CHANGING INFLUENCES

There are a number of internal and external factors that are shifting companies toward demand-driven business models. It's essential that business leaders recognize the impact of these factors on their business, and act on them.

Today, the traditional top-down approach to supply chain is no longer applicable. Companies have gone through a process where margins have been compromised by changing retailer and consumer purchasing patterns. When retailers started to reduce stock levels and consumers had a tendency to stockpile products, manufacturers responded by creating more product categories in a bid to increase profit margins. The result, product proliferation on shelf, expanded buffer inventories and wasted working capital. Yet forecasts are still based on an inventory or replenishment response.

There is a more fluid distribution of goods today because customer purchase behavior has changed the way products are created and sold. The rise of the Omni-channel and new purchasing processes such as Amazon.com make inventory management more unpredictable. The Omni-channel also increases the influence of external factors like social media, tweeter, and mobile devices which make it more challenging for distributors and retailers to plan deliveries and stock orders. Regardless, same day or next day delivery is an expectation that manufacturers and the supply chain process are tasked to support. These factors are making demand more volatile, and as a result manufacturers can no longer operate using inventory buffer stock to protect against demand volatility as it can too easily result in lost profit.

AUTOMATED CONSUMER ENGAGEMENT

The definition of fast for consumers today is dramatically different from the fast of 5 to 10 years ago. Consumers are demanding more, and expect it quicker than ever before. This is being driven by the Millennials, as they want instant response and same-day delivery. Consumer demand is no longer driven by supply availability, but instead, companies must shift their operational models by listening to demand and responding to consumer pull in order to remain successful. A supply push strategy is no longer viable in today's digit world.

Using sales and marketing tactics and a consumer-centric approach, companies are now pulling demand through the channels of distribution. To do so, sales and marketing tactics have to be more focused on the automated consumer engagement (experience). The influence of unstructured data and social media are having a more prevalent impact than ever before on the entire purchase process, which must be factored into the demand management process. This is the result of the openness and availability of consumer feedback that social media influences and delivers. Feedback via social media is both a gift and a detriment for retailers, distributors, and manufacturers. Although it provides insight into sentiment and provides opportunity for brand exposure, it adds additional complexity to how consumer pull can be influenced. It also means demand can be influenced across multiple channels and, more often than not, with very immediate consequences.

Demand is also changing because customers want to consume products in new ways. Subscription lifestyles and shared economies due to the on-demand world have impacted how companies need to plan, design, and create products for an indecisive generation of consumers. The consumer experience must remain at the forefront of retailer and manufacturer priorities. Flexibility, efficiency, and a consumer-centric approach will be the key to their success.

An increasing percentage of revenue will come from new product lines increasing product life cycles, which are getting shorter. Also, levels of stock-keeping units (SKUs) are escalating. This challenges companies to create faster delivery systems for more products, making the supply chain even more complex. In addition, the rise of online shopping and same-day delivery has resulted in consumers expecting quicker turnaround from retailers and the manufacturers that support them. 3D printing at home is representative of this ever-increasing phenomenon. In the near future, consumers who want a product now may well create it themselves. Companies, particularly manufacturers, will be competing with a very short-lived product life cycle. Business leaders will need to adapt their business models in order to cope with more frequent peaks or troughs in consumer demand. This has to be achieved in a sustainable way and without negative impact on revenue and profit.

NEW WORLD ORDER

Business leaders need to adapt their business models for today's demand-driven supply chain. Big data analytics allows a more accurate demand forecasting and planning process to improve production and shipments. To be successful, companies must redefine their supply chain definition to include the commercial side of the business.

The shift to the next generation demand management will only be achieved through better use of data, the implementation of horizontal processes, and more emphasis on predictive analytics. Subsequently, there needs to more importance on consumption-based modeling using a process called multi-tiered causal analysis (MTCA), which combines downstream data with upstream data and applies in-depth predictive analytics to:

• Measure the impact of marketing programs on consumer demand at retail
• Link retail demand to shipments from manufacturers to retailers
• Enable manufacturers to perform what-if analyses to shape future demand and help them choose the optimal sales and marketing strategy for producing the highest volume and return on investment (ROI)

Consumption-based modeling is an approach that links a series of quantitative methods to measure the impact of marketing programming and business strategies that influence downstream consumer demand (demand sensing). Then, creating what-if scenarios to shape and predict future demand (demand shaping) using point of sale (POS) and/or syndicated scanner data. Finally, using consumer demand history and the future-shaped consumer demand forecast as a leading indicator in a supply model to enhance supply volumes (shipments and sales orders) using predictive analytics rather than judgment.

Once MTCA measures the KPIs (key performance indicators) that influence consumer demand, the demand analyst can model and perform what-if simulations to predict and shape future demand, developing short- and long-term forecasts. These simulations capture real-world scenarios and show what happens in different situations. The demand analyst can simulate the impact of changes on key variables that can be controlled (e.g., price, advertising, in-store merchandising, and sales promotions), predict demand, and choose the optimal strategy for producing the highest volume and ROI.

Through this process, leaders can predict how market influences or changes will impact their supply chain, which allows them to formalize ways in which the business can accurately learn through the increasing automated consumer engagement process. It will require more anticipatory predictive analytics to ensure that the right amount of products in the right product mix make it to the shelves and into consumers' hands. The sheer size makes demand forecasting and planning on a global scale highly complex. Product categories, sales regions, and an abundance of participating internal organizations combine to weave a tangled corporate web. “To have the right quantity of the right products at the right place and time,” companies will rely heavily on the combination of transactional data and digital information to anticipate and influence what consumers will purchase. The overarching goal is to be able to “take proactive measures instead of simply reacting” through strong horizontal alignment processes, stronger collaboration with key accounts (customers), and the use of predictive analytics supported by scalable technology.

GAME CHANGER

To make the shift to the next generation demand management, leaders need to bring together different aspects of the organization to make informed decisions based on a holistic view of available data. Previously, the technology available to companies did not facilitate the integration of data, nor facilitate predictive analytics. This is especially true for the sales, marketing & operations planning organizations. They will all be required to source and share data on a continual basis and learn from not only the shared knowledge collected from across the company, but from information collected digitally by sensors, as a result of Internet of Things (IoT). This is why the corporate culture is crucial to the success of this new demand management model. The culture requires an atmosphere of horizontal collaboration, trust of predictive analytics, and scalable technology in order to ensure all the ingredients are in place. Similarly, organizations need to be ready to work quickly with minimal latency to act on the trends and insights produced. Failure to do so risks a reactive culture prevailing.

There needs to be people with the appropriate skills to provide advice to drive the process with the right domain expertise to make more informed fact-based decisions to support business strategies. There is also a broader requirement for those involved to better understand how supply chains are managed under the new demand management model. For example, making sure demand and supply data are not confusing, but, rather, integrated—working in lock-step to deliver value to consumers and customers. Finally, sales and marketing organizations will need a new way to source and organize information in order to feed into the new generation demand management model. The frequency and the way in which the company collects data will require changes, as well.

Like all change management, transitioning to the next generation demand management model while working in a volatile marketplace is a journey that requires time and does not happen overnight. Data and predictive analytics provide the insights and quantify the challenges a company is facing, but it is business leaders who see the bigger picture, realize the urgency and are not afraid to tackle changes, and the frequency of recurring common problems. So to make informed decisions on how to reorganize and resource the business will require leaders, not followers.

The myriad forces impacting the relationship between demand and supply are set to expand their influence. Finding ways to be better prepared means implementing a corporate culture and structure that brings together organizations, and most of all, data from different sources. The analytics and technology capability is now available, so organizational changes and skills must be the focus to transition to the next generation demand management. However, it will also require ongoing change management to not only gain adoption but sustainability that will eventually become the new corporate culture.