

• Decision-Makers appear to have less and less time to assimilate the information
• Simplicity is good for speed but often hides the icebergs ahead; so these captains of industry need someone in the crow’s-nest to look ahead
• Decisions are often made by gut feel, even though analytics has proven to be more accurate
• Follow-up on results while desired is often not accomplished: Many organizations are professing a learning culture, however the current state of being is most reviews are still flagellation inquiries [management is still a political game]

Structure in Threes: Integrating Finance and Engineering approaches to Risk

As I continue researching risk elements for designing and enterprise, it is interesting to see how implementing risk management translates differently depending upon your discipline.  Finance focuses on of course financial risk; the various forms risk takes with regard to translating investments into returns in a monetary sense.  While engineering disciplines focus upon risk that effects the degree of achievement to performance goals of a product or lately service.  Both disciplines acknowledge the others concerns but often do not provide the linkage between these.  Finance will often categorize engineering risks into buckets called operational and strategic/business risks.  Engineering will lump the various economic risks into a single bucket called financial risk.

This is mirrored in how Business Continuity/Disaster Recovery(BC/DR) and Enterprise Risk Management (ERM) are implemented in most corporations. The BC/DR practices focus on the engineering risks of project, process and product, while the ERM practices direct attention to the financial aspects of the enterprise.  What seems to be missing is the linkage between the two.  The interrelationship between the two or cascading effects appear to be a neglected concern.  This maybe due to the nature of our western culture or increased specificity of roles within corporations even in white collar positions now.  The role of the generalist or systems thinker has been diminished or dismissed or possibly transformed.  More and more of my systems thinking peers have become entrepreneurs, possibly because they do not fit the new organizational models or appear to be in direct competition with mid-level management.  This is odd in that first line and mid-level management no longer have the time to consider various degrees of consequences of actions and decisions or alternatives, but is the stock and trade of systems thinkers.  This may be one of the root causes to several of the catastrophic failures of the economic system, geo-political relationships and technology achievement misses.

Today’s research continues down the path of system dynamics and identifying the linkages between financial and engineering risk management.  It may turn out that there is no true mathematical formula that links these and the best that can be achieved is to use Bayesian logic to create priorities for a balanced scorecard that reflect enterprise values and then monitor how these correlate to the ecosystem.  Which brings me back to using system dynamic models and validating these with actual performance in the real world.

In my opinion , despite the emergence of BI and Big Data, application at this level is still years away.  The majority of enterprises and thought leaders are still at a primitive level when thinking about exploiting such technology.  Think of how sophisticated and how long it took to apply various influence and behavior models in the marketing community.  Then consider the effects of having too much information, creating an information glut.  While computers are great at dealing with volumes of data, we humans are not.  We still need to deal with the limits of cognition.  Despite all the hype about multi-tasking, the facts are coming out, something is lost when you try to focus on too many tasks at once.  In fact you’re not actually focusing on them at once, you are switching attention between them rapidly (page swapping) and eventually you either reach a limit where you get nothing accomplished or a catastrophic event happens: Texting while driving during the Grand Prix is not a good idea.  What this suggest is that it will take a long time to really sort through BI and Big Data’s potential into something practical verses creating more noise in the enterprise system.

Projects Past

As part of my office relocation project this month I’m reviewing, purging and scanning materials from my project archive.  Today I scanned a few of my 1980s projects at Rockwell International and Lockheed.  It’s amazing all the advanced R&D these companies gave me to do:  Building a PDM for the B1-B program, Developing and implementing Product Lifecycle Management, Group Technology Based Shop Floor Scheduling, Automated Archive and Retrieval of CAD drawings, Predictive Analytics of Aircraft Systems and Engines.  I wonder if current executive management will understand the lessons from this era; real mentorship, the discovery projects (e.g., IR&D), and the value of think time.

Its also amazing how we managed to design and build these system with little automation and tools:  Modeling and Drawing tools such as Visio and ITHINK were not available. I started using a CAD/CAM system –Computervision CADDS III & IV– to diagram and flow chart as personal computers (no IBM PCs on market yet) were just starting to become available which resulted in senior executives asking me to build diagrams fro their projects also rather than using the graphics department.   I started studying some of the works of IBM guru’s then to add to my intellectual toolkit; Ed Yourdon, Gerald Weinberg, Tom Demarco. Robert Benson, and later John Zachman etc.   Never did I think I was going to continue in the IT field, join not one but two of the greatest IT companies (IBM and Microsoft), and have as mentors these greats in industry.  Today I’m still privileged to not only still maintain associations with such people but asked to collaborate together at times.

Structure in Threes: Business Continuity / Disaster Recovery

Several months back I had released the first four parts of a White Paper Series on Business Continuity / Disaster Recovery Strategy for Microsoft’s Services.  During my research & brainstorming efforts for the series I became aware of just how fragmented the entire domain was.  There are efforts in Finance; Information Technology; and Corporate Governance, Risk and Compliance functions.  However, collaboration between these functions on the topic of protecting the corporation are often non-existent.   This fact become further evident to me during a discussion I had yesterday around an old engagement on Y2K mitigation.  I was discussing an old consulting engagement with a group director.  He had wanted to get a handle on “How I Think”  –I though it reasonable, but unlikely to succeed objective, but was willing to give him the best opportunity to do such.  The unfortunate think about discussions like this is these require similar knowledge bases and context as often terms and concepts are used to relay deeper meanings.  If you’re not aware of these materials its like hearing a foreign language; you may pick up some of the tone of the conversation but the deeper meanings are lost.

To continue while discussing the engagement I had started to think about how to integrate these three Business Continuity / Disaster Recovery function’s focus around ensuring business survival in context to Portfolio Management.  Clearly, the financial planning specialist consider these goals.  Then another recent request for information and conversation came back to me regarding the Future of Wealth Management Branches.  This past year I’ve been getting lots of inquiries from various Wealth Management and associated  groups about what they can do for me.  Or may be I’m just more attune to the messages this year due to the topics I’ve been researching and developing Intellectual Property around.   From the synthesis and analysis of the data I had been collecting, the financial services industry around this topic was just as fragmented as businesses itself.

–As an side, it was appearing to me to become the organizational equivalent of a Fractal, now you see why I though understanding my thinking process was going to be difficult.  I’m continually developing broader and deeper knowledge base, like most people…however, I spend time generalizing these into patterns and looking how to connect and integrate these into my broader knowledge base.  This was the foundation for my company Intellectual Arbitrage Group.  Which later I discovered a small collective of other people are doing also; Genrich Altshuller whose methodology TRIZ is a brilliant formalization of the process I go through is one example.–

So as I review the outline for my book project I’m starting to see another thread develop which also looks to be another triad.

If a capabiity grows in the forest does it solve a problem?

Don’t want to bust anyone’s balloon.  However, despite all the hoopla, Big Data and BI are still as Gartner has labeled it in the early stages of the Hype-Cycle.  While the technology is approaching critical mass, the market is still hasn’t crossed the chasm.  That is not to say vendors of such capabilities are full of puffery –actually not.  The problem become one of Strategic Execution and Exploitation.   Over the past ten+ years I have been actively engaged on and off on what arguably could be call BI and Big Data projects [Yup ten+ years!] What I’ve experienced from these projects is that for a first for IT, they’re ready before the line of business is to deploy the capability.  Example: one instance, I developed an approach to infer what markets are heating up and which are cooling off.  It took sales data, several other sources of information and some basic statistics -well may be a tiny bit more that basic statistics.  The result was a heat map for geographic and industry market segments.  The Marketing Executives were impress; not with what the data indicated, but with the fancy graphics.  Clearly the message was lost in the media.  A few years later I went back to check the forecasts, surprised by how close the predictions were.  The sad aspect to this adventure, the system I spent time building before I left was lost to missing competency, thus the application was discarded as no one new how to use or what to use it for.

Fast forward several years.  A colleague I was mentoring was asked to build BI capability for the company she just joined.  Not a cynic by nature, I asked some fairly cynical questions:

1. Do they know what they are going to do with the capabilities?
2. Do they know what problems / questions they’re going to apply the capability to?
3. If you build it, is there anyone that will know how to operate it?
4. Does anyone have the background in statistics and analytics to understand the results?

The scary answer I got back was actually no across the board.  The various departments had barely a remembrance of descriptive statistics.  Concepts like correlation, confidence level, linear regression were vague labels from a statistics class they had years ago.  It immediately drew me back to my engineering/manufacturing past and the comments attributed to Kelly Johnson (Lockheed Skunkworks): “I don’t need more computers, I just need more engineers that can read slide rules”.  The comment infers that Kelly was anti-computer and that’s not really so.  What I understood from his comment was you needed people that understood how the computer solved the problem and the range of where the solution should be, otherwise you’re at the mercy of the computer (i.e., The computer said…)  As another wise pundit said “Computers make great slaves, but terrible masters”).  Not understanding the underpinnings of how the capability works (not necessarily the computer logic) leaves you at the mercy of the computer.   This not to say leaving the grunt work to the computer is bad, but to continue the old adage-feast I’m on “A fool with a Tool is Still a Fool” or “When all you have is a Hammer, everything looks like a nail”.  Thus not all problems are suited to be solved by BI and/or Big Data, this is were Enterprise, Business Architects, and Solution Architects come into play.

Originally I was going to discuss BI and Big Data, however, in the end I’ve come to the conclusion the true value of Architects is not in the plans created to guide construction, but  in the questions asked to ensure what is built solves the enterprise’s problems and provides true value.  In ending If a capability is created and nobody uses it is it of value?

Start of my book for comments

 

  

The Business Bermuda Triangle

The Convergence of Business Intelligence, Performance Management and Business Process Management

Brian Keith Seitz

 

 

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The Business Bermuda Triangle

 

[Quotes from friends and colleagues]

 

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The Business Bermuda Triangle –The Convergence of Business Intelligence, Performance Management, and Business Process Management

Brian Keith Seitz

Copyright © 2008

 

 

All rights reserved.

No part of this book may be used or reproduced in any manner whatsoever without written permission of the author and the publisher.

 

Printed in the United States

Cover Design by Intellectual Arbitrage Group, Eatonville Washington (360) 832-2025

 Library of Congress Catalog Number:

ISBN: 

 

 

 

 

 

 

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“Zombie Zone”  and “Smart and Simple Marketing” is a trademark of Intellectual Arbitrage Group, B.K.Seitz & Associates, and Brian K Seitz, denoting a series of products that may include but is not limited to books, pocket cards, white papers, calendars, audio cassettes, CDs, Video tapes, DVDs, Seminars and Webinars.

 

Published by:

Intellectual Arbitrage Group

a B.K.Seitz & Associates subsidiary

36203 Pulford Road East

Eatonville, Washington 98328

 

 

Order Information

To order more copies of this book or receive a complete catalog of other products by Brian K Seitz contact:

Intellectual Arbitrage Group

By calling:

(253)219-8977

 

 

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Other Stuff

By

Brian K Seitz 

 

 

 

 

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Acknowledgements

Joel Orr	Dana Campbell-Seitz
Brad Holtz	Steve M Smith
Stanley Seitz

 

 

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Dedication

Dedicated to:

My father and role model Stanley S. Seitz

My mentor Michael Kutcher

In addition, my wife Dana –for her inspiration to put down on paper what I have spent a lifetime collecting and her loving badgering to just do it.  I may not have always appreciated it at the time, but afterwards I do.

 

 

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Table of Contents

What is so intelligent about your business?. 1

A Rose by any other name. 1

A simple map of business intelligence. 1

Operational Intelligence. 1

Financial Intelligence. 1

Market Intelligence. 1

Organizational Intelligence. 1

Building a business nervous system.. 3

Business Intelligence Taxonomy. 3

The magic number seven. 4

Operational Nerves. 5

Financial Nerves. 5

Marketing Nerves. 5

Market Planning. 5

Customer Service. 5

Execution. 10

Organizational Nerves. 10

Ensuring your business intelligence is used intelligently. 11

Appendix. 12

 

 

 

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What is so intelligent about your business[b1] ?

 

 

 

 

A Rose by any other name

What is business intelligence?  Throughout the past several decades, various terms, concepts and technologies have been associated with the term.  If we look to human intelligence as a model for business, there are multiple forms of Intelligence. Dr. Gartner in his book defined several types of intelligence.  Each of these described various behaviors and attributes of humans, all of which are considered intelligence.  To add to this collection of intelligences others have branded other types such as Social, Emotional, and Moral.

If humans can have multiple types of intelligences then businesses which are nothing more that associations of people, processes and technology must also have the same.   For a type of Intelligence to have relevance in business, it must have several qualities: measurability, etc[b2] .             

 

A simple map of business intelligence[b3] 

 

• ·         Operational Intelligence
• ·         Financial Intelligence
• ·         Market Intelligence
• ·         Organizational Intelligence

Operational Intelligence[b4] 

 

Financial Intelligence[b5] 

 

Market Intelligence[b6] 

 

Organizational Intelligence[b7] [b8] 

 

 

 

Building a business nervous system

Business Intelligence is about gaining insight how a company operates and competes; to do this a business must be able to sense, measure, and analyze the attributes that effect its survival.  Were a company a biological organism this would be called a nervous system.

Nervous Systems enable both organisms and corporations to be aware of both internal and external conditions that both threaten survival and foster growth.  Without awareness of conditions entities often fall prey to those conditions.

Prior to building a nervous system, understand the taxonomies of the components of such systems and the decisions that need to be made based upon specific corporate culture and architecture is needed.

Business Intelligence Taxonomy

Understanding the Business Intelligence, landscape suggests that a map is necessary.   The primary map proposed here is offered as a simple visualization of function and location of decision making.  These dimensions were chosen as they most accurately reflect the application decisions corporations are involved today.

 

Intelligence Functions

 

Location of Decision Making dimension in the 50s was a fairly easy decision; the corporate mainframe or service bureau.  There really was no choice.  Computing and Data Processing was such an expensive undertaking all applications were corporate applications as the technology costs and maturity prohibited desktop processing.  With the advent of the integrated circuit the Personal Computer became possible that enabled processing power at the desktop.  This revolutionized and liberated decision making for all sizes of businesses. 

The end result was to expose that there are different types of decisions made, by various people within the organization that had various spans of effect on these businesses.  Thus not every decision needs to have a corporate decision support system, even if corporate data is being used. 

The magic number seven

Building a management system that creates and uses business intelligence is not really a technical challenge.  I can hear CIOs all over the world moaning and yelling now.  However, if you really think about it, the technology, tools and skills to build a world-class I.T. infrastructure to support B.I. are already in place or can be had fairly quickly. 

What is not in place is a definition for the specific business what needs to be measured and managed from a strategic perspective.  Once that is determined how it is to be measured and managed.   During my years of being brought into fix failing projects, reengineering processes and organizations I am always amazed at how complicated the management system has become.  This is not a phenomenon limited to just one type of business.  Companies needlessly overcomplicate monitoring and measuring.  There seems to be a mantra, if a little is good more is better and even more is great.  It just is not so. 

In today’s business environment, we are bombarded from every direction with data, most of which does not add anything to the decisions we make and execute.  There was actually a term to describe this coined in the 1990s: Information Glut.  Executives, Managers and Employees are now faced with problem on a daily basis.  New tools and techniques were developed to help address this self-induced problem.  There are actually consulting practices and gurus in the field with systems on how to be more productive and prioritize the things on your desk and in your in-basket. Most of these focus on reorganizing materials into piles you have eventually do in some priority order. I am not sure I would call this management.

In 1956, George Miller published an article in The Psychological Review “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information” that change the way people think about are abilities to manage information.  In that article, Miller professed there was a limit to the items a human being could manage effectively.  That number was seven, plus or minus two.  This was before the ubiquity of the personal computer.

Shortly after this article, many businesses started capitalizing upon this phenomenon.  The telephone company started clustering or chucking numbers together to make them easier to remember.  The federal government limited the numbers in a zip code and when they expanded the zip code, they chucked the additions into a dash appended to the original schema.   Personal Productive grew significantly.

When the digital computer was introduced and then later the personal computer, its first tasks were mathematical calculations.   Endless columns of numbers were processed and spit out in wide green bar fanfold paper reports that were barely digestible to only the bravest of executives.  As the computer was applied to other type of information processing tasks, the message of simplicity and effective human processing limits was lost in our zeal to use this new tool. 

Today information technology has become embedded into the very fabric of companies.  This is true whether one is conscious of this fact or not.  The benefit and the liability of this has been connectivity but not integration.                              

 

Operational Nerves

 

Financial Nerves 

 

Marketing Nerves

Market Intelligence unfortunately has been limited in scope to snooping and discerning what competitors of the company are doing.  This however skews the focus of the company aware from holistic survival and growth towards simply watching and reacting to the nearest and most visible competitors; enabling other threats to a company’s survival to go unnoticed.  

Market Planning

 

Customer Service

O

ver the past several decades there has been a lot of discussion around customer service.  Numerous books have been published extolling the value of extra ordinary customer service or promoting the slogan the customer is king.  Many organizations are now investing in Customer Relationship Management (CRM) Systems, Reengineering Customer Service Groups and significant training programs to improve customer satisfaction.  

While good or better still extra ordinary customer service is a nice idea, at what price is investing and improving customer satisfaction worth the effort?

Suppose your company invested two million to purchase and deploy a CRM system throughout and improved your customer satisfaction rating from a 65% to a 75% rating.  These sound like good results for your investment.  However, at the end of the year did this investment really affect the bottom line in a positive manner?

Customer Service Metrics

All too often companies invest in improving a rather vague measurement called customer satisfaction.   This metric is gauged typically by some survey asking the customer how satisfied are you with what you got from the company on a scale of 1 to X.  While for a quick snapshot like these sounds good, measuring this way gives a corporation only half the picture: Customer Attitude.  

Customer Attitude in surveys only tells you the customer’s state of feelings not his or her behavior toward the corporation.  I may have a satisfied attitude toward my purchase but does that mean tomorrow I’m going to purchase some more from your company or go out and tell everyone how great your products and services are. 

Having a customer satisfied is equivalent to being apathetic.  A satisfied customer is well, satisfied.  That means the customer’s needs have been met and does not see much of a value in pursuing any further relationship or procuring additional products and services.   It neither helps nor hinders you company.

While a delighted customer may be more incline to seek additional products and services of potential value from you, evangelize your company or both.

Likewise I may have a customer that indicates that they are not satisfied but still continues to purchase products and services at your current or increased return on investment.

This brings one to the next aspect of customer service measurement; Return on Investment.  At one end of the spectrum Customer Service is an added expense to fix mistakes in products, services, marketing and sales.  At the other end of this continuum customer service can be a profit center.  Customer Service can be a rich source for new requirements and product ideas, developing insight for marketing, leads for sales and also revenue.

Many software development companies had turned their customer service departments into profit centers that customers are willing to pay for in maintenance contracts and charges.  Some types of customer service customers see tremendous added value[1] and are willing to pay significantly for, while others are perceived to be of limited value and expected to be absorbed by the vendor as the cost of doing business.                  

Customer Service Effectiveness Matrix

 

Brian K Seitz © 2008

Before investing in customer service or specific customer service initiatives a simple check of effectiveness is desirable.  A way to gain perspective and insight on the effects of initiatives is to visualize the two metrics in a matrix.

By taking the time to determine customer attitudes accurately you will be closer towards making investment decisions that do more than just make you feel good that you did something.  The next step is to look objectively at your customer service and investments to determine the cost effectiveness. 

Questions to asked are; how much do I currently invest, what do I get in return, and can I get the same or better returns another way?

The simplest way to evaluate this is to capture customer service costs as they relate to revenues. Establishing a monitoring system such as this is beyond the scope of a traditional accounting system.  Thus, new types of applications have been developed to address the need such as dashboards and performance monitoring servers[2] that provides a rich set of capabilities and almost limitless scope of flexibility through programming.

 The unfortunate aspect of Performance Point Server and any other application that provides so much capabilities and flexibility is that it comes with a cost; increased complexity and learning curves.  This does not have to be an obstacle though, if you spend time to define what you are trying to accomplish instead of “fishing with metrics” hoping some improvement will happen magically because you are measuring things.  While something may happen similar to the Hawthorne Effect discussed so often in business school case studies, it may not be the desired results you hoped for.

Zones within the Matrix

 

Zombie Zone

The Zombie Zone is sinister in how it saps the vitality from a company without it being aware

The Zombie Zone is that area of the matrix that traditionally never seems to get much attention from management.  It shows up neither red as a crisis nor green as superior results.  While these appear to be nothing terrible to report, this can be deceiving.  The Zombie Zone is almost sinister in how it operates.  The news and effects are not bad enough to attract management attention and intervention in the immediate context.  However, over time, this constant malaise saps a corporation’s resources and drains its vitality until suddenly all its reserves are gone when a new challenge arises in the same area.

The Zombie Zone is the organizational equivalent to the boil frog syndrome[3] where it is professed that a frog is insensitive to slight changes over time as opposed to a sudden change thus enabling someone to boil a frog with slow incremental changes.  While there is dispute about the truth of this myth, there is no doubt that organization due tend to ignore slow incremental changes in the business climate unaware of the threat until it becomes a crisis.

Being in the Zombie Zone is not a desirable state to be in.  It gives you a false sense of security and control; “My customers are not complaining that much so everything is all right”.  Meanwhile marketing and sales costs are increasing and profits margins are harder to maintain.  Your organization sees no imminent crisis to address so is hard to motivate and resistant to change. All of this should tell you your corporation is in the Zombie Zone.  Working while asleep at the wheel ignorant and unaware to its plight and potential fate.                

Life of the Party Zone

 

 

 

Eventually you wake up with a terrible hangover

 

 

 

 

Execution

 

Organizational Nerves

 

 

 

Ensuring your business intelligence is used intelligently

 

 

The triad that created the Business Bermuda Triangle also creates the physics behind the interaction between each.  A business to fulfill its primary mission, to survive and grow, needs to balance each of these functions and the underlying forces that created them.

Too much of a good thing, is too much.  If a business builds up its market sensing capability to such a degree that it dominates its business; over the course of time, it will become non-competitive as the tendency is for such organizations to become backward looking, always looking over its shoulder to see its competitor’s actions.

 If a business becomes obsessed with business performance management, here too the fallout will be poor results; measuring everything and understanding nothing.  Performance Management is a good strategy to follow, however, here the 80/20 rule definitely applies.  If a company is spending 80 percent of its time and effort managing and monitoring and 20 percent producing product and/or services its margins will evaporate in overhead costs.

While Business Process could be, consider the older brother of the previous two or possibly subsuming these, the obsession to manage the process above all else can turn a profitable enterprise into a dogmatic dinosaur over the course of its lifespan, unaware of its impending doom.  The case for having and managing processes, creating and managing business rules is strong.  However, without introspection and revisiting these from time to time the company will become caught in its own successes and failures with the refrain “We’ve always done it that way”     

 

 

Appendix

 

 

 

 

 

 

 

 

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[1] During the 1970s through the 1980s IBM used the term ”IBM Added Value” to describe the system engineers and support personnel that were assigned to customer accounts to ensure product deployment and full utilization.  These services appeared to be free but in reality the cost and allocation of resources was factored into the purchase price of installed products.  If a Customer Account reduced its IBM footprint an equal reduction in support resources followed.   

[2] This paper will provide an overview of creating a Customer Service Performance Management System with Performance Point Server™ in later sections.

[3] G. Stanley Hall and Yuzero Motora, “Dermal Sensitiveness to Gradual Pressure Changes” American Journal of Psychology 1, No. 1. (1887): 72-98, on 72-73.

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 [b1]Change title focus to convergence of BI/BPM/Perf Mgt

 [b2]Detail out this paragraph

 [b3]Introduce various domains of knowledge and the BI component for them

 [b4]The mechanic of how the organization operates including processes

 [b5]Knowledge of how cash flows and is used by the organization

 [b6]Knowledge about markets, competitors, products, customers, and behavioral dynamics of translating a company’s offering into revenue and profit

 [b7]Understanding of how organizations operate, how to build effective teams that support organizational goals

 [b8]Intro to the concept that is further detailed out in chapter three