Omnichannel is changing the way we view demand planning

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Omnichannel Analytics are helping companies uncover patterns in big data to improve the customer experience.  Using those insights, companies can anticipate what consumers are planning to purchase and influence that purchase in real time.    

Companies are experiencing unprecedented complexity as they look for growth and market opportunities. Their product portfolios are growing with new product introductions, new approaches for existing products and new sales channels. The emerging endless aisles of the Internet and mobile are expanding product offerings, adding unparalleled supply chain complexity and making it difficult to manage inventory effectively. Trade promotion spending, designed to grow sales revenue, continues at a staggering pace.

The ultimate goal is to grow demand, but it comes at a cost—the cost of demand complexity. This complexity makes it hard to forecast demand accurately when faced with expanding new items, new channels, shipping costs and new consumer engagement preferences.

Companies are quickly realizing that traditional demand forecasting techniques in this complex environment have reached their limitations, and are no longer capable of hitting the target.

What role does data driven analytics play?

To address these new challenges, companies are striving to become more data driven. They are embracing analytics capabilities, which requires emphasis on new data streams as an opportunity to measure the effectiveness of marketing campaigns, sales promotions, product assortment and merchandising.

The goal is to improve decisions regarding products distribution, and operations across all channels of their business.  As direct customer relationships are influenced by mobile devices and in-store IoT these new data streams are introducing new sources of insights. However, it’s taking time to transition from a limited analytics role to a more expansive role.  Companies are quickly realizing that their enterprise effort requires a completely different culture that includes different skills, processes, and technology. Although many companies have already started to collect data across all their distribution channels to gain more customer/consumer information, the race to apply analytics and optimize sales and inventory across all channels has taken much more effort than anticipated.

Meanwhile, consumers have been gaining power and control over the purchasing process, as well as driving new buying experiences. Unprecedented amounts of information and new digital technologies have enabled this control over retailers and manufacturers.  Instead of influencing consumers to buy their products in traditional brick-and-mortar channels, marketers have found themselves having to create new digital buying experiences.  Even as customers continue to exert unprecedented control over the purchasing process, power is starting to revert back toward marketers with the help of new technology and predictive analytics. Which is now possible with a consolidated view of online and offline sales combined with other shopper behavior such as upstream website visits.

Why is consumer control important?   

Consumers are turning increasingly to technology to help make purchase decisions. That has been enabled by four converging trends, according to Consumer Goods Technology.

  • A shift from active engagement to “automated engagement” where technology takes over the tasks from information gathering to actual purchase.
  • An expanding Internet of things (IoT), which embeds sensors almost anywhere to generate smart data regarding consumer preferences and triggers actions and offers by marketers.
  • Improved predictive or “anticipatory” analytics technology that can accurately anticipate what consumers want or need before they even know it, based not just on past behavior but on real-time information and availability of alternatives that could alter consumer choices.
  • The availability of faster and more powerful software combined with supper computers that crunches petabytes of data, filters it using advanced analytics to help marketers gain previously unheard of efficiencies and make highly targeted offers.

Companies are addressing some of these issues by improving alignment between different functional units, introducing advanced analyticsand taking an agnostic approach to inventory and distribution.  Developing strategies to fulfill orders from multiple channels (nodes) in the supply chain network are driving this change. This requires the need to sense downstream consumption for all channels in the supply chain network. The ability to fulfill orders from the distribution center, direct from the factory, or from various other demand points in the transactional lifecycle are essential to winning.

Why Omnichannel analytics?     

Predicting demand and managing inventory across every channel is hard work. With shorter product lifecycles, expanding assortments, frequent price changes and sale promotions compound the challenges companies are experiencing due to the disruptions created by digital commerce.

It’s enough to make you wish you had an “easy button" to figure out today’s savvy shoppers. Fortunately it’s not necessary.  With a demand planning and optimization solution, you can simplify your demand planning process and create an integrated planning framework that supports multiple forecasting methods with one synchronized view of demand and supply for every type of customer.  Making predicting the future much easier and more precise than ever!

When are you planning to take a serious look at demand planning and optimization powered by Omnichannel Analytics?

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About Author

Charlie Chase

Executive Industry Consultant/Trusted Advisor, SAS Retail/CPG Global Practice

Charles Chase is the author of Next Generation Demand Management: People, Process, Analytics and Technology, author of Demand-Driven Forecasting: A Structured Approach to Forecasting, and co-author of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation, as well as over 50 articles in several business journals on demand forecasting and planning, supply chain management, and market response modeling. He is the advisory industry consultant and team lead for the SAS Retail/CPG global practice, and writes a quarterly column entitled, “Innovations in Business Forecasting” in the Journal of Business Forecasting. Author page

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