Intense competition for product companies and retailers and the squeeze on margins challenge companies to get a lot better at planning.
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Demand Management as a pursuit, a skill, a function and a set of technologies, has grown considerably in importance due to new ways to reach customers and new ways to analyze data about them. Intense competition for product companies and retailers and the squeeze on margins challenge companies to get a lot better at planning.
The web, mobile, sensing, and location-based services have provided more sources of data. Analytics and the constant refinement of planning techniques have provided more fine-tuning abilities and made our forecasts more accurate.
Companies need to pursue the skill sets and capabilities in demand management that allow for improved customer service, protection of margins, management of the extended supply chain, and precision in product offerings—right product, right price, right time, right place.
In this series we will explore the Demand Management Technology Market from several vantage points:
Firstly, we will explore new innovations in the market. What are the new advances? Why are they important?
Who are the players? What do they do? Who do they serve? This topic will be tackled in a number of ways. This series of articles will position the Demand Management players in the market by major attributes and markets they serve.
Then we will review the Retail Market for Demand Management. Retail technologies, especially in demand management, have been undergoing a revolution. Mobile, social, and search have changed the game of understanding and reaching customers.
Demand Management for Manufacturers will be next. Manufacturers have some similar issues, but also many that are distinct from retailers’ concerns. Collaborating and integrating with complex supply chains to ensure product timeliness and overall total cost of the supply chain is more critical than ever with global competition, private label, and new requirements placed on the manufacturers.
Then we will tackle the thorny challenges of analytics. Big data? New algorithms? Social sentiment? Elastic clouds and high-performance servers, to name a couple, have given the enterprise new ways to understand their markets.
Finally, we will discuss architecting demand management solutions today. There are departments and employees in remote locales, inter-departmental involvement in supply chain, multiple layers of management (for multi-plan alignment), and different types of forecasts. Therefore, demand planning processes, timing, and workflow need to be well designed to ensure full engagement, consensus, and most importantly, precision, to improve supply chain performance and corporate revenue growth.
We’ll conclude with The Dream Demand Solution, a composite of the best ideas in Demand Management technology.
So why read this report? In the words of Michael O’Guin, “Competitors never halt innovation and new product introductions; therefore, if a company fails to invest, it should assume a deteriorating competitive position.” Look around. Have we not seen new stars rising as older stars fall? Are there new risks? Do some firms seem to have the edge in brand marketing, understanding their customers, and getting the extra edge in profits? These outcomes are not accidents, but the result of the pursuance of constant innovation and improvement—across the board—in business practices, product innovation, relationship and employee practices, and technology adoption. Demand Management is just one, but terribly important, aspect of this pursuit.
Technology Providers Covered in this Series
Enhanced Retail Solutions
New Dimensions for Demand Technology
In this article we will cover the many new and interesting innovations coming from the Demand Management Technology Market. Some may be considered leading edge. Some are practical refinements made more practical and easier to adopt. These refinements follow a more evolutionary curve as end-users become more skilled at managing their supply chain data and business processes.
We will look at both the revolutionary as well as the evolutionary elements. In fact, you will need both dimensions to stay ahead of your competitors who, often, are also innovating to gain insights about their markets.
The Revolution in Demand Technology
So let’s wade into the revolution. The web, mobile, and big data have allowed us to directly understand the elusive customer, rather than relying on inference or second-hand data. Here are a few examples:
Social Networking—Consumer Engagement, i.e., directly communicating with your customers, learning from them, incenting them, and building their loyalty through social and mobile is critical, especially to brand and manufacturers who may not have direct reach to the consumer. Retailers also benefit, since they bear most of the burden of incenting customers to buy.
Social is also about culling metrics, i.e. social sentiment. These are early days in creating and leveraging the results from social data to understand brand power, product preferences, and the power of the group.
Crowd Sourcing—Location-based services (LBS) is a growing field. GPS coordinates can help consumers to locate as well as be located. As a foundation, these coordinates aligned with consumer data can be used for demand shaping, i.e. crowd sourcing. Crowd sourcing is a bi-directional or many-to-many concept not only to understand the ‘crowd,’ but also to create crowds or bring the crowd to you. Here is where the adjacent technology provider can partner with firms who provide location-based systems and social streaming and blend them with the demand solution to create a world of interactive real-time processes with customers.
Mobile—Mobile is the platform of choice for a new generation of consumers and business people on the move. Here we are engaging directly with the customer. We may have other information about the customer if they have signed up for a loyalty program on the phone. The mobile platform is a rich source of data, but more importantly, it affords an opportunity for direct customer interaction. We are still in the infancy of what can be done here.
Promotions, locating, social networking, and the promise of crowd sourcing for demand are all applications in use on the mobile platform. The ubiquitous QR codes, mobile coupons, etc. have high value for demand, not only to incent customers, but to provide a complete integration of the information chain. Unlike paper or other media advertising, mobile couponing can be used to ensure that your promotions create the right kind of behavior and your partners are properly compensated for promotions. Mobile couponing has built customer loyalty in many strong ways and direct-to-the-phone holds the opportunity for more exclusivity (i.e. your points).
Predictive Demand Analytics—Finding a more scientific approach to understanding demand signals. Predictive demand analytics uses machine learning engines, other knowledge/AI, and analytical approaches. Using history is an important step forward for planners, but too often, history is driven by supply constraints. History tells us: “This is what we had, so that is what we sold.” But it doesn’t tell us what the customer wanted. So, the goal really is to understand demand streams, which are many and have various levels of accuracy. Intuition is good—but can be enhanced with science. We will talk more about this concept later in the report. This is the new mathematical frontier of Demand Management!
Gamification—Launching a new product and want to know if consumers will like it? What features will they really want? What are they willing to pay for it? Engaging the consumer before a product launches or before buyers place risky bets on products can not only save companies from product obsolesce and markdowns, but can also help them set the initial ticket price. Setting the right price initially can also avoid markdowns and margin loss later on.
Search and Big Data—Search and ye shall find—and be found. This is big business for marketing. Although the science behind tracking and offering “those who bought this also buy that” or the new social version, “your friends like this” has been around for a decade, in our language—demand shaping, i.e., linking these specifically to forecasting—is still in its infancy.
High-performance servers—The use of memory-resident architecture is not new in supply chain. We have seen simulation systems since the early 1990s, but they really came into favor with the explosion of Advanced Planning & Scheduling software and inventory optimization systems in the late nineties. New analytics engines are on the market as appliances or accessible in the cloud.
Cloud Platforms—Demand goes to the cloud. Many players are providing hosted systems in the cloud for their customers. And some are providing multi-tenant solutions which are really useful for demand collaboration.
UI—Not to be underrated, the user interface is not just a screen or report design. It’s an effort to create a better module for users to deal with multiple data threads streaming and screaming at them, as well as the myriad of platforms they may use to access the data—whether mobile, tablet, web, or desktop.
That is all exciting stuff. But as my parents told me, do a little homework before you play. In this case I mean it’s time to step up your game—foundationally—in the art and science of demand planning and forecasting. Let’s look at a few developments.
Managing demand across the product lifecycle—Products behave differently in their early days than at a potential end of life. Modernization of old brands has provided explosive growth in many product categories. How can we manage that transition?
Promotional impact—What are the interactional impacts of multiple promotional programs? Often companies look at ‘a promotion’ and try to finesse an uplift number. But campaigns have a lot more complexity. What if I use multiple promotional approaches—mobile and TV vs. social and TV? Or magazine coupon and web coupon vs. newspaper, etc. The old adage, “50% of my advertising works; I just don’t know which 50%,” can be addressed to determine not only effective promotions, but the value of combining programs. What is the value of one placement vs. another? Insert vs. back page? Upper right vs. lower right? Many of these decisions are extremely costly. And you want to know what is really going to work.
Web analytics—This same discussion holds true on the web. What campaigns and web channels were most effective for you? Which drove the most traffic?
Attribute-based forecasting—Attribute-matching technology looks at various product and demand/market characteristics. These traits can be features that can be used across different product families, colors, categories; or customer demographic information such as gender, age, geography. When examining attributes, products align in many ways. This approach becomes very useful if you are determining demand for features, add-ons, etc., that traverse multiple products. For example, anti-oxidants are really popular now. So in which products—cereal, crackers, cookies—should we put dried blueberries? Or in which TVs or PCs do we embed certain hardware or software features? In industrial manufacturing, these types of decisions—2-door or 4-door for example, have huge ramifications across manufacturing. They affect the actual plant and inventory and cost scores of millions of dollars in line design, parts, etc. These are incredibly important decisions. And tracking demand once a product is on the market to make changes up or down in your offering as soon as possible is essential. This leads us to the next topic.
Demand sensing—Here we are in the domain of short-term demand streams. What is happening in the market now and how do I need to adjust forecasts, pricing, replenishment plans, and shipments to reflect the current multi-echelon distribution chain? Demand sensing/near-term forecasting allows firms to live with much lower levels of safety stock.
Demand Segmentation—This looks at products based on their sales performance: fast movers vs. slow, profit, or channels, for example. This approach helps planners prioritize which products need more attention, or group them according to forecast frequency, safety stock, or purchase frequencies, for example.
S&OP Multi-site, Multi-functional Alignment in the Cloud—S&OP is an old story, but poorly practiced. The challenge is that people arrive with different versions of data. Integrating sales, marketing, manufacturing, and executive revenue plans is challenging. Newer approaches of S&OP are smarter engines that sit on top of a variety of the ‘functional planning and operation engines’ (such as manufacturing planning, forecasting, pricing, etc.) to create a holistic way to synthesize the data and allow for simulation that can be reflected back into these functional systems.
Demand Management Now—Not Later
Time to cast off your cynicism about demand planning! Both large and small organizations do get important results from doing demand planning to constantly refine—evolve—their game.
Evolution vs. revolution? Not every innovation needs to be revolutionary. Some revolutionary aspects of demand management are often more experimental, requiring commitment to achieve results. Often, they are not well integrated into other systems, necessitating additional finessing of data. However, they are netting interesting insights for the companies who are forging ahead. And this year, you will see major players taking the leap to integrate innovations like social sentiment and gamification with established methods.
Get to know your business better—analytically speaking. The numbers tell the real story about your business. How do your products behave? What impact do certain business decisions have on the numbers? The demand management players have been enhancing their solutions to provide deeper insights, and you probably can’t afford to miss learning how the markets and customers view your products. It is time to join the re-evolution.