Are Collective Intelligence Solutions being Oversold?

Posted on November 29th, 2008 by mat

A reply to Chris Masse on Midas Oracle

Chris,

Management struggles to understand and plan for the future. When forecasts are inaccurate, corporations incur huge costs due to inventory write-offs, stock-outs, misallocated resources or cost of capital. Collective intelligence delivers objective, accurate forecasts in real time, thus saving many millions of dollars for our corporate clients. The solution is not being oversold, to the contrary, the potential vastly exceeds current awareness and adoption.

“If foresight is not the whole part of management, at least it is an essential part of it” (Henri Fayol, 1916).

In my 10 years experience as a management accountant and corporate planner, I have witnessed multiple forecasts suffer from inaccuracy due to uncertainty and biases. Whether forecasting a launch date, sales volume or cost of development, it is the systematic biases due to incentive systems, politics and common cognitive errors that contribute more to inaccuracy than the uncertainty. The problem stems from the fact that the owner of a forecast is normally the owner of the business unit / sales team / project, and budgets and bonuses are based on forecasts. This necessitates game playing and politics and makes the development of an objective, accurate forecast near impossible.

Collective intelligence can overcome these problems by incentivising a diverse crowd of knowledgeable employees to share their insight, balancing the resulting estimates, and rewarding accuracy and timeliness.

However, we are at an early stage in the development of this opportunity. There is still work ahead of us to develop the ideal mechanism to combine simplicy of UI with richness of information gathering. In addition, we need to further develop the way collective intelligence interfaces with traditional corporate structures, processes and systems. These are Xpree’s challenges……stay tuned.

Mat
CEO, Xpree

John • January 29th, 2009 at 2:41 pm

I agree Mat . . . just came across your site. Very interesting.

There are numerous applications from half past human – predictive linguistics to FICA for creditworthiness which have attempted to cull current information to predict future events.

I was involved with the Cornell Theory Center while at SGI to create, in part, predictive models for Financial Markets.

Within the scope of what you are trying to achieve with Xpree, I believe you are in an interesting space. For the vast majority of companies, the typical planning process is an iterative top-down, bottom-up exercise which tends to have the following characteristics:

Ã¢â‚¬Â¢Narrow constituency (with, as you stated biases)
Ã¢â‚¬Â¢Internal focus (both at the macro and micro level)
Ã¢â‚¬Â¢limited (or non existent) consideration of external factors

The result of the process is then used in round table exercises to determine forward-looking business and, ultimately, financial projections.

Complexity theory suggests that models and patterns (as described above) to which we have grown accustomed are becoming significantly less relevant. In its place, and accelerating in importance, is the concept of viewing reality as a set of dynamic systems. It is within these systems that the abstract phenomena of origination, emergence, evolution and seemingly random flow appear.

For businesses to survive and thrive, it is incumbent on leaders to recognize the patterns of emerging change.

Taken from this perspective, I believe business leaders will be increasingly tasked to sense and recognize emerging and evolving patterns and to position their company to take maximum advantage of (or minimize the impact of) these forces in order to maintain continuity and viability.

The only way to do this is to change the paradigm, and correspondingly, the models. Good luck in your effort to achieve this.

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