We've been looking at recent models for measuring risk and opportunity cost. This is an age where it's the cost of NOT innovating that is crippling so many NZ organisations. Measuring ROI is pretty straightforward, especially when you've got some history to build on. Customer lifetime value (CLV) and Value per sale (VPS) can add to the picture as well. In fact there's a verysimple formula they teach in business school that gets us thinking about opportunity in terms of trade-offs. However, this is no longer enough. We need to factor in costs for failing to innovate. Remember, CERN came very close to knocking back Tim Berners-Lee on his "WorldWideWeb" proposal. If this is a problem you are trying to work through, there's an article you might find useful here. Risk mitigation is something we know - we'd be happy to help if you want to talk things through.
What are the most urgent threats facing large corporations who depend on cloud services? What can we do now to mitigate these risks? These questions were put to Igniter recently by an industry leader in New Zealand. There is nothing rhetorical about them! Few industries are secure in the face of international competitors with global platforms . Rather than turning inwards for solutions (always a mistake!) Igniter brought together a think tank with enough experience and the guts to face these questions squarely. Together, we came up with a strategic response that we believe will protect our client for the next ten years, if not longer. If you'd like to know more about the Igniter approach, join us at LinkedIn.
We've formed a research partnership with the Wellington City Library to collect and analyse the latest global research on artificial intelligence. Like us, you're probably sick of all those frothy proclamations from futurists and the foreboding horoscopes of consultants. Buzzwords & buggery bollocks! In our view, the real journey is one that takes us from data to information and then insight. To be more precise, we're concentrating on that all-important space where the rubber hits the road: development-level applications. Would you like to be kept in the loop as we learn to understand artificial intelligence (and vice versa)? Join us on LinkedIn and we'll take it from there.
When a client asked us recently to explore the potential for a machine-learning platform, we took the tried-&-true Igniter approach: after a toe-in-the-water investigation we planned some prototyping and tests. The first of three steps involved a bunch of no-holds-barred experimentation. How might such a system develop and apply its own learning, autonomously? To cut a long story short, the results pleased and surprised us all. They also allowed us to address two major questions in advance:
What system(s) would the AI operate in during its initial prototyping, and;
How would the learning and prediction specifications act?
Once the client's risk had been mitigated, we knew how to proceed. More importantly, by the time major investment was needed we were sure of success.