For Climate Month I thought I’d research something on the positive side of the equation. My last two climate posts were a bit gloomy, as they focused on greenhouse gasses and ocean acidification. Instead we’re going to tackle a product adoption issue related to the climate: When might the United
When it comes to forecasting new product launches, executives say that it's a frustrating, almost futile, effort. The reason? Minimal data, limited analytic capabilities and a general uncertainty surrounding a new product launch. Not to mention the ever-changing marketplace. Nevertheless, companies cannot disregard the need for a new product forecast
My colleague Gerhard Svolba (Solutions Architect at SAS Austria) has authored his third book, Applying Data Science: Business Case Studies Using SAS®." While the book covers a broad range of data science topics, forecasters will be particularly interested in two lengthy case studies on "Explaining Forecast Errors and Deviations" and
There are two ways you can react to a “Hey – that was my idea” situation. The first would be to throw a pity party and lament about how unfair life is – if only the car hadn’t broken down and I didn’t have grass to mow and laundry to
Because you are already halfway there and you should want the entire process to be data-driven, not just the historical reporting and analysis. You are making decisions and using data to support those decisions, but you are leaving value on the table if the analytics don't carry through to forecasting. In the
We ended last time having selected a cluster of surrogate products -- a subset of the original selection of like-items that had the same attributes as the new product. Judgment has been used throughout the process so far, in specification of the relevant attributes, filtering the original candidate pool of
The real estate market provides a good example of the use of analogies. To determine a reasonable listing price for a property (such as this dump on the right) that is new on the market, the sales agent will prepare a list of "comps" (comparable homes) that are currently on the market or
How do you build a forecast when you have no historical data? This is a recurring challenge for businesses that update their product offerings, and a recurring question in online forecasting discussion groups (e.g. this one on LinkedIn). The bad news is that you probably can't expect to achieve highly
Q: Company always try to forecast 12 or 24m ahead. Whether we should track accuracy of 1m/3m/ 6m or x month forecast, does that depend on lead time? How to determine out of these 12/24 months, which month should we track accuracy? Correct, forecast performance is usually evaluated against the
Have you noticed the annoying stock art they put on The BFD blog header? All I can think of is "If those idiots only used SAS Forecast Server, they wouldn't have to draw graphs all over their window panes just to do forecasting." It must really p.o. the housekeeping staff at that
Love can make a person do bad, dangerous, stupid, and irresponsible things. Love of country can make a politician stray from his wife. Love of Pepsi can make a pop musician lose his hair in a pyrotechnics-gone-bad commercial. Love of acting can make academy award winners accept starring roles in Ishtar. And for
