Global companies are changing their operating models to meet increasingly complex demands on their businesses. Too often companies struggle with how to effectively adapt their demand planning operations as these models evolve. If not done right, it can lead to unclear and inaccurate forecasting, ultimately putting the long-term viability of the business at risk.

The fundamental approach to demand planning needs to change. There is no “one-size-fits-all” approach. Different operating models require different processes. Whether it’s a global operating model leading by regions or a country-led model, both are favored by a number of major consumer goods companies. A “hybrid” model of demand planning is required to achieve the most effective process and desired outcome. Some industries, such as consumer goods, are recognizing the importance of such a model and are beginning to adapt it, while others want to take the leap now.

The Evolving Landscape
Consumer products businesses have initiated their demand and supply planning from the country of operations for many years. This worked well because local insight into immediate competitors’ behavior, customers’ needs, and consumer preferences sharpened planning. With brands becoming regional, supply chains were quick to follow. However, demand planning was still typically a local process controlled by the local general managers. It was common for the local leadership team to manipulate the forecast, and then submit it to regional management, which would also manipulate the numbers. Therefore, forecasts would be manipulated multiple times before the global business leaders first saw them. As a result, the demand planning process became flawed, and required a complete overhaul across the industry.

Adding to the complexity of this transition is the increase in regional diversity witnessed over the last 10 years, where a wide divergence in growth and prosperity has prompted the division of regions. This is well demonstrated in Europe in the last five years or so. Once viewed as homogeneous, there are now at least two tiers with differing products required, for example, in Spain versus the United Kingdom. “Poverty is returning to Europe. If a consumer in Spain only spends €17 when they go shopping, then I’m not going to be able to sell them washing powder for half of their budget,” says Jan Zijderveld, Head of European Business at Unilever.

Importance of Demand Planning
Demand planning is an essential process in determining how much product a business will sell to satisfy all customer demands. It typically involves completing eight steps in a monthly cycle (see Figure 1).

The process begins with a review of the recent customer sales performance compared with earlier expectations and assumptions, and a cleanup of any data issues or outliers that are believed to be one-off events. These data are used to generate a baseline statistical forecast. Planners will discuss, with marketing and sales, and incorporate the latest market intelligence gained from the five C’s:

1. Customers
2. Consumers
3. Competition
4. Consumption
5. Cannibalization

Planners also consider changes in company plans, such as promotions, advertising, sampling, new products, or pricing. They determine with the help of statistical tools if any of these will impact the forecast of future demand.

Once they make a forecast, they review it in light of known category trends, run rates, and competitor information among other measures. Then they work with the finance team to value the forecast. The resulting unbiased forecast is presented in the Demand Review meeting. In this meeting, cross-functional S&OP members challenge the forecast with intelligence on the trends, assumptions, key indicators (accuracy and bias), and the potential up- and downside risks. The goal is to arrive at a consensus forecast. This number may require some post-meeting reconciliations by the demand planning team before the final agreement is made. When businesses were managed locally, this process could be entirely completed by local teams. Once demand planning has moved to regional or global business models, how can the teams keep close to the local trends, insights, and shifts?

Overcoming the Local and Regional Roadblocks
So how can the demand planning process evolve to use local market intelligence while working with regional brand and supply teams? A hybrid model allows for a number of significant benefits. Local teams are able to better observe, record, and share customer, consumer, and competitive insights, and feed them to a regional demand planning team. The planners then work directly with the regional brand and supply chain teams to develop production plans. Building the hybrid model requires additional steps to collect the local market insight and review the forecast as well as to change plans when necessary.

To do it objectively, the key activities of the planning process must be reviewed to decide if responsibility of forecasting, planning, or both should lie at the local or regional level, as there is often repetition of labor. The decision is often made easier by testing each activity by responding to these questions:

• Where will the operation be most efficient? It may be too costly to have full planning and forecasting operations both locally and regionally. The regional group may be able to leverage specialist forecasting resources, such as statisticians and insight groups.
• Who has better local market insights?
• Can we use most effectively our scarce expertise if all the countries within a region work together?
• Can regional planning take into account the consensus forecasts of each country in a region?
• Is it possible to standardize the planning of each country?

In essence, you must first separate regional and local processes by disaggregating activities into smaller tasks and “units of responsibility,” and assigning them directly to either the local or regional team (see Figure 2). This is not always possible, but where activities must be shared, both regional and local teams need to know that they must collaborate. To this end, the process needs to adapt and build in reviews to align all parties with the final objective.

In this new hybrid “collaborative” process, there is a new dimension, and therefore extra steps. Regional demand planning teams can provide the baseline statistical forecasts using their expertise and the IT Systems (Develop Forecast), but then they will need to work with the regional marketing teams (Marketing Review) as well as the local market demand planners and local management teams (Country Review) to prepare for a management meeting where a consensus on the demand plan can be obtained (Demand Review). This aligned demand plan can then feed into the S&OP process (see Figure 3).

The following six skills are what the team must have to improve forecasts, and make the regional process effective:

1. The ability to comprehend the overall business, and a clear understanding of how the business operations and processes are to be linked. For that, close local, regional, and global collaboration among Sales, Marketing, Finance, and Supply Chain is needed.
2. The ability to integrate business planning between localities and regions for Sales, Marketing and Finance.
3. The expertise in statistics and experience in understanding which numbers can influence planning. The best forecasting departments can, for example, distinguish between trends and one-off occurrences, and correlation and causation.
4. The skill in system and reporting, which is crucial. The focus is always on significant variances with high quality reporting of findings to decision makers. This requires understanding of which data will be important to which stakeholders. Linking and updating such data is important so that anything out of tolerance is noticed and explained quickly, if needed.
5. The skill of analysis and communication is needed, particularly for scenario-based planning. There should always be a Plan B in case an unexpected scenario materializes. Communication around this also needs to focus on identifying options and making recommendations to address any issues.
6. The quality of leadership, which is absolutely essential. While this may seem a statement of the obvious, leaders must be able to foster agreement among the regional and local planning influencers. Without agreement, good planning may never come into effect.

Strong IT should underpin all demand planning. A regional, rather than local, demand planning structure simplifies and speeds implementation, and makes it cheaper by requiring considerably fewer licenses as the total members of the regional demand planning team (regional plus local resources) is likely to be always lower than the sum of all local planners in a local planning model.

Providing Clarity in a Complex Business World
As the world changes, flexible structures are required to ensure there is minimal disruption to the information flow of businesses. The flexibility that is necessary would be in terms of the ability to change processes, to shift organization structures, to adapt information systems and key measures, and to enable the teams to balance and coordinate workload. In the consumer goods industry, some brands are local, regional, or global.

Some customers, or retailers, are also local, regional, or global. Therefore, it is no surprise the consumer goods companies have responded by creating matrix-like structures. And as companies change these dimensions even faster (note Unilever's desire, at least in Europe, to divest “local jewels,” meaning local brands), flexibility is the only way to survive. We believe a regional structure gives many advantages to multi-national corporations. If implemented properly, it enables flexibility, maximizes the company-wide benefits of expensive expertise and systems, and gathers relevant and timely intelligence. The hard reality is that global companies must adapt their approach to demand planning operations to provide as much visibility on their forecasts as possible amidst ever-complex financial backdrop.

Richard Loretto is a Senior Director with Alvarez & Marsal in London.

This article originally appeared in the Summer 2014 issue of the Journal of Business Forecasting.

Re-published with permission.