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 10th 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]

Enterprise Portfolio Management -Thoughts and Insights

Woke up early this morning to the buzzing in my head…An idea that Options Theory as currently applied within more sophisticated enterprises for IT Investment was off the mark.  I’d spent the past year going through application of approaches such as Black-Sholes which for external markets tracks well.  However, for IT Investments there is something slightly askew.  That uncomfortable feeling of what and how finally popped in my head this morning.

Several things about the standard approach to Investment Markets Options Theory rely upon market forces to determine value.  However, within the Enterprise Ecosystem value is not measured by standard economics of buyer/seller in the traditional sense.  Arbitrage in the market does not apply in the traditional sense.  The investment is either exercised for its perceived utility or not; typically based and prioritized upon return on investment of the asset (in the broadest sense of the word asset).   In corporations however there are two economic systems at play:

  • External Ecosystem, the one in which the enterprise participates in.  Here the economics that investment professionals typically discuss and where options theory approaches such as Black-Scholes apply.  One can apply hedging as in Black-Scholes to capture the best Risk/Reward.  Within this ecosystem market dynamics have investments flow between investment vehicles based upon perceived future value.  With items other than perishable commodities the perceived value is not always inline with standard accounting practices.  When valuation of corporations occur Intangible assets such as “Customer Good Will” and “Intellectual Property” are used as a filler to account for the difference between residual value of physical assets in general accounting practices  (i.e., cadaver accounting) and investment accounting.
  • Internal Ecosystem, a set of economics that is governed more strongly by general accounting practices; costs and benefits must somehow be in balance.  However, a semi-closed system is assumed within such an economic system.  That assumption is later adjusted each quarter or year by increasing an Intangible Asset valuation on the books.  This ecosystem is driven by several factors: Asset Depreciation and Utility Value of Assets deployed.

These two economic systems interact through several interfaces of which not all are visible or easily measurable.  Monetary funds go into the Internal Ecosystem from the External Ecosystem on the assumption that these funds will be used to purchase assets and through utilization of these assets return more or increase in value the enterprise.  This in the external system takes the form of stock price or dividends.   Which in many US based firms now provides a stronger drive to the internal dynamics of a publically held corporation.

However, the value of individual assets inside a corporation is not as simple as those in the external ecosystem.  Inside the corporation assets are combined with a purpose in mind, to create a utility value.  While the individual assets are accounted for in general accounting practices the utility value of a configuration of assets is typically not.

An example; a machine is purchased, a process developed to use it and others to create a product or service, supplies/consumables are also purchased, and people trained to create and sell the product / service.  This creates some value if the product or service is consumed by the external ecosystem in exchange for revenue.   Ten years later the internal assets have been depreciated in value to zero, yet the enterprise is still getting utility value from this configuration of assets.  One year later a competitor’s product / service attracts enough consumers to make the enterprise’s offering unprofitable.  The assets once providing utility value, though zero accounting value through depreciation, are now in negative territory.  Now we’ll complicate things.  One of the assets in the configuration was a computer.  It can be reassigned to do other tasks thus extending its utility value in another configuration.

Thus the value of assets in an internal ecosystem’s portfolio needs to be managed differently.  Those management practices need to more strongly account for internal utility value that it contributes within an hierarchy of abstract portfolios that support an enterprise’s participation in the various value streams in which it is a member.  That insight realized this morning has been what has been driving me to revise the portfolio management practices I had defined for previous employers –though better than none– seem not adequate for the task.   With that insight in mind developing the economic methods –for what I’ve called Level 5 Dynamic Management that are closer aligned to how an enterprise operates internally– appears more attainable and palatable than just inserting a standard Black-Scholes model.

Enterprise Portfolio Management insights

This weekend’s brainstorming and reading brought up some interesting insights.  So much so I couldn’t sleep and woke up around 2am with the following visuals in my head.

First of was a refinement? on Govindarajan and Trimble’s concepts about two competing engines within an enterprise in their book Beyond the Idea.  Their proposed model theorizes whay its so hard to get innovations deployed and adopted in existing concerns while startups do not seem to have this internal conflict issue.

Gravity Centers in Enteprise

Second was an idea I’ve been refining over the years; that portfolio selection is not just a single event but a series of filters applied to narrow down the pool to the portfolio member to actively work on.  There are lots of models on sections methods (BCG Matrix) Balanced Scorecard, etc.  What is common to all is a concept of sorting and filtering members into groups, which creates a group of members to actively work on.


Portfolio selection is a filtering process

While these are not likely the final visualizations of the presentation I’ve proposed for an internal conference in February.  The metaphors speak clearly to me; I wonder if they do the same to others?


Project Trajectory Analysis and Risk Assessment

Spent part of yesterday reviewing one of the projects I’m on to analyze the risks and trajectory its on.  Part of this analysis brought up adapting an old technique my father taught me when he was managing large defense projects. It relied upon the law of large numbers but still seems valid today given all the interdependencies.  Instead of tracking expenses which are shown in the example, I substituted level of effort (LOE) in mhrs.  Along with the trend line function in Excel I was able to project likely outcomes.  Added to this was the interdependence risk DSM(s) I has previously started using which indicated where the highest risk elements in the project would occur.  I’ve yet to add a social or influence analysis to the tool kit but expect to have that as another DSM.

Lite Weight Project Management Dashboard   Component Risk from interface type DSM

The one significant issue using techniques like such is bringing the team along with the insights: As some people will not get it at first, Others will think you’re being a negative person, and still others will want to argue the validity of the analysis or its inferences.  Presented in the light of discovery rather than blame helps (i.e., mapping out my understanding yields this….is this right?  If so what should we do about it?).  This only works however, if you’re in a ego”less” culture and those you bring up have a vested interest in the successful outcomes.  That is if they don’t see the issue you bring up as core to their success, they are unlikely to care to address the situation, even if its for the greater good of the company (Ref: Tragedy of the Commons Systems Dynamics Archetype).

Structure in Threes: IT Business Models


Yesterday on the way back from client’s site I started pondering the intersection of Service Quality, Brand Value, and Business Models with regard to Information Technology.  Traditionally, IT functions had been focused around a product development model with operations being dragged in tow as a little more than after market support.  The only difference was that IT had a captive market or so the unconscious bias appears to be within these organizations.  As the IT industry has aged, other goal expectations were placed upon these organizations.  These ranged from being the gatekeeper to precious information, the controller for allocating technology & resources, and the integrating force between other parts of the organization. Whether it is possible for one function to successfully execute on all three missions is a topic for another post.

These expectations struck a nerve with me as I was reading Step Guide for Building a Great Company .  I have been researching business strategy, models and processes for most of my career.  As I read through the first few pages I wondered if IT Functions were not using the wrong business model.  In the past decade many IT functions are desperately trying to change their culture to a service oriented business.  Initiatives such as ITIL, COBIT, and SOA seek to inject a service mindset.  I think the objective is a laudable.  Having experienced a slightly less than customer / service oriented environment decades ago (a story for another time over a beer).

However, the typical service model that is put in place is one for a stabilized or mature business.  A business that has a standardized set of services that are being optimized, not a service that is constantly evolving which has been the nature of the IT function over the past several decades: Mainframes, PC/Workstations, Network, Internet, and now Cloud and BYOD.  This would not be considered a stable and mature industry as the technology keeps changing.  The  consider as the technology keeps changing new services are being either asked for or developed constantly.

With that fact I wonder if the business model IT functions should use is that of a Startup or possibly a bifurcated model that has service groups start out in incubators and move into optimization models as the service matures.  This is very similar to the extension’s I developed for another employer with regard to managing business portfolios.  I had based much of the initial work on The Alchemy of Growth: Practical Insights for Building the Enduring Enterprise adding another horizon and much more recently figuring out how to tie each horizon portfolio together using Real Options and Cluster Analysis.

In this recent expansion new services in ideation are considered a new business opportunity or new technology opportunity.  This determines if they are a Horizon 3 or Horizon 4 portfolio member.  As the internal market/business develops or the technology becomes understandable and stable enough to pilot these opportunities move onto the next portfolio where different operating rules and metrics are applied to manage these.

The result of using such a model makes the IT Function vertically integrated business incubator going from Founder & Angel Investor, to Startup & Venture Capitalist, to an stabilized operating line of business.   Which leads to yet another simulation model to build for my clients and possible discussion at next April’s Engineering Conference.

Structure in Threes IT Lifecycle Management: EOL

Spent a few minutes during breakfast pondering some of the issues around IT Lifecycle Management.  Specifically the term End of Life (EOL).  IT community is still a little behind other engineering disciplines in its understanding and application of this concept.  Take S/W for instance.  There EOL typically means either no more support for the product or that the product has been withdrawn from the market.  That is on the vendor’s side of the equation.  On the customer side EOL has other implications.  Does the application still operate and provide utility?  If so EOL is really a transition from vendor support to self-service;  think out of warranty for your car.  A third level of consequence are the customers of IT, the Line of Business that use the service based upon the application.  Does EOL of the application mean EOL for the service or does it mean a mad scramble to replace the utility by some other means.


This brings me back to the nuances I am exploring in Portfolio Management.  Currently one of the failings of IT Portfolio Management has been the lack of linkage between service utility and application serviceability in managing a portfolio.  Too often have a seen that second and third order consequences were not considered during portfolio decisions.  Y2K issues a decade ago are just one ripple effect of short term decision making.  The hierarchical model of portfolio I’ve been prototyping and testing appears to address this issue.  I’ve started to look at applying via usage strategies of Active Directory which was what I had considered when we came up with the conceptual design.  Only a decade or so behind schedule.  However, Cloud technologies may make implementations easier and harder now.  IT Financial Management approaches are on an upswing again so the timing might be right

Structure in Threes: IT Investment Strategy Lessons

This week as I continue to research IT Strategic Planning issues for a series white papers I’m writing I’m noticing more gaps in the average IT organization’s planning approaches.  Despite more sophistication in technology, the planning efforts are still rather primitive.   Many IT Planning organizations spend significant time on the technology requirements, functions and interactions; which they should.  However, when it comes to the effects and benefits to the business which they serve, these functions come up fairly short still.  The average business case just little more that a primitive ROI based upon very weak assumptions.  It is not wonder why CFOs and Controllers are tightening the screws on IT projects and considering outsourcing and cloud alternatives.  A few organizations I’m aware of are looking at eliminating their IT function entirely and moving everything to the cloud.

Review of prior Portfolio Management R&D at IBM

This coming week’s agenda is to develop the optimum means for presenting the Modern IT Portfolio Management process to executives and managers.  During the initial portfolio management R&D for business investment at IBM an interesting reaction was observed.  Executives and Managers disliked operating on models with more than two to three factors, preferring two factor matrices with binary values.  This was rather interesting observation in that each Stakeholder when surveyed asked for multiple factors to be evaluated.  However, in practice only a couple of factors are examined for consideration.  These factors typically center around near term monetary consideration.   optimal portfolios with high risk.  Thus other factors or strategies should be considered which infers a more complex matrix of considerations.

Lessons learned from Venture Capitalists

Venture Capitalists (VCs) evaluate investment candidates based upon returns like other investors, however, other factors are often used to classify and filter opportunities.  These are often used in what has been called a stage-gate process.  This is a series of smaller decisions that in effect gate weaker opportunities out of the pool of candidates.  This makes the decision not a single yes/no but a series of yes/no decisions.  The other aspect of a VC‘s investment process is the core to the portfolio management concept; multiple independent investments.  Typically this is accomplished by VCs teaming with other VCs enabling them to make smaller bets but spread amount a larger group of opportunities.  This strategy reduces risk by eliminating the eggs all in one basket approach.  The final strategy many venture capitalist used to mitigate risk is employing a variation of options theory.  Employing this strategy, VCs will often stage release of funds based upon a business venture’s ability to meet specific goals.  If a venture does not meet these goals the VC has the option to discontinue funding and cut their losses or potentially take a more active role in the management of the venture.

Other Research

Other areas of investment research under current study for this practice include:

  • Stock Brokerage [reviewing interview notes]
  • Investment Bankers
  • Insurance Actuaries
  • Natural Resource exploration enterprises