World Modeler adds a Systems approach to Project Management
In my last post I took a stab at defining, and explaining, the concept of Decision Intelligence. I’m willing to bet you’re going to be hearing a lot about it in the not-too-distant future. So you don’t have to click back and forth, I’ll copy over what I wrote about it in that post:
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.
Now, having had some time to think about it – it’s been over a month since that post -and having discussed it a bit with Quentellia’s Chief Scientist, Dr. Lorien Pratt (@LorienPratt), I’d like to add a little something to both the definition and the description of what World Modeler has to offer. Keep in mind, as with many things, perhaps even more so with something truly emergent and reasonably new to my experience, both my understanding and my ability to explain are evolving; developing structure and nuance as I learn more theory and encounter more examples of real-world situations.
I consider systems thinking, or the ability to see systems — and systems of systems — as the most effective way to understand what is happening within any one or more of those systems, as well as have a chance at affecting the outcomes of the ones designed to produce value and realize valuable results or consequences of their workings. The more elements of a system that can be modeled, the more likely you will be able to understand downstream effects of your decisions, and the more likely you are to see the unintended consequences of actions before you take them.
Here’s where Quantellia’s World Modeler™ excels as a decision modeling — and making — tool and enabler. Consider Predictive Analytics, the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. PA usually returns fairly simple, pairwise relationships, e.g. these customers in this demographic, with this amount of revenue, etc. are likely/not likely to churn or devoting a certain amount of energy to customer retention is likely to affect/not affect customer churn.
World Modeler, on the other hand, allows you to create a highly complex systems model. This means you can look at numerous elements and their interrelationships to see how they work together, e.g. customer characteristics, customer retention efforts, likelihood to churn, total customers, revenues, and even business rules that might have to be taken into consideration if certain levels of activity are reached. Furthermore, when you don’t have data for one or more of these elements, you can use human expertise, the tacit knowledge of your employees or the group to fill in the gaps. When you have real data, if you later are able to gather it, you can then plug it into the model and continue going.
One more thing. World Model is a highly flexible, iterative navigation mechanism. It allows you to predict without complete or perfect knowledge, then pivot and change the model as new and/or different knowledge, information, and data are gathered or encountered. You can do this repeatedly over the course of months or years, whatever’s necessary to help you make the best decisions for achieving your desired outcomes. So success doesn’t depend on long-term predictions. Rather, it depends on navigation and alignment between the organizations systems, processes, and the humans that employ them.
Now . . . having learned all that, aren’t you interested in seeing how this tool works? You can get a free evaluation copy and all you’re giving up is a little contact information. There’s no obligation. Click on this the link to download a fully-functional two-week evaluation copy of World Modeler. Give her a Whirl(d)!
Systems Savvy 
Tweaking Facebook
Use the Like, Luke.
I am — at least, I was — a Knowledge Management professional. It’s what I did for over a decade at Rocketdyne, starting when it was a business unit of The Boeing Company, up through my retirement from Pratt & Whitney Rocketdyne, a division of United Technologies. Pratt & Whitney paid for me to earn a Masters Degree in KM online from CSUN’s Tseng College. It’s such an exclusive degree they don’t offer it anymore. 🙂
I mention this because it affects how I share information, especially here on my blog. One of the tenets we tried to drill into people’s heads, and follow ourselves, was to avoid reinventing the wheel. That is, make it a habit to reuse information and knowledge that’s already been won at some cost to one or more individuals and the organization in which it was produced. This means, among other things, I am not interested in rewriting what others have written, while adding my own twist to it. This doesn’t apply when how I perceive an issue is substantially different than others, but it does when I’m sharing things I mostly agree with.
Yesterday and today brought me two great, and related, examples of things that need sharing and for which there’s little for me to do than announce them. The first I will actually place second, below, as it’s the subject of the second, which is a post by Dennis Howlett, which he published today in diginomica. What Dennis discusses is a Google Hangout Robert Scoble conducted, wherein he described what he has learned in thousands of hours of tweaking Facebook’s algorithms — primarily through his educated use of lists, likes, shares, etc.
Both Dennis and Robert are still far more embedded in the business world than I am and, rather than attempt an explanation through my eyes, I want to leave it to both of them to help you out. If you are using Facebook for your business or profession, or even if you just want to have a much better experience when using Facebook personally, I suggest reading the post and watching the video, which I am also including here. As Dennis points out, Robert is very generous with sharing his knowledge, something this KM pro really admires. You really should take advantage of it.
http://www.youtube.com/watch?v=Wq4IzbVZr3o
If you care to share:
Leave a comment | tags: algorithm, Business, comment, diginomica, Facebook, Google, Google Hangout, Howlett, KM, Knowledge Management, Like, lists, Personal, Scobleizer, share, sharing | posted in Business, Info Tech, Knowledge Management, Marketing/Branding, Professional, Social Media, Technology