While, as I said in a comment above, I have not seen any Delphi tools in Sharepoint or similar collaboration technology, that does not mean they don’t exist or could not be readily created.

Interesting mashup.

If we are neither, are we out of options? Maybe not.

We could try to prove the ROI from our sparse array of information. But as I mentioned in my posting On the true nature of business intelligence that requires a level of sophistication that is difficult, read expensive, to provide.

Ironically it is well-known to be very difficult to prove the ROI of just the kinds of forecasting tools we would need to demonstrate the ROI of our best ideas – largely because, as you said, human brains are fantastic pattern recognition engines, and it is hard to beat their value proposition when faced with a sparse array of data.

So here is a product idea. It may already exist, but I have not seen a Delphi forecasting capability in the new generation of collaboration tools.

Remember that a Delphi forecast is a formal workflow-based approach designed to help a group of experts arrive at a common forecast. It avoids the problems of single expert forecasts – bias, real or perceived, and a lack of authority with the check-signer – and the problems of interpersonal group forecasts – bad forecasts resulting from group dynamics: dominance, persuasiveness, sex.

Essentially, a Delphi forecast consists of a series of questionaire-response-refinement cycles, where a questionaire is distributed to the group, and the answers are collected and used as inputs to improve and focus the next one. The cycle continues until the result has stabilized.

Back before Movie Gallery came in and bankrupted them, Hollywood Entertainment used a modified Delphi forecast to predict the performance of new videos that had done over 10 million box office. Statistical forecasting methods and tools based on historical titles with similar attributes were used (including some I architected or helped architect while working there as a contractor then an FTE) to ’seed’ the forecast. But the final process was a sort of Delphi forecast where a standing panel of experts weighed in in a voting cycle.

It would be interesting to create and position a Delphi collaboration technology solution, and then to see what weight an impaneled Delphi team whose forecasts where formally faciliated by the collaboration technology might have where a lone pioneer’s voice might fail.

It turns out that at the real Delphi, hallucinogenic fumes were seeping out of the ground. The prognostications of the Oracle were just the stoned ramblings of someone with a good buzz on. If we knew the True History of Steve and The Woz, we might find a modern variation on a classic theme.

You were motivated to reduce costs–that and a vague dissatisfaction with the quality of the popped corn and a hope that you might do no worse and possibly better at a reduced cost.

You were pleased to find that changing vendors and reducing cost did not result in a sacrifice of quality. Just the opposite once you changed your process; the vintage popping process was slightly more labor-intensive (ergo costly) but actually improved customer experience to an undeniable degree.

You were so pleased with the results your brand loyalty was influenced and you were moved to publicize the fact.

Arguably, you are not a typical customer. You did not require education in the benefits of the switch in vendors or a more laborious process. You recognized the lost qualities because you had experienced them in that past and were prepared for your Proustian reawakening. You even knew the lost art of oil-popped corn, including the test kernels.

So the question is, how atypical are you? Is there a market opportunity for a vendor to tap the pent-up demand for oil-popped corn? Is that opportunity sufficiently large for the vendor to risk capital reaching your demographic? Do they have an affordable plan for marketing to your demographic–assuming they can define it and quantify it? It may be that only a specialty market exists for niche players to explore first–you are, after all, admittedly, very price sensitive.

It may be, therefore, that exploration of higher quality designs, processes, products and services will continue to be explored by risk-takers willing to roll the market dice, while bigger players observe and wait until the market declares itself in favor. Some large vendors then pioneer, while others prefer the conservative third-wave settler position. Your risks and opportunities will depend in no small measure upon whether you choose to join company with Lewis and Clark, Leland Stanford or simply pay to ride one of the latter’s trains across territory explored by the former.

Nothing is more frustrating than being an explorer at heart riding a train and trying to convince the conductor to change his schedule because you know for certain there is danger ahead if the present routine is continued. At best you evoke laughter; do it too many times and you get thrown off the train.

As my last three employers have said: “You can’t possibly know that.” Meaning because I could not quantify the dangers and the benefits of the alternatives I proposed, they dismissed first my warnings and then me. Of course what I predicted came to pass–it was never in doubt. One sees patterns in sparse matrices. But companies as they grow become extraverted, ergo reactive. You’ll get a mandate (meaning budget) for quality the day the lack of it shows up clearly in successive quarterly statements. Unless you believe you are correct and go find or start a Corps of Exploration. And you know that they sometimes suffer high attrition and don’t always reach the coast—let alone find their way back to tell about it.