- 16 May 2019
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Contracts and Procurement SIG
Data Analytics in procurement: new opportunity or pandora's box of risk? webinar
Data analytics, machine learning, and statistical analysis are increasing our ability to make reliable predictions. Automation and AI (artificial intelligence) can reduce the drudgery of analysing and evaluating masses of data. But they can also introduce hidden biases and reduce transparency. How does this apply to procurement?
As a project manager accountable for selecting suppliers, imagine a world where clients share data on supplier performance, on their adherence to schedule and cost, compensation events and volume of costed change requests. This data enables insights into how the supplier relationship is likely to evolve, and the likelihood of project success.
Data analytics is used to predict who is going to compete for a contract and whether there will be an outright front runner. By changing the evaluation rules, you can level the playing field and encourage greater competition.
Then, as a bidder, imagine a world where an organisation can reliably predict their win probability before they bid for work. A capability that scrapes the internet for opportunities; identifies competitors and their strengths and weaknesses; and ranks the opportunities based upon the greatest probability of win … it begins to reshape how organisations bid for work.
It sounds like something from the Minority Report, but these capabilities are with us today.
BUT is this approach defensible? It is fraught with legal and ethical risks which may, in themselves, cause significant delay to your project as well as reputational damage to your organisation. Savvy bidders will attempt to game the system defeating the object of identifying the best value provider. It may ultimately lead to over-reliance on a few or one supplier. But it could also save organisations a lot of unnecessary expense and focus on those bids they know they have a good chance of winning.
Within this talk, Martin will walk us through the art of the possible, with its potential to transform procurement and bid management, and also explore the wide range of issues that must be very carefully managed, before you choose to implement it … or should we say, if you choose to implement it.
Objectives / What you will get out of it
- An appreciation of the art of the possible and how AI may shape the future of procurement, for bidders and clients alike.
- An overview of the risks and issues and how they may affect potential roll out.
- Sufficient understanding to enable you to develop a strategy on how to engage with it or consciously decide not to.
- An appreciation of how it may impact your career.
a. Introduction to AI and Project Data Analytics
b. Potential use cases
c. Sources of data
d. Examples of how this could be applied today
- The opportunity
a. How we may be able to deploy it
b. Potential roadmaps
- The challenges and risks including:
a. Collusion and gaming the system
b. Creating black lists
c. Unfairly discriminating against suppliers with recent problem projects
d. Progressive over-reliance on a few or one supplier
e. Using legacy data to shape procurement decisions
f. The ‘computer says …’ syndrome : black box algorithms can lack transparency
- Impact on the career of procurement professionals
Martin Paver is the founder of the London and Bristol Project Data Analytics Meetups. A community of over 2,200 people with an interest in leveraging the exhaust plume of data that is emitted from projects. He is a Fellow of APM, Registered Project Professional and Chartered Engineer. He is the CEO and Founder of Projecting Success, a consultancy that is pushing new boundaries in advanced project data analytics.
Dr Jon Broome is the managing consultant of leading edge projects consulting ltd, Chair of the Contracts & Procurement SIG and a trustee director of APM. He also runs his own investment portfolio, investing directly in individual companies.
APM Body of Knowledge 6th edition reference