ServicePower Field Service Optimization Software

Strategic Planning and Decision Making in Field Service Organizations
By
Michael R. Blumberg

The problems associated with strategic planning and decision making for an OEM or product-centric field service operation are relatively straight forward. Typically, the operating budget for a field service organization that is run in support of manufactured products is set by the marketing organization based upon a percentage or allocation of the planned sales revenue for the coming year. By dividing the number of service engineers from the previous year into the operating budget, it is possible to come up with a simple estimate of "budget per service man" parameter. This factor, divided into the new, approved operating budget, tends to define the staff levels to be established for the coming year. A similar averaging or ratio analysis is utilized to establish the logistics budget.

However, with the growth in service, both in industry and the market, and increasing competition and the emergence of multivendor, services-led organizations, the service executive and manager are now faced with a much more complex strategic planning and decision making process that requires a full analytical examination of the trade-offs between service levels to be offered, measured in terms of response time, customer down time, and the cost and/or price of service to be delivered. This must be evaluated in terms of alternative staffing and logistics support levels. The framework in which a service executive is required to make these strategic choices is increasingly based upon an optimization of both revenues and profitability; the ultimate objective is generally measured in terms of a trade-off between service profitability and revenue levels compared to customer service satisfaction levels.

In essence, it is essential for service executives and managers to shift from business planning based on static or subjective estimating and averaging methods at an estimated or given budget level to a careful and considered dynamic, analytical investigation of both customer service levels and cost and price levels under alternative staffing and support budgets. Usually, and typically, the service goals and cost/price goals are in conflict; service can be improved with increased costs and price, or price/costs can be reduced at the expense of the level or standard of service offered. This complex equation is made even more difficult if one needs to consider market segmentation, in which different market segments are willing to pay different amounts to achieve a given level of service. This requires the development of an optimized service portfolio and service pricing by market segment, trading off service performance and response against the cost or price of service as a function of customer requirements for service and customer willingness to pay on the one hand and operating costs and expected service performance on the other.

Thus, as we move into more competitive and complex service environments, the field service executive and manager, and his/her staff, must take into account a much more complex array of factors and parameters to determine the optimum strategic plan and balance. This involves an explicit consideration of:

The service portfolio mix and market segments to be served at a given price target
The level of service (measured in terms of response time, customer down time, and accessibility) as a function of the customer service requirements
The impact and allocation of territories and regions, as well as product density, on given service levels and portfolio mix of specific customer segments or groups
Determination of the optimum service force staff levels and spare parts inventory allocation strategy to optimize the tradeoff between service/customer satisfaction levels and service portfolio cost and price

In this situation, the "back of the envelope" or subjective planning based upon "rules of thumb" or hit and miss methods are no longer a satisfactory solution. The service executive and manager and staff must carefully consider the complex tradeoffs involved, as well as the integration of more than 25 to 30 variables, parameters, and confidence estimation levels, to calculate the optimum solution.

Since a commitment to a given service personnel staff level and budget tends to be difficult to change in relatively short timeframes (for example, in less than two to three months), inaccuracies in the calculation of strategic choice or mistakes in allocations and assignment of service force and logistics support levels can be very costly in terms of both financial consideration and economics, credibility, and ultimately, market share, operating from having too much or too little service capacity. Our experience suggests that differences in planning and decision-choice methods could lead to a difference in service revenue and/or profitability of 25-50% or more in a single year. There is also a need to examine and evaluate alternative scenarios, to provide the answer to the general question: “What would happen if some change were made?,” and to examine the sensitivity service performance measures and costs of various alternative scenarios at both the strategic and tactical levels.

Finally, as service organizations increasingly commit to and make investments in enterprise service management systems to manage day-to-day call handling and dispatch and logistic support, we find that a tremendous amount of data and parameters that have previously been "locked up" in manual or handwritten reports are now becoming increasingly accessible through an organized, accurate, and quantitative digital database. In particular, the typical field enterprise service management systems and point solutions on the market today can generate considerable detailed information concerning the installed product and customer base, mean time to respond, mean time to repair, mean time between failures, logistics fill rate by location (at the field service engineer trunk or site level, at the local regional depot, and at the central depot), and finally on service requirements and needs. This new robust data, properly organized and evaluated, can substantially improve the accuracy and strategic impact on both revenue and profitability of service planning alternatives.

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Michael R. Blumberg, CMC, an authority on marketing research/strategy formulation in the high-technology service market, is president of D.F. Blumberg & Associates, Inc, a Fort Washington, PA based management consulting firm that provides client services in strategic planning, market research, productivity improvement, and management systems design and implementation. You may reach him at michaelb@dfba.com or (215) 643-9060.