Predictive analytics can help us estimate how many units we will sell of the product, but that’s not the only thing predictive analytics tells us about. Business forecasting and predictive analytics can also be used for insights into relationships so you can better identify risk and opportunities before the event, or identify the driving factors which allows us to shape demand, instead of sitting back and waiting for the demand to play out organically.
And that level of insight is super powerful.
Ahead of IBF’s Predictive Business Analytics, Forecasting & Planning Conference In New Orleans from May 6-8, 2019, I want to discuss just what predictive business analytics can do, and why it is so important. The above are all business decisions that need to be made and they all require some kind of prediction or insight to help guide that decision. We tend to think only of the big decisions, but the reality of business is that we take many decisions (big and small) every day at every level in an organization. Every decision has an input and judgement and if there is a time lag between that judgment and the result of the decision, it also requires a prediction or forecast.
Most Predictions Are Just Hidden Assumptions
More often than not, our predictions are hidden inputs into the decision-making process, i.e. we take decisions based on non-data driven assumptions. But of course, better predictions means better decision making.
Companies in the future that unlock the full potential of business forecasting and predictive analytics will make smarter and faster decisions, as well as redefine business operations. Strategically, predictive analytics allows for a objective, unbiased evaluation of information to help pursue new opportunities.
Predictive Analytics Allows For Micro Targeting
Tactically, predictive analytics can allow companies to micro target a market with precise accuracy, as well as help determine who to reach and when, and how to shape demand. And operationally, in almost real time, predictive analytics allows you to sense and react immediately across an entire supply chain to signals and changes.
10 Important Predictive Business Analytics Examples
But what are real life predictive business analytics examples? Here are just 10 of many business questions that can be answered more effectively with predictive analytics:
- Can we service our customer? With accurate forecasting, you can achieve a higher rate of OTIF delivery. The information from demand forecasts can not only help to achieve these targets but also provide a clearer picture for the customer of what service may look like in the future.
- What should we carry in inventory? The more accurate the demand forecast, the better prepared your company will be to manage its inventory and resources. With a more consistent demand plan, you can factor in and reduce uncertainty which means better management of cash.
- How much risk is involved? With ambiguity increasing in today’s business, it’s more important than ever to determine the risk of developing a new product or expanding into a new market. Predictive analytics can help provide the insights and probabilities of what could occur.
- Are we going to keep that customer? Every business wants to predict which customers are about to leave, and for what reasons, so they can manage churn and target their retention efforts. Without predictive analytics, a retention campaign may be a lot costlier.
- Should we discontinue this item? Business forecasting can look at what future sales and market share may be for a particular item, along with segmenting based on other items, as well helping to identify which items may be less profitable to maintain. Predictive analytics also can help understand cannibalization or provide a more complete picture of impact if the item is discontinued.
- Should I lower the price? Price elasticity models are based on analysis data that can be converted into predictions. Even better though, solid forecasting may help elevate the need. Better predictions ahead of time may prevent the need for panic sales to rid your business of excess merchandise.
- Who should we target? Predictive analytics may be used by marketing departments for micro-targeting campaigns for a narrowly defined audience. Understanding the correlations, relationships, clusters, and probabilities or outcomes with different variables are predictions that need to be made.
- Is this a fraudulent order? Predictive analytics can be used in fraud detection by understanding behaviors and patterns, using predictions of what customers typically order and looking for outliers to those patterns.
- What is the impact on margin? Business forecasts can help provide insights and stability in the signal with fewer changes. Financial managers can do more precise net-revenue forecasting by calculating the expected cost of ordering products, price cuts, promotions and advertising, and the gross revenue from expected sales.
- What color should the banner be on our website? Another way predictive analytics helps companies is with understanding how price, placement, wording and even color schemes on websites impact sales. Online retailers can use the tons of data they gather on the behavior of their customers to make adjustments based on what appeals to them the most.