Collective Forecasting : Because Sometimes You Don’t Even Have Data
Electronic data that is. The most important decisions aren’t data-friendly. But they are the ones worth the most dollars, nerves, careers and lives.
“Do we want to mail an offer to this particular person” is a far less important question than “Do we want to acquire this company”. The former is a decision supporting precise, very low level action, for which data exists, because essentially the same action has been carried out many times, and will be again. But how do we apply analytics directly to the second question ?
This is where collective forecasting can help, by applying analytics rigour to get the benefit of the most important data in an organisation, the tacit data in the heads of its people.
Collective forecasting is a truly “Analyst First” technique: the analyst comes before software, and even before (electronic) data. Indeed, software is helpful, but not essential, and data may be scattered, in short supply orabsent entirely.
Here is a presentation given last week at the Australian Institute of Professional Intelligence Officers (AIPIO) annual conference, explaining the benefits of the collective forecasting approach to organisational strategic decision making. These include a powerful KPI for strategic forecasting and decision making, and flow-on effects of a truly meritocratic, depoliticised decision making culture, where Highly Paid People’s Opinions (HiPPOs) do not carry the same weight as a good predictive track record.
Improvement is gained through the use of the group, or collective forecast, which fuses the tacit knowledge of relevant knowledge holders to create a more reliable decision making mechanism.
The presentation also presents results of the first round of AIPIO’s collective forecasting competition, where the group forecast performed very well, as expected.
Readers are invited in the second round of the competition, which is running currently.
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About us
Analyst First is a new approach to analytics, where tools take a far less important place than the people who perform, manage, request and envision analytics, while analytics is seen as a non-repetitive, exploratory and creative process where the outcome is not known at the start, and only a fraction of efforts are expected to result in success. This is in contrast with a common perception of analytics as IT and process.Authors
- Eugene Dubossarsky (43)
- Greg Taylor (4)
- John Lowry (1)
- Richard Fraccaro (1)
- Stephen Samild (87)
- Tapir (1)
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