October 17, 2017
Digital Crystal Ball: Seeing the Future with Predictive Analytics
You might not be able to actually see the future; however, with predictive analytics you can get pretty darn close. By monitoring data, businesses can see their future trajectory and stay on the course of improvement and success. While the future remains unwritten, data can help you control where your story goes next.
Descriptive analytics tell the stories of the past. Predictive analytics look forward. While some market behaviors prove highly unpredictable, predictive analytics can guide businesses in the right direction. Marketing managers tend to leverage predictive analytics the most, however they serve a wide array of business functions. A company may use predictive analytics to determine if they will be successful in a new market segment or geography. Economic predictive analytics can allow hiring managers to make sound decisions given the future state of the economy. The possibilities are endless.
In marketing, predictive analytics allow companies to hone in on high-value prospects and create impactful messaging and content. Marketing professionals that focus on their ideal customer profile, can use predictive analytics to determine how best to reach them. Which marketing channels present the best ROI, what kind of messaging to create and how to turn general interests into sales.
Predictive analytics extend beyond outbound and target marketing. It can also help with inbound marketing. For companies that possess an inflow of inbound leads, predictive analytics can help decide which ones to prioritize. This allows your sales force to quickly target and engage with the right prospects.
Supply Chain Optimization
Supply chain optimization is critical for the health of any business. Demand planning, procurement, inventory management and logistics all play a role in delivering the optimal amount of product to the end user at the right time at the right cost. Predictive analytics can help navigate the complexities of supply chain optimization.
Integration of the internet of things and predictive analytics in supply chain will be key to servicing consumers and their just-in-time expectations. Machine learning models can trigger demand signals upstream to prevent stock outs and service failures while carrying lean inventories. This is an example of how predictive analytics works in conjunction with other technologies that will be integral in digital transformations.
Predictive analytics present endless opportunities for businesses to make their organizations smarter and more profitable. How companies decide to harness the power of predictive analytics will be determined by their overall digital strategies and willingness to espouse new, advantageous technologies.