What You Can Learn About Predictive Intelligence from AccuWeather

If you want to get the best ideas you'll often need to look outside your imminent department, business unit, or even enterprise. Take data analytics. Some of the most innovative applications are coming from… wait for it… businesses that make it their business to accurately predict weather patterns. It makes perfect sense if you think about it. Everyone is obsessed by tomorrow's weather: will I bike to work or take the bus? Will my fishing trip be canceled? Will the dry spell hold for this weekend's wedding? Do I need to water the garden? You get the picture… Weather represents the absolute litmus test for predictive data modeling. So, what's been happening in that neck of the woods recently? Earlier this week I got a press release announcing a new "D3 Analytics" capability from AccuWeather Enterprise Solutions. While my initial thought was to bin it, I couldn't resist a skim and was amazed by the parallels. The release touts using "weather data and forcasts with superior accuracy to provide high impact, actionable insights for businesses through data-driven decisions analytics". That's the kind of language I might have used to describe shared services' latest value-add, right? But wait, there's more. What this software does is analyze more than 300 data points, with consumer behavior and sales data, to provide a scientific, predictive base for corporate decision-making. What AccuWeather's leadership team has so accurately perceived is that businesses need all kinds of data, including all that unstructured data that surrounds us, to make smart decisions. The part I really liked is where the company's chief commercial officer describes how the solution takes businesses from "an anecdotal understanding of weather impact" to "real, quantifiable business intelligence that not only protects against lost opportunities but maximizes profits." [inlinead] Let's switch over to shared services for a moment. If you replace "seasonal-specific impact events" with "seasonal specific shifts in services demand" you'll get that you can predict customized delivery models that reflect enterprise demand as well as – and here's the crux – your supply potential. Let's assume for a moment, that there is a lull in your center's activity while at the same time one of your customers has a non time-sensitive requirement for a certain service. Perhaps this downtime in your own team could be transferred to lower cost? The point is that as data becomes more transparent both for you, on the supply side, as well as the customer, on the demand side, decisions can be made that optimize resources. AccuWeather's latest solution promises to "hedge against interruptions in supply chain and production levels". Even more brilliant. Its software can analyze the impact of severe weather to highlight weather-driven opportunities to drive business results. Translate that to shared services language: you could determine the impact of changes in regional sales or shifts in product demand to support business profits. AccuWeather's advantage is that it can work with thousands of companies to sharpen up its knowledge base and drive its capability. But you can, too. Not thousands, maybe, but you have plenty of customers to work with. The "D3" nomenclature is clever: Data Driven Decisions. I'll have to check with legal whether I can adopt the terminology (!) – but you surely should adopt the mindset.

What You Can Learn About Predictive Intelligence from AccuWeather

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