Everything You Always Wanted to Know About Your Spend Data – Webinar on November 28th

In less than two weeks’ time you can enjoy our webinar with leading spend analytics and artificial  intelligence expert Paddy Lawton. The title is Everything You Always Wanted to Know About Your Spend Data …  (But Were Afraid to Ask) 

So, do you nod your head knowledgeably when people talk about AI and machine learning?  But do you really understand it?  I’m not sure I do - but Paddy does. As the founder of analytics firm Spend 360, which was acquired by spend management software giants Coupa last Christmas, he has been immersed in the AI and machine learning world for years.

But this won’t be a theoretical discussion. We’re going to talk about our new Spend Matters briefing paper, also wittily titled Everything You Always Wanted to Know About Your Spend Data (But Were Afraid to Ask).  That looks at six areas where spend analytics can currently help organisations get more value out of their third-party spend, and where further advances in technology are likely to bring even more capability.

The webinar will include me throwing questions at Paddy, and we hope delegates will add their own questions into the mix. So please register for the webinar here – then even if you can’t make it on the day, you will get a link to listen to it later at your leisure. In addition, that briefing paper will be published VERY soon (watch this space), but here’s a short excerpt just to whet your appetite.

 

Everything You Always Wanted to Know About Your Spend Data …  (But Were Afraid to Ask)  (a short extract)

Can I get actionable information in real-time?

Historically, most spend analytics has been resolutely backward-looking. (Our colleague at Spend Matters US, Pierre Mitchell, calls it “spent analysis” – the use of the past tense being deliberate as well as witty).

Through traditional spend analytics, we examine what the organisation has already spent in the past and any comparisons relate to events and purchases that have already happened. Clearly, this has value, as already discussed, but also means that in a sense it is too late to do anything about what has already occurred. But this is changing as technology moves to acting in real time, and then there is additional potential to move further on and look into the future, with predictive analytics …

The next step takes analytics into looking forward and helping the organisation to predict requirements, costs, or even identify future risks and required actions to maximise value. We may see AI looking for opportunities amongst the spend data, relating that to the organisation’s future plans perhaps to highlight areas where a different approach might bring value.

Despite some of the hype, AI and machine learning cannot do everything an experienced procurement executive does today. We suspect that opportunity assessment for instance will still require human judgement for many years to come, to prioritise potential actions if nothing else, but it is likely that analytics will certainly move into predictive mode rather than having a purely backward-facing role.

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