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Matt Wilkins
Partner, CMInstD
Matt Wilkins is a seasoned professional specializing in leveraging data, advanced analytics, and strategic insights to drive organizational success.
His educational background includes a Postgraduate Degree in Tourism Development and a BCom in Marketing & Management from the University of Otago, as well as certifications from the Institute of Directors in New Zealand and executive education from Harvard University.
Matt has held key roles in various organizations, including Director and Chair positions at Datamine Limited, where he also served as a Partner and Senior Consultant.
His diverse experience extends to roles such as Business Lead for Data Driven Services at New Zealand Post, Consultant for Data Services & Tools at PacMicro, and Account Director for Activities & Adventure Tourism at Tourism New Zealand - Qualmark.
Additionally, he has contributed as a Board Member for the North Shore United Football Association and previously served as a Director at Faraday Catering Limited.
Matt's expertise lies in strategic decision-making, data-driven services, and professional services firms, making him a valuable asset at the intersection of analytics and business strategy.
Highlights
I know we’ve all probably come across Tim Worstall before. He was the guy writing for Forbes back in 2013 who claimed that Excel was the most dangerous software on the planet – “more dangerous than rogue code running a nuclear power plant” were his exact words.
I guess he meant useful, but often dangerous.
And I think he’s still right about this because we regularly come across organisations running critical processes and making decisions out of atrophying and frankenstein-esque excel spreadsheets.
And when I say critical, its often the economic engine of a business like pricing, resource allocation and buying decisions. The decisions that help businesses make money sit as formula and macros in an Excel spreadsheet.
So when we’re asked “where do we start applying data science?”, you could probably do worse that targeting these points of inefficiency and failure and building more resilient applications, as you reengineer these processes with data science elements to optimise the decisions you're trying to make.
They often serve as great catalyst projects that can build momentum and confidence in a data science function or affirm investments in digital transformation. We explore this in a little more detail and explain why you shouldn’t always rely on a “Kevin”….
