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Tag Archives: decision making

Simplicity is the Ultimate Sophistication

 

In an effort to improve my “working out loud” chops, I’m learning from a friend who has begun sharing the text of (not links to) his blog posts on Facebook and LinkedIn, as well as on the blog he’s had for a very long time. <Light Bulb!> This one’s a kind of reverse emulation, as this is something I shared on Facebook first.

Simplicity - Da VinciI have found an interesting difference of opinion on the subject of simplicity versus complexity, but it seems to hang on what dimension of endeavor we’re looking from. From an engineering design perspective – especially wrt products for the consumer market – there’s evidence complexity (think shiny objects) is actually a better seller than simplicity.

It seems to me, however, that da Vinci was looking a little deeper than marketing prospects and was more interested in the aesthetics of design . . . all kinds of design.

So . . . I’m thinking of it in terms of this software tool I am now representing, called World Modeler, which is used to model the elements required to make important and quite likely expensive organizational decisions to better . What we (Quantellia, LLC and I) can do is transform highly complex decision models (involving numerous decision levers, external factors, intermediate effects, interconnections, and even qualitative assumptions) to graphically (and quite simply) show how they will play out over time given certain values. The goal is to render the complex simple, not to simplify that which is complex.

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What Did I Say I Did?

Biz Card

You Read it on the Internet, so it Must be True!

Anyone who knows me, knows I am quite the stickler for clarity and correctness in communication. I have proudly held myself out as a Senior Inspector in the U.S. Grammar Police, as evidenced by this card I created only halfway in jest. Actually, the card’s creation (I shared the process publicly) led to a couple of paid editing gigs. I’ve also been called a Grammar Nazi, which has caused me to momentarily flash a slightly sheepish smile, accompanied by a sparklingly demure blush.

Recently, I began a new engagement with a company I’ve wanted to work with for some time, Quantellia, LLC. As of the beginning of the year, I am what they call a referral partner. As such, I am contracted to Quantellia to sell their product, World Modeler™, and their services, which include training, workshops, etc. designed to help organizations make better decisions. In learning about my new venture, I have come across a few phrases that are similar, yet different enough to cause me to dig a little deeper in search of clarity as to their meaning. I want to very briefly share my understanding of the meaning of four separate phrases, each of which begins with the word “decision”.

At first, I thought one of the terms was kind of a catch-all; an umbrella term that encompassed the others. However, I no longer believe that to be the case, at least not fully. Keep in mind, all four of these phrases are relevant to what it is Quantellia and I are doing. At the same time, my understanding is quite likely imperfect and incomplete. As I gain a foothold in the discipline, and become more proficient, I have no doubt my definitions and my understanding will need refinement. 

Decision Science – at first I thought this term was one into which the others neatly folded. However, having done a bit of research, I can no longer say that’s the case. As I currently understand it, Decision Science concerns itself not so much with the process of making business decisions, but with the psychology of making any kind of decision. In other words, why do people make the decisions they do; what are the factors they take into consideration; how do they weigh them; how emotional are people in reaching decisions, etc.

Originally constituted in late 1968 as the American Institute for Decision Sciences, and later named the Decision Sciences Institute, this organization had its first annual meeting on October 30 – 31, 1969 in New Orleans. If interested, here’s a history of the organization written in July of 1989 by the then President, Bernard W. Taylor III. According to Wikipedia, the Institute is a “professional association of university professors, graduate students, and practitioners whose interest lies in the application of quantitative and qualitative research to the decision problems of individuals, organizations, and society. Many of the members of this academic organization are faculty members in business schools.”

It seems that Decision Science is a relatively new discipline. This conclusion is backed up by the history of its presence in some of the Universities and Colleges in the United States. For instance, Carnegie Mellon University’s Department of Social and Decision Sciences finds its roots in 1976, as part of what is now the Marianna Brown Dietrich College of Humanities and Social Sciences.” The Harvard Decision Science Laboratory opened its doors much more recently. According to their website, they’ve only been around since January of 2009. I couldn’t find the date George Washington University’s Business School’s Department of Decision Sciences opened its doors, but my hunch is it was sometime in the last decade, at most. The Columbia Business School’s Center for Decision Sciences, formerly part of the Institute for Social and Economic Research and Policy, appears to be fairly young as a separate discipline as well.

Decision Modeling – Although at best an inexact science, decision modeling can be a highly effective tool in helping an organization better predict the outcomes of its decisions. This is made more likely if the model is comprehensive, based on not merely data and analytics but also the knowledge of the people involved in the organization for which the decision is being made, and if the model is iterative and capable of incorporating newly discovered information and relationships. Furthermore, the structure of the model becomes more and more effective as it accurately models the complex relationships it seeks to help understand. World Modeler™ is capable, despite it’s seemingly simple interface, of modeling highly complex relationships. I’ll post more in the future about its capabilities, including embedding some excellent videos showing what it can do.

Decision Engineering – This is a term I don’t believe we are using any longer to explain what Quantellia does. Frankly, as someone who spent over two decades working with aerospace engineers and rocket scientists (quite literally, on the Space Shuttle Main Engine, Delta, and Atlas engine programs), I’m kind of partial to engineering. I can, however, understand how it may sound a bit intimidating or dweeby to people without my background, so I won’t dwell on it here.

Decision IntelligenceDecision Intelligence – This is the term Quantellia now uses to describe what it is we do. NB – The term is not “Decision Analytics”; there’s a reason for this. Perhaps it is best understood when one looks at a part of how decision modeling is accomplished. Part of the raw material available today for making decisions is what we call “big data”. There’s an awful lot of attention being paid to the field of predictive analytics, which uses big data as its raw material. We at Quantellia prefer the term predictive intelligence. This is because predictive analytics uses past performance (data) to project trends into the future. We like to think we take the concept a bit further.

While we believe analytics are useful and important, they lack the dimensions of human knowledge and understanding that can more completely predict how the past will play out in the future. A subtle distinction? Perhaps, but I find it a valuable one. Unless we’re talking about the future activity of a machine designed to perform a very limited set of instructions or actions, our activities involve human understanding, emotion, and interpretation. There are times when these attributes can dramatically change the course of an organizational effort, rendering previous decisions moot or, at best, only partially useful or correct.

By providing a method whereby human understanding, intuition, and wisdom can be incorporated into the decision model itself, we believe we can more intelligently predict the future. We are well aware there is no such thing as infallibility. However, we also know the more useful and actionable information and knowledge we have available to understand what has happened − and is likely to happen − the better our decisions will be.


 

Mild Disclaimer – I hope I didn’t rattle anyone’s cages too much with these definitions/explanations. They represent my current thinking and, being somewhat of a newbie to the science/craft of decision making as a discipline, my understanding is necessarily incomplete and in a state of flux. Nonetheless, this is a first attempt at explaining some of the concepts that are informing my work with Quantellia and World Modeler™. Consider it an ongoing process.

At the same time, I would like to make it clear that Quantellia has been doing this for approximately eight years and has a track record of helping organizations both large and small to make decisions and manage programs successfully. Dr. Lorien Pratt, co-founder and Chief Scientist, as well as her team, know their stuff and are the biggest part of my team. We are looking for people who have “wicked problems” they need to solve; people who are facing highly complex decisions involving lots of time and money, and for whom the wrong decision could be very costly. If you fit that description, or know of someone who does, you could do a lot worse than contact us for an initial discussion of your needs. We begin with the end in mind and believe we can help. Only by understanding what it is you face can we determine whether or not that’s possible.


Changing My Game

While I have written a little bit about one of the new endeavors I have set out to pursue (here and here), I haven’t really done much to explain what it is I’m doing with decision modeling and my work with Quantellia LLC. I am in the process of writing a post about some of the concepts I’ve been looking into and learning about, but it won’t be ready for a while, as I have more studying and research to do.

I do, however, have the ability to share some of the material I’m learning from, as Quantellia has produced a significant number of videos and recorded webinars. This one is the one I usually send to prospects. While it is the oldest, it’s also one of the shortest and still conveys the essence of what Quantellia, and it’s product World Modeler, can do for a business or organization facing complex decision-making.

So . . . I’m not sure if I actually announced it here on my blog, but as of the beginning of this year I have become a referral partner for Quantellia. In my opinion they have not only a superior product, but a superior mindset regarding how decisions are made. As a systems thinker I am keenly aware of the value in a long-range, strategic, informed approach to deciding how to proceed and to keeping track of what’s happening, always being prepared to take a different path if circumstances warrant it. I believe the people of Quantellia do exactly that and that World Modeler is a tool that makes it much easier to accomplish.

If you have an important, complex decision to make you need to understand how decision modeling works. As Dr. Pratt says on the video, you can model many decisions using paper and pencil, but you can’t do a good job of it without understanding how to “engineer” the decision using more than just analytics and predictions based on them. You need to use “Decision Intelligence”. Quantellia can help, which means so can I. Please let me know if you’re interested in discussing your specific needs. I’d be happy to set up a teleconference to see if we can help. Thanks.

PS – I’m going to share more of these videos here, but you can see them all for  yourself at Quantellia’s YouTube channel, located here.


Defining Knowledge Management

KM Wordle

KM Wordle (courtesy of Information Architected)

As long as I can remember, I have always looked for smarter and better ways to do things. Some people have described this propensity as lazy, but I don’t think working smart is really laziness. I like to think of it as a form of conservation. Of my energy! Additionally, working smart means you can be more productive; accomplish more in the same amount of time. No one should have to defend spending energy on making things easier and more efficient and effective.

I say this because this proclivity ultimately led me to the concept of Knowledge Management (KM) in the mid-90s and changed the trajectory of my career (late as it may have been) rather dramatically. Actually, KM had been around for as long as humans had the need to ensure hard-won lessons were passed down from generation to generation. However, as I was beginning to encounter it back then, it was being transformed by the proliferation of the personal computer and the expansion of the Internet and the capabilities it provided. These developments fairly exploded with the advent of Web 2.0 capabilities; the interactive web, and this ultimately led me to what has been called Enterprise 2.0 (now being referred to as Social Business).

Beginning around 1996 I began working with a small group of KM people at Boeing Propulsion and Power, a division of The Boeing Company, to apply these concepts to our various rocket engine programs. Shortly thereafter, I was appointed as the KM Lead for the Space Shuttle Main Engine Team, the largest of our then current contracts. From the very beginning it proved difficult to succinctly explain what Knowledge Management was. Although human beings have been sharing what they learn since time immemorial (it’s part of what makes us so unique), it proved exceedingly difficult to “define” KM. That is to say, it didn’t easily allow one to create a 30-second elevator speech.

I have therefore decided to offer a collection of definitions and explanations, culled from the best minds available on the subject, as discovered by me – through my research, experience, and education. I’m going to publish it as an ongoing project with the intention of adding to it, either by my own hand or through the input of those who find their way here. As it turns out, this is a somewhat convoluted process since so many have tried to define KM for over a decade. In doing just a little research I’ve come across lots of attempts to do the same thing I’m doing here, with varying degrees of success. Even my old friend, Luis Suarez, has an important collection. Unfortunately, one the main collections he refers to is no longer in existence (at least his link is broken). ‘Tis a bother.

Truth to tell, few of these are offered as definitive (which is kind of ironic, don’t you think?) by practitioners. I believe that’s because the practice is at once pervasive and deeply contextual. It’s just plain hard to pin down to a single or even a single set of practices or behaviors, or processes, etc.

I also want to include the sage words of Frank Miller, taken from a paper – I = 0 (Information has no intrinsic meaning) – he published in October of 2002. You really should read the paper if you want to understand his premise, which I think is really valuable if you want to get a grasp of what knowledge sharing (as opposed to knowledge management) is about:

This is a vexed issue. KM is, sadly, deeply embedded in most modern literature connected with the productivity of intangible assets. Yet this paper tries to make clear that when subjected to critical analysis, KM is an untenable notion. Knowledge (i.e., what people know) simply cannot be captured or managed, and hence the term Knowledge Management is inappropriate. Worse still, the language of KM suggests that knowledge is a commodity capable also of being processed, delivered, transmitted etc when it is not. Whilst knowledge sharing is an acceptable concept, the notion of knowledge management is, at best, dubious!

Please feel free to offer your own definitions, take issue with anything I’ve posted, or point me to others who you think deserve to be part of the conversation and I’ll do my best to edit it in to the body here. Thanks.

Definitions

Knowledge Management  is a field that takes concepts of Library Science & Pedagogy and, utilizing the latest trends in Information Technology, seeks to facilitate the capture, transfer, and useful application of the collective knowledge of an organization or group. – Rick Ladd

The purpose of knowledge management is to provide support for improved decision making and innovation throughout the organization. This is achieved through the effective management of human intuition and experience augmented by the provision of information, processes and technology together with training and mentoring programmes.

The following guiding principles will be applied 

  • All projects will be clearly linked to operational and strategic goals
  • As far as possible the approach adopted will be to stimulate local activity rather than impose central solutions
  • Co-ordination and distribution of learning will focus on allowing adaptation of good practice to the local context
  • Management of the KM function will be based on a small centralized core, with a wider distributed network David Snowden

Knowledge Management is the discipline to enable individuals, teams, organizations and communities, more collectively and systematically capture, store, share and apply their knowledge, to achieve their objectives. – knowledge-management-online.com

Knowledge management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizations as processes or practices.Wikipedia

Knowledge management refers to strategies and structures for maximizing the return on intellectual and information resources. KM depends on both cultural and technological processes of creation, collection, sharing, recombination and reuse. The goal is to create new value by improving the efficiency and effectiveness of individual and collaborative knowledge work while increasing innovation and sharpening decision-making. – Steve Barth


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