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.
I have just returned from a terrific and all too brief visit to Wellington, New Zealand, where I presented the Analyst First (“A1″) vision to NZ’s intelligence community’s professional body- the New Zealand Institute of Intelligence Professionals (NZIIP) – at their annual conference. A big thanks once again to the organisers for inviting me, and giving me the opportunity to meet such a dynamic, interesting and intelligent group of people.
The presentation was too long for the time allowed,as it tried to capture the main aspects of the set of ideas comprising A1. The response was positive, with further NZ related A1 developments to be announced shortly.
It also included a picture that captures the whole idea of A1 in the ironic “Motivational Posters” style. You can find the picture on the second page.
This was only the first of two presentations that I gave at the conference, the second being delivered to an audience that included the New Zealand Prime Minister John Key. Not the kind of thing that I am used to by any means. This second presentation did not come with slides, but an extemporaneous opening of the NZIIP Forecasting Competition. Unfortunately this competition is closed to NZIIP members only. All are however welcome to participate in the Australian Institute of Professional Intelligence Officers (AIPIO) Collective Forecasting Competition, which is currently running.
I look forward to seeing some of the NZIIP people again at the AIPIO Annual Conference this week in Sydney.
For those in Sydney or able to get there in early July, I will be presenting on the results, findings and workings of the AIPIO Collective Forecasting Competition at the Sydney Users of R Forum On Tue July 10.
The AIPIO is of course the Australian Institute of Professional Intelligence Officers. They have hosted a number of A1 related presentations in the past, and are a natural friend of A1, given our principle of The Intelligence Model of Analytics.
Collective forecasting and related methods such as Prediction Markets, working as they do on the aggregated tacit data of human beings, are truly “Analyst First” analytics techniques, with human beings adopting the traditional roles of algorithms and electronic data. Collective Forecating is also the only tool consistently appropriate for the most important decisions made in businesses. These tend to be one-off, data poor and often based largely on human-held tacit knowledge.
Big claims? Come along and argue if you happen to be around.
The AIPIO Collective Forecasting Competiton also begins its new round.
All are invited to participate by registering and entering predictions, or by suggesting additional events to forecast.
The months of July and August will involve a number of other Analyst First related events, including:
The long anticipated launch of regular public Analyst First events in Canberra, with thanks to BAE Systems for providing the venue, as they kindly do for monthly A1 ACT chapter Leadership Group meetings.
A presentation of the Analyst First vision in Wellington, New Zealand at the annual conference of the New Zealand Institute of Intelligence Professionals (NZIIP)
Regular Analyst First Leadership Group meetings in Melbourne, Canberra and Sydney. Those interested in being involved in chapter leadership groups please contact me or the other Chaoter heads: Graham Williams in Canberra, Yuval Marom and Tony Laing in Melbourne, and Kevin Gray in Tokyo.
Also forthcoming are a number of expansions of the website, and the creation of new content including a charter of A1 principles, and a list of subscribing A1 practitioners. A number of other initiatives in the works too rhanks to good work by Canberra Chapter Leadership Group.
A1 is a proud supporter of the AIPIO Collective Forecasting Competition, hosted on Presciient’s new collective forecasting platform System II.
A beginner’s guide may be found at the top of the page.
Collective forecasting and related methods such as prediction markets represent the area of analytics that we call Tacit Data Mining, and allow the extraction, deployment and analysis of the most vital data in the organisation, which lives in people’s heads. It also provides the ultimate data fusion platform, fusing all available data through human filters to provide powerful strategic decision support.
Collective forecasting allows accurate forecasting of future events, and also can condition those events on possible actions, thus providing a powerful decision support. It identifies the consistently most effective forecasters, acting as a filter for the most insightful and prescient members of staff or the public.
It has application in any strategic decision support domain.
The competition at hand has 3 expiry dates for predicted events: in April, July and October, each has prizes for 1 month ahead, 1 week ahead and 1 day ahead. The July and October expiries also have 3 months ahead prizes, and a six month ahead prize for the October expiry.
The one-month ahead April expiry deadline is tomorrow, so don’t delay, register and put in your predictions.
Welcome to A1′s very first podcast.
This is a relatively quick (less than 30 mins) overview of what Analyst First is all about, and why Human Infrastructure matters so much.
This is a recording of the presentation I gave to the Intelligence 2011 conference, which is the annual conference of the Australian Institute of Professional Intelligence Officers (AIPIO), as part of their very apt “The Analyst vs the IT” stream.
I presented my talk on A1 and Human Infrastructure yesterday, and will upload a recording of the presentation along with slides shortly.
The talk was a variant of recent “Human Infrastructure” presentations, but in this case focused on intelligence (as in James Bond, though a bit of the Einstein kind does not hurt).
The audience was larger than expected, with the usual mix of folks from law enforcement, military, other government agencies, and private sector folk primarily from software and consulting.
The message of putting people first resonates strongly with a profession that is challenged by adaptive, well-resourced adversaries, and in need of equally adaptive, human-driven technological support. There were questions regarding training and where to start, and an “amen” regarding the power of commodity tools, specifically MS Excel.
There are two other Analytics related presentations at the conference, one by Cai Kjaer of Optimice, and one by Graham Durrant-Law of Hyperedge. Both deal with social network Analytics, from very different angles. As it happened Cai’s presentation ran at the same time as mine. To remedy this we met at the bar afterwards, and a small crowd gathered to watch us run through both presentations.
Cai’s presentation dealt with applying social network analysis to create a more efficient, effective and innovative intelligence function by mapping communication channels and relationships, and identifying key social connectors and contributors. The standout slide from his presentation was a map showing what percentage of relationships is removed as staff leave. The results are indeed devastating. I hope that Cai will make his slides available online.
As a bonus Graham ran through a sneak preview of his, which he will present later today. His presentation dealt with mapping the publication relationships of Iranian nuclear scientists. A bit like Cai’s, but more from an adversarial targeting perspective.
All good fun, many interesting people and some great war stories. My slides and talk to be uploaded soon.
About usAnalyst 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.
Tags in a CloudAIPIO analyst first Analyst First Chapters analytics analytics is not IT arms race environments big data business analytics business intelligence cargo cults collective forecasting commodity and open source tools complexity data decision automation decision support educated buyer EMC-greenplum forecasting HBR holy trinity human infrastructure incentives intelligence model of analytics investing in data lean startup literacy management culture MBAnalytics operational analytics organisational-political considerations Philip Russom Philip Tetlock prediction markets presales R Robin Hanson Strategic Analytics tacit data TDWI Tom Davenport uncertainty uneducated buyer vendors why analyst first