ITx 2019 Rutherford Programme

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DRAFT: The ITx Rutherford 2019 Programme may change without notice

Valuing the Invaluable

Friday 2:50pm - 3:20pm, IT Professionals NZ (Wairau Room)

Often the most difficult part of selecting among potential strategies or a portfolio of potential projects is putting a value on their outcomes.

Enough hard information is rarely available, so judgments must be made under uncertainty.

There are well-proven principles that can be combined to make this process rational, transparent and repeatable at subsequent decision points.

They are used less often because they work best when combined but come from disparate disciplines: project management, social science, and statistics.

Together they can aggregate numeric and non-numeric data with the wisdom of your corporate crowd to create information that is reliable and readily understood.

This paper brings those disciplines together into a usable process underpinned by research.

Using this model you can for the first time compare opportunities on a level playing field with risk mitigation.

Speaker

Graham Harris

AcuteIP

Graham has been a project manager, led a team of project managers and operated a Project Management Office for an international company.

More recently he has been on the sponsor side of the table, managing a spend of up to $50m a year against a demand of more than double that.

Organisational culture often expects project proposers to express certainty around the costs and benefits of proposed actions, but what they get are just estimates with no indication how wide is the margin of error.

For his Masters research thesis, Graham combined techniques from social science to derive a methodology to estimate repeatably the value of a future intangible, and communicate the degree of certainty in that estimate.

In later practice, he has integrated more social science methods to counter several types of bias, and statistical methods to aggregate whatever facts are available with many individuals' calibrated estimates (wisdom of crowds) into a simple, reliable, transparent model of the proposal showing the aggregated uncertainties in both costs and benefits.