Weather Data Analytics

How Weather Data Analytics Can Help You Succeed

Using data analytics to improve decision making is smart. One area that is gaining traction because it has a daily impact on business is weather data analytics.

As with analyzing data about anything, analyzing weather data can give your business opportunities to improve that it hadn’t realized with other types of data.

By turning granular weather data into meaningful business intelligence (BI) results, companies anywhere in the world in any industry are enabled to:

  • Reduce wasteful spending
  • Increase ROI
  • Optimize logistics
  • Fine-tune marketing campaigns
  • Effectively plan for resource usage peaks and lulls
  • Increase management’s ability to forecast and plan
  • Optimize supply chains
  • Pinpoint times to purchase inventory
  • Adequately plan staffing
  • and more

With weather data analytics, companies can answer such questions as to why one location is outperforming another, how to properly stock shelves and manage inventory purchases, how to maintain appropriate staff levels, why sales were higher (or lower) on a particular day, and what changes are needed to successfully manage their supply chains.

The types of weather data that can be collected include:

  • Temperature
  • Precipitation
  • Snowfall
  • Wind speed
  • Cloud cover
  • Dew point
  • Relative humidity
  • “Feels like” temperature (wind chill & heat index)
  • Surface pressure
  • Specific humidity
  • Wet bulb temperature
  • Visibility

Here are some examples of how some companies have used weather data analytics:

  • A national motorcycle brand analyzes past weather data to help them successfully plan and deploy a marketing plan that targeted their consumers at the right time in the right locations in a way that significantly increased sales across the US.
  • Energy companies use past, real-time, and forecasted weather data to help plan resources accordingly, especially for peak usage periods, leading to efficiency and improving the bottom line.
  • Retailers use weather data to optimize their supply chains, pinpoint times to purchase inventory, reduce stock-on-hand amounts, improve staffing, and optimize marketing programs.
  • Restaurants find that analyzing weather data increases management’s ability to forecast and plan in areas such as staffing, sales, and inventory purchases, which all lead to an improved bottom line.

Imagine how empowered your management team can be if it can access past weather data to identify the weather sensitivities for your company through sales analytics, marketing analytics, and traffic analytics.

The potential to be able to make insightful decisions to improve your company’s bottom line is possible with the right technology.

In pursuing the best way to obtain weather data for your company, consider the types of data that are beneficial – the more types of data the better. How many resources are being used to collect the data? Is it simply radar and satellite, or is it a suite of weather models? Also consider how far back in the past data is available – having a history leads to better predictive analysis.

A very important point to consider is how relative the collected data is to the location you need it reported on. Is the weather being collected from a weather station up to 50 or even 100 miles away from your business, or is it within a couple of miles using a ZIP Code or Lat-Lon point? There can be a lot of weather fluctuation within a few miles, so this is a serious consideration.

There are companies, such as Weather Source, that can collect and deliver precision weather data for you so you don’t have to make large investments and try to reinvent reliable weather data yourself. Weather Source has already done all the hard work.

And BI platforms, such as Domo, Tableau, and Qlik can enable your company to apply weather data analytics to your business processes.

If you haven’t incorporated weather data analytics into your business’s BI platform, what are you waiting for?