Finding an Optimal Distribution Network Strategy without Betting the Business
31 Oct, 2012By: Tom Tiede
One of the more complex business problems supply chain leaders face is providing the answer to the questions:
• “How many distribution facilities should we have?”
• “What capabilities should they provide?”
• “Where should they be?”
Offering an answer to these questions is especially difficult when confronted with the perpetual need to increase service levels, reduce operating costs and rationalize capital investments.
Infrequently are the answers derived from a mathematical equation. Instead, designing an optimal distribution network strategy for the business is a delicate balance of art, science and compromise.
The art is in defining feasible distribution network scenarios that cost-effectively support the planned goals for the business. The scenarios must be practical, implementable, allow for future flexibility and create a competitive advantage for the organization.
No surprise, the greater the complexity of the network (e.g., multi-channel and/or multi-node distribution) and the more uncertain the future, the greater the need for creative thinking when deriving feasible scenarios to evaluate. This also requires challenging the status quo. To achieve and sustain competitive advantage, the strategy must be forward-thinking, distinctive and seek to exploit new or anticipated opportunities in the market.
The science is in conducting the cost vs. service tradeoff of all of the feasible scenarios. This is typically performed through optimization software analysis which calculates the theoretical costs (i.e., freight, warehousing, inventory and taxes) to serve customer demand within defined geographic areas. Among the many assumptions in the analysis are the locations of the facilities being evaluated.
Often, the analysis is based on theoretical geographic locations rather than actual sites. Hence, facility location is one of the two primary areas where a compromise decision is often made when designing a distribution network.
The gap in cost and service between an actual site location and the theoretical location assumed in an optimization analysis can be wide. Software-driven optimization analysis is incapable of evaluating all of the factors associated with location and site selection.
For example, key factors in site selection include:
• Preference to buy or build to suit
• Availability of suitable facilities in the preferred geographic radius
• Proximity to strategic customers
• Availability and makeup of the local labor pool (e.g., education, wage rates, union influence)
• Access to highway arteries and freight carriers
• Negotiated lease rates
• State and local incentives.
So, site selection inevitably leads to a compromise on cost or service.
But perhaps the biggest compromise organizations make when designing their distribution network is in regard to managing risk. Distribution network design and implementation can be a “bet the business” proposition — the bigger the change, the higher the bet.
The propensity and bandwidth for change in every organization is unique to its culture. To be successful in any significant redesign of the network requires a bit of a “gambler’s streak” among executive leadership as well as a full commitment of dedicated resources who will tightly manage the implementation and the risk associated with change.
Organizations that have the combination of abundant, skilled project resources and executives who are willing to make “bet the business” and potentially “bet the career” decisions are very rare. Therefore, compromises are almost always made to control risk, balance resource constraints and effectively manage change, which often results in incremental changes made to the network over time rather than a potentially more beneficial but riskier strategy.
Does this lead to a sub-optimal distribution network? Not necessarily. Optimal is not the same as ideal. Ideal is an elusive and unrealistic target. An optimal strategy means finding the best balance across all meaningful criteria. Optimal goes beyond algorithmic analysis.
Ultimately, an optimal strategy is not only cost-effective and service-friendly, it is also forward-thinking, broad in view, easy to articulate, distinctive in the market, balanced in approach, accommodates growth, allows flexibility, mitigates risk and, very important, has the steadfast commitment of key leaders and stakeholders.
Certainly, defining and executing an optimal distribution network strategy is a daunting challenge. But it’s a challenge every distribution-intensive business must accept to succeed.