Sophisticated companies use business forecasting software not just for planning, but also as a basis for performance analysis, process improvement, and optimization.
As technologies have improved, they’ve been able to develop solutions that are customized to their business problems, coupled with their data architectures, and integrated with other systems… at a lower cost than ever before.
So it’s not surprising that the market for forecasting software is dynamic. OR/MS Today, a publication of The Institute for Operations Research and the Management Sciences (INFORMS), recently completed its 2016 biennial survey of forecasting software vendors.
Here are 6 trends that professor Vijay Mehrotra and I are seeing in the marketplace and that are detailed in the report.
1. Integration. Corporations are seeking not only to generate forecasts, but also to integrate those forecasts into planning, optimization and reporting systems. As one survey respondent, ForecastPro, stated, “More and more business users are calling for comprehensive forecasting solutions that in addition to simply generating statistical forecasts can be used as the backbone of ongoing corporate processes such as sales and operations planning (S&OP), demand planning and supply chain optimization.” Many vendors appear to be addressing this demand.
2. Automation. Forecasters are seeking features such as automated model selection, automated alerts, and automated graphics and reporting. As data velocity and complexity are growing, there is an increased willingness to entrust model design to the software, especially when many forecasts are being generated simultaneously. In response, nearly all of the vendors surveyed, report having some type of automatic or semi-automatic forecasting capabilities.
3. Visualization. High-quality visualizations are fast becoming part of the “table stakes” for forecasting software packages. In addition to standard statistical output, many of today’s tools offer a range of visuals, including features like box plots, normal probability plots, histograms, ANOVA Pareto charts, decomposition charts and automated statistically-generated range-forecast plots.
4. Virtualization. Several vendors have begun to move their offerings to the cloud, offering virtual hosted forecasting tools. Statgraphics, XLMiner.com, Roadmap GPS and PEERForecaster/PEERPlanner all mentioned their cloud offerings. As cloud computing continues to grow, we foresee this trend continuing.
5. Forecast quality measurement. Forecasters are continually pressured to improve the quality of their forecasts, or defend why their forecasts are as good as they can get. Vendors are addressing this need with solutions such as automated ANOVA analysis, automated naïve forecast generation and automated forecast value added analysis.
6. Capabilities enhancement. Forecasting software vendors are giving increased attention to “hard” forecasting problems such as new product forecasting and forecasting of intermittent demand, while also providing ways to integrate additional machine-learning techniques into their forecasting suites. Some vendors are offering the ability to create automated ensemble forecast models, built by combining multiple forecasts, generated by employing different techniques in order to improve overall forecast accuracy.
Read the full report on business forecasting software, including a case study about California rainfall that illustrates these trends, at OR/MS Today.
Chris Fry is an expert in using analytics and data science to support strategic decision-making. He has over 20 years of consulting experience at firms including Booz&Company and McKinsey, and is now Managing Director at Strategic Management Solutions. He has worked with BTG on numerous projects and has served clients in a wide range of industries, including high technology, energy, automotive, life sciences, and consumer products.