Here’s a nice quick read about how Machine Learning works. A few points we’d emphasize: 1) Usefulness of current machine learning tools is a function of data and pattern recognition. The more relevant data that the machine learning tool can utilize, the more likely it is to recognize patterns to improve accuracy in the assigned task. 2) In order to facilitate the learning, “researchers continually monitor the input data streams and make adjustments if necessary.”
Here at Sales Temperature, we are rapidly growing our user base, allowing us to feed our machine learning tool with additional retail sales data. We are also constantly testing and adjusting external variables. As a result, our machine learning tool is getting smarter every day and producing increasingly accurate sales forecasts. Visit us at http://www.salestemperature.com to sign up for a free trial, and “Know Tomorrow’s Sales TODAY.”
Welcome to the Sales Temperature Blog! Here we will try to highlight and discuss articles that we feel may be helpful and informative. We recently read this article in the Wall Street Journal regarding some of the regulations that are being adopted by state and local governments to address concerns of part-time workers:
The article highlights three primary goals shared by many of these regulations. First, provide employees with more notice of their schedules. Second, give employees more access to extra hours. Third, provide compensation to employees for last-minute scheduling changes.
We believe that these kinds of regulations highlight the need for retail managers to more proactively manage employee schedules. This may seem like a daunting challenge, but we are here to help! By utilizing advanced machine learning technology, Sales Temperature provides an accurate, continuously improving seven-day revenue forecast that can be used to predict labor needs and provide the insight and lead times to anticipate schedule changes. All of which will help retail managers to effectively react to changes in regulations.