Articles

What Is Analytics?

It isn’t news that we are living in a data-driven world. And the pace at which data flows into our daily lives increases in such a way that makes it impossible to keep on top of it all.

When running a business, you collect a lot of past actual data in some format to use for various future forecast and budget activities.

Adding weather analytics to your company’s BI platform can help you find ways to reduce wasteful spending, increase ROI, optimize logistics, fine-tune marketing campaigns, improve resource planning, and so much more.

Simply put, “analytics” is turning your collected data into insights to know, for example, when to order supplies or help determine how many employees to have on a particular shift.

Analytics is changing everything from businesses and sports to government and healthcare.

Here’s a helpful definition from Wikipedia:
Analytics is the discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance. Analytics often favors data visualization to communicate insight.

By tracking several different types of data from past actual activity, you can apply formulas to that data (through software such as Microsoft Excel, or platforms such as Domo, Tableau, and Qlik) to gain insights that inform decisions to help you predict future activity and performance.

Sports analytics have been used for years. It’s where data, such as averages, performances, and tendencies of individual players have been recorded and shared out as statistics by player, by team, by league, and so on.

If you run a retail business, you have an understanding of the importance of price points with your competitors. You collect certain types of data and analyze it in a way that helps you remain in business.

In the healthcare field, medical professionals use analytics to gain direct access to data that can help improve performance and deliver better patient care.

In your own personal world, your smartphone is constantly tracking your location and how fast you are traveling. Fitness bands track your heart rate, number of steps taken, number of calories burned, and even how well you sleep. Data is collected and processed, and you use the analytic output to determine how much farther you want to go, how to choose better foods to eat, and how to improve the quality of your sleep.

Analytics is a way to improve your business (or your life) through knowledge gained from experience and past performance; it gives you the ability to understand data in a meaningful and new way.

The companies that use analytics to make insightful decisions are the companies that are moving ahead of their competitors. Isn’t that what you want to be doing?

Weather Source Delivers Next-Generation Business Intelligence with OnPOINT Weather

OnPOINT Weather™ provides the accurate and reliable hyper-local past, present and forecast weather analytics businesses demand to optimize their global operations. Read our press release:

http://www.businesswire.com/news/home/20160607005148/en/Weather-Source-Delivers-Next-Generation-Business-Intelligence-OnPOINT

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?

Weather for Analytics

Are you looking for weather data for analytics…i.e., weather data at the ZIP Code or even the Lat/Lon level?  OnPoint from Weather Source is what major organizations utilize to analyze their data (energy, sales, etc.) with the granularity to make your results meaningful. Most other sources are weather reporting stations like airports. If you or your clients live next to an airport, then you are good to go. However, this is usually not the case. Weather Source’s OnPOINT  utilizes 15 data sources to determine accurate weather readings (temperature, dew point, humidity, wind speed, etc.) by ZIP Code or Lat/Lon.

Most of our weather analytics clients obtain 3 to 5 years of historical weather data. With the historical weather they can utilize various statistical methods to help discover patterns and relationships between weather and their data. Our clients can also analyze the historical weather data and their own historical data to “forecast the past”. “Forecasting the past” is a necessary part of the process. Without this knowledge, you are just making assumptions. Granted, you may assume correctly on obvious relationships, but it’s the subtle data relationships that can be discovered and become the most useful. Once these relationships are understood, then applying current and forecast information can be beneficial to your organization’s bottom line.

In a nutshell, analyzing the relationship between weather and your data can assist in:
-Adjusting and optimizing logistics
-Adjusting and optimizing marketing strategies
-Reducing waste
-Increasing ROI
-Improving the bottom line.

Our OnPOINT data is available in CSV format or through using our Weather API. OnPOINT Weather is brought to you by the team at Weather Source – the experts in historical weather data, and trusted by numerous Fortune 500 companies to provide their past weather needs, including:
-Walmart
-Target
-Comcast
-Live Nation
-Darden Restaurants

Weather for Business Intelligence (BI) enables businesses to discover and learn how weather affects their sales, energy, product distribution, organizational performance, and more through weather analytics.

Sales: WS_Sales@weathersource.com

Weather Source
1 Stiles Road #201
Salem, NH 03079
844-813-2617 (toll-free)
Fax: 866-703-7505

Twitter: https://twitter.com/weather_source

Weather for Business Intelligence (BI)

Modern Business Intelligence (BI) platforms enable companies to harness Big Data and leverage it in a way that is visual, complete, and insightful. BI empowers organizations with the knowledge and insight they need to make better business decisions and execute faster.

Weather for BI enables businesses to discover and learn how weather affects their sales, energy, product distribution, organizational performance, and more through analytics.

OnPOINT Weather from Weather Source provides hyper-local past (back to the year 2000), present, and forecast weather.

When integrated into a BI platform such as Domo, Qlik, or Tableau, OnPOINT Weather enables companies to analyze correlated weather information to proactively strategize operations, sales, and marketing to improve future performance and optimize profits.

OnPOINT Weather turns granular data into meaningful BI results that enable companies anywhere in the world in any industry 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

Business intelligence with OnPOINT Weather enables organizations, such as these, to identify trends specific to their industry and locations. Companies can answer 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.

By using the high caliber of past weather data delivered through OnPOINT Weather, companies can reach their performance, monetary goals, and other business milestones.

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.

Why Weather Source and OnPOINT Weather?

The Weather Source team has been using cutting-edge science, engineering, and meteorology expertise to deliver precise weather data since 2004.

OnPOINT Weather is ‘on point’ and contiguous. No other weather information system is as complete or leverages a wealth of inputs such as radar, satellite, weather station observations, and a suite of weather analyses and models to accurately determine weather conditions worldwide.

OnPOINT Weather provides the highest resolution of global weather data that businesses need to support their operations around the world.

Weather Source is a global provider of precision weather data. OnPOINT Weather provides information precisely relevant to locations via ZIP Codes and Lat-Lon points for all major land masses and extends to more than 200 miles offshore.

Weather data is available instantaneously from the OnPOINT Weather API. Data retrieval is phenomenally fast and highly available and scalable through the API. Weather Source is able to process a virtually unlimited number of requests through numerous cloud-based servers.

Industries currently using the precise data supplied by OnPOINT Weather include: automotive, aerospace, chemical, manufacturing, construction, banking, finance, entertainment, media, major league sports, film & broadcasting, healthcare, pharmaceutical, travel & tourism, energy, insurance, weather, computer, telecommunications, and more. State, local, and federal U.S. government agencies and top universities and academic institutions also use OnPOINT Weather.

Business Intelligence (BI) is the wave of the future.

Business Intelligence is the ability to transform tremendous amounts of raw (structured and unstructured, external and internal) data into meaningful and useful information to use for analysis.

BI technologies use past, current, and future predictions to enable businesses to identify new opportunities and implement effective strategies for long-term growth and stability.

Companies need to have some type of BI process to remain competitive in their markets and industries. BI supports management in decisions pertaining to operations, strategic goals, benchmarking, performance management, analytical processing, reporting, and so much more.

How can historical weather data help your business?

Society, in general, is very adept at using weather forecasts and past experiences to make near-term personal or business weather impact decisions.

We have all seen how weather can impact an organization’s operations. Many organizations have plans in place to deal with weather. For instance, schools close when needed and add extra days to the school calendar in response. Many grocery stores staff based on expected weather and customer demand, but in general the overall impact to grocery stores is a time-shift of customer purchases and therefore the impact is lessened somewhat (http://www.federalreserve.gov/pubs/feds/2000/200008/200008pap.pdf). Unfortunately, many other businesses like restaurants are impacted by weather and have no substantial way to recoup the lost business due to events like snowstorms and rain.

What if you could better understand the impact of weather and use the insight to take advantage of opportunities or cut costs? Today’s technology will let data scientists analyze weather and other datasets at levels of granularity that are amazing. The starting point is by looking at historical weather first. Historical weather information can be used in analytical models to help determine patterns and relationships with other datasets (like sales, energy usage, etc.). It is easy to understand how energy usage is affected by weather (especially temperature), but other patterns and correlations can also be discovered. One widely mentioned example of unexpected discovery with weather events and retail is a dramatic increase in strawberry Pop-Tarts at Walmart stores ahead of a hurricane (http://www.adweek.com/adfreak/hurricane-coming-get-pop-tarts-21329).

To do these correlations, a data scientist or analyst will use many different methods to help them understand the relationships and patterns between different datasets. Once these patterns and relationships are better understood, current and/or forecast weather can be incorporated to help predict sales, usage or other impacts. This is how historical weather data can benefit a business. Is this process beyond your capabilities? There are a number of independent data scientists and business analytic experts that can assist smaller organizations who don’t have the staff to perform the analytical functions.

Since weather is local, it is imperative that organizations offering or performing the analytical services use the proper weather data for their analyses. In the past, historical weather data has been only available from weather reporting stations, many of which are located near airports. Weather data from stations 10 to 50 miles away may not be very useful, especially if elevation or coastal influences are common. Technology is such that historical weather data down to the ZIP Code or Latitude/Longitude level is now available making it possible to correlate weather with specific locations. After these correlations are understood, it is then possible to use this intelligence in many ways. At the very least, the knowledge of how last year’s sales or energy usage was impacted by weather can assist in making decisions about what to do this year. By using weather forecasts, the same correlations can be applied and actionable decisions can be made for the near-term. Some long-range forecasts (15-90 days out) are granular enough that they can also be used especially if temperature extremes impact your business.