SWTCH by Pigment
Three days of predictions, insights, and advice from leaders in finance, sales, HR, supply chain and more
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SWTCH by Pigment
Three days of predictions, insights, and advice from leaders in finance, sales, HR, supply chain and more
Register now here
By Timo Wienefoet, Principal at Kainos
These are exciting times for finance and Prediction Machines are a part of it. The promise of technology for a sneak peek into the future gives finance a crystal ball on where to steer resources today for an optimal utilization tomorrow. Can the Arabic proverb “he who knows the future lies even if he is proven correct” be overcome?
There is progress calculating the likely tomorrow out of existing data. Weather forecasting reliability „a week ahead“ today is as accurate as the „next day forecast“ 30 years ago (see Wikipedia). For businesses, forecasting accuracy in the supply chain is the prime example of related cost drivers and enhanced customer experience. Applying these promises to the fate of corporate planning, budgeting and forecasting requires to analyze
a. the confidence intervals associated to the timeframe of the process (less confidence the larger the timeframe) and
b. the costs of introducing new prediction machine technology.
As of today, the question mark behind the efficacy of the investment stays steady while methods to improve the quality of looking ahead do exist for FP&A. Three examples and their interaction once the investment seems favorable are stated for discussion:
The MIT paper substituted the absence of best practices in channeling vast amounts of data to KPIs with a promise of machine learning enabled dashboards. One third of the 4k respondents blend their experienced intuition with data. The assumption that relevant data crossed with a curious, experienced mind yields optimal results sounds fair. The caveat in the data assessed strategy imperative is the more strategic a decision, the less relevant operational data is for the narrative. FP&A should manage the expectations accordingly. Be it less for the far future, prediction machines can provide value to the foreseeable future:
The basics are laid out in the book “Predicition Machines. The simple economics of Artificial Intelligence.”
Summary
The common theme is a broad applicability of prediction machines that should be countered with a broad analytical stream of its strategic effects. Beyond the fears, uncertainty and doubt of the digital brain, this stream provides for vision and ideas that can help shape strategy. Optimal decisions today on maximizing future yield can be scaled with prediction machines. Our instincts on causality in the analog world guides these in what they do best: finding correlations in data rich environments. FP&A has the potential to coordinate the discussion and ensure an aligned application of prediction machines throughout the company.
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