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Accenture

To forge new competitive advantage, many service businesses must upgrade theirtraditional, commodity-like service capabilities.

Today, the concept that the service business can be the profit engine for product manufacturers and resellers looking to achieve high performance is not new or even particularly insightful.

Many companies, such as Caterpillar and General Electric, have understood this premise for decades – and they have driven their bottom line with service profits. Others, such as Dell and Home Depot, have recently scaled up their service capabilities to capture profit while simultaneously growing their top line.

In either scenario, it’s apparent across industries that the service business offers the next great frontier for established companies to retain customers, increase their margins and improve business performance. But complications arise when old-world, “big iron” OEMs – those comfortable with competing in the capital-intensive world of engineering, manufacturing and distribution – attempt to compete in the sometimes ethereal and intangible world of service.

Furthermore, the service vision described above is not the basic set of point-of-entry capabilities that businesses have employed for years – for example, call centers, repair services, warranty programs and the like. Accenture’s vision of service is a model where complex capabilities – which are very hard to replicate – are strategically selected to provide a competitive advantage to a company, leading to increased customer retention, premium pricing and market expansion. Companies can implement these innovative service capabilities to help them achieve high performance:

• Integrated supply/demand planning (ISDP) for service;
• Service demand management;
• Profitable contract management;
• Service order promising and execution;
• Scientific service-parts management; and
• Product design for serviceability.

Integrated Supply/Demand Planning

Product manufacturers long ago discovered the value of integrated supply/demand planning, also known as sales and operations planning (S&OP). But for myriad reasons, S&OP – the process of using decision-support tools, cross-functional teams and organizationspanning metrics to balance supply and demand – has had trouble crossing over into the service world.

Essentially, integrated supply/demand planning is the mechanism by which the service business aligns labor and material resources to meet service demand. Figure 1 shows the ISDP conceptual model and its primary components. An enabler of this model is often called “intelligent dispatch,” because the business has the ability to dispatch the technician with the right “parts and smarts” based on a priori knowledge of the equipment configuration, asset history and potential fixes. This is a complex capability to implement, in that technical and process integration must be achieved across functions that are traditionally in silos, such as materials management, field service and engineering.

Accenture teamed with a cellular services provider that adopted the integrated service resource management philosophy and termed it N&OP, or network and operations planning. The purpose of its network and operations planning program was to bridge annual business planning – conducted twice per year – and weekly, tactical planning and scheduling. N&OP meetings were held in the third week of each month and were attended by three primary groups: demand, supply and customer teams. Demand teams were led by program managers and staffed with forecasters; supply teams were led by network engineers and staffed with inventory and fulfillment planners; and customer account managers led customer teams.

Service Demand Management

Service companies face multiple types of demand streams from customers. As a result, the business must discretely identify these varying demand profiles, quantify and translate the nature of these demands and create customized marketing and logistics responses that best meet them. For example, customer-service demand (submitted via call centers, websites, walk-in service centers, automated equipment, maintenance schedules, etc.) can be classified in a variety of ways: proactive, reactive, planned, routine, emergency, unit-down and so on. Any field service manager will tell you a typical ratio is 80 percent reactive (unplanned) to 20 percent planned calls. Figure 2 shows the daily historical demand split between planned and unplanned service for a commercial restaurant equipment repair service. This data provides evidence of the 80-20 ratio.

Companies should therefore be aware of a few critical implications for managing such a high degree of operational uncertainty:

• To meet demand, the business must carry surge capacity in the form of extra technicians, materials, vehicles and other assets, which at times may appear unproductive.
• To support tight execution, capabilities such as labor scheduling, dynamic dispatch and parts issuance become highly critical.
• To maintain operational flexibility and connectivity, advanced planning capabilities that attempt to freeze resources, develop finite plans and conduct scenario analysis become less important.

An excellent example of service demand management in action is a large commercial airline carrier that analyzed several years’ worth of maintenance job records to improve staffing of aircraft maintenance technicians and storeroom inventory levels. From tens of thousands of complex maintenance events, it developed a simple demand classification scheme.

Based on this analysis, the airline modified its job tracking systems, aircraft maintenance technician procedures and documentation. Additionally, the airline analyzed job-card data and developed correlative forecasting models; it also reset safety stocks and reordered quantities as demand became more predictable. Since the critical path for a specific aircraft was stabilized and became more deterministic, this new demand management approach improved performance by decreasing cycle times for heavy maintenance visits. Furthermore, the initiative significantly reduced the return flow of unused parts back to the storeroom after heavy maintenance visits were completed.

Profitable Contract Management

Selling contracts is a dual-edged sword for a service business. On one hand, it can be the biggest driver of profitability and customer retention when managed successfully. On the other hand, ineffective contract management will quickly drive away customers and result in unprofitable accounts. To effectively offer contracts, Accenture has determined that a service business must successfully manage each of these five steps:

• Sell and Market Contracts – The business must conduct buyervalue analysis; develop new contract offerings; and retool the marketing and sales departments to push these offerings to customers using consistent, fact-based approaches. Value propositions – once historically product-centric – must be recast to focus on service and outsourcing benefits, such as asset optimization, guaranteed service levels and reduced operating risk.
• Plan Contracts – Once the offerings are developed, the operations department must quantify the labor, capacity and material requirements to support the contracts, as well as acquire new capabilities and resources to execute the contracts. This process primarily includes determining labor and materials requirements to support contract commitments.
• Price Contracts – The operations analysis should directly drive the cost modeling of the contract product. From there, the business can develop price strategies based on margin targets, customer account strategies and competitor offerings. Pricing should be reviewed regularly for each account, such that current financial performance influences future contract pricing before unfavorable economics become locked in.
• Execute Contracts – Contract execution must be supported by formality of process: formal operating procedures, formal metrics and formal communication channels. Only then can the service business have confidence that execution will support commitments. For example, if a service-level agreement (SLA) is estimated to be breached, the business must have an escalation, or “jeopardy routing” capability to redirect resources and support the SLA before it’s breached.
• Conduct Post-Sale Analysis – This analysis must be conducted to track the profitability of contracts. Often, a company underestimates the complexities, and thus costs, of being a solutions provider – and account profitability may decrease. If this happens, the business needs to immediately address the root cause and take actions, such as adjust prices, reduce costs and assets and/or collaborate with the customer.

These activities are intensely data-driven and use market research, customer-buyer value analysis and operating and financial data. We teamed with a mining equipment OEM to incorporate this five-step framework and determined that it was consistently failing to execute its maintenance and repair service contracts. The SLAs in the uptime guarantees were not being met, costing the dealer network (and ultimately, the OEM) millions of dollars in customer penalties.

The uptime agreements in the mining company’s contracts were very complex. Contracts often covered hundreds of vehicles that were geographically dispersed across dealer zones and operating under varying environmental applications. As a result, it was common for an emergency service call technician to arrive at a dealer that he alone could not fulfill. In these cases, the lead time to mobilize resources across dealers produced a response that did not meet the SLA. In Accenture’s five-step framework, the “plan contracts” phase had not been given due diligence. A detailed requirements analysis justified new capability investments, such as GPS-based schedule and dispatch, an online technician skills database and an online cross-dealer parts locator.

The business case for these investments was justified on multiple dimensions. First, the initiative increased direct labor productivity (both chargeable and expense) due to optimized routing and scheduling. Second, it captured profit from incremental parts sales as a result of increased availability across dealer zones when responding to emergency calls. Third, both dealers and the OEM were able to avoid the significant customer penalties that had been occurring due to breached SLAs.

Service Order Promising and Execution

We’ve all probably endured this experience – waiting around for the cable guy who promises to show up sometime between 8 a.m. and 8 p.m. for your installation. This level of responsiveness is now viewed as unacceptable, and in recent years, we have seen the cable guy narrow his promising window to a marginally better four hours. But imagine a capability that allows customers to access a personalized website, create and submit a same-day service request and select and confirm a one-hour time-banded appointment from a list of multiple appointment options. Meanwhile, an optimization system has selected – and if necessary, dynamically redirected – via mobile device the most-skilled and lowest-cost service technician to this new call, while also delivering driving directions, equipment data, repair procedures and billing information to the technician. Additionally, a backfill technician has been automatically dispatched for the redirected technician. The technician is armed with a “ruggedized” wireless laptop enabling him or her to quote prices, plan future service calls and order parts at the customer location. Accenture is currently working with an 800-dealer equipment reseller network to deploy this capability in the U.S. across 48 states. The contrast of this vision with our cable guy scenario and the impact it would have on reducing customer churn and increasing technician utilization is quite dramatic.

Scientific Service-Parts Management

Managing service-parts inventories requires capabilities above and beyond what is considered adequate for production inventories. Applying traditional forecasting, planning and procurement capabilities that are well-suited for stable, dependent demand inventories is not sufficient. In fact, it’s Accenture’s experience that more than 90 percent of all service-parts organizations lack the “scientific” tools needed to optimize their inventories. These advanced capabilities include the following:

Deployment Strategies for Stochastic Inventories

Our modeling has shown it is not uncommon that 50 percent of service-part SKUs for a business may exhibit stochastic (random) demand patterns, making forecast-based safety stocks not only impractical, but also dangerous to apply. This percentage dramatically increases for end-of-life spares programs. New probabilistic techniques to determine target stock levels are required, which may not be available even in advanced service-parts planning applications. In these cases, reliance on a time-series forecast to derive monthly safety stock values for stochastic parts is an exercise in futility; a typical result is that too much inventory is held, as the forecasting system confuses a random demand pattern as an increasing demand trend.

Multi-Echelon Optimization

One characteristic of a typical service network is its distributed, fragmented structure. Master-stocking depots, field hubs, customer proximity depots and van stocks can all drive the number of stocking locations into the hundreds. In these cases, the cost of applying true optimization technologies is warranted. Advanced optimization tools are able to determine the optimal stocking quantity for each SKU, where carrying costs are exactly balanced by stock-out costs, which can then be dynamically re-optimized as demand and supply changes.

Service Target Optimization

The sales department or management typically mandates service targets, such as a 95 percent unit availability rate. In other words, there may be little science in determining the optimal service target for a SKU, customer or customer segment. But companies that use empirical data, such as stock-out costs, account profitability and inventory carrying costs, can ensure that the customized service levels they are delivering to customers are warranted based on financial and strategic benefits. The business can then roll this analysis up into an aggregate cost-service modeling tool to conduct “what-if” analysis on different service and inventory scenarios.

By applying a more “scientific” approach to inventory management, Accenture helped an aircraft engine OEM reduce aftermarket and spares inventories by more than 25 percent in just 12 months, while holding service constant and supporting increasing sales. Accenture teamed with the OEM to achieve these results by implementing several new and innovative programs. First, statistical modeling was conducted to isolate stochastic demand parts that cannot be forecasted using time-series approaches. For these parts (many of them slow movers), we applied new forecasting and safety stock algorithms. Second, we developed a new replenishment strategy that customized lot-sizing techniques based on the supplyand- demand characteristics of inventory segments. Third, we implemented new metrics at different levels in the business. To support tactical execution, we developed statistically valid exception criteria to quickly identify SKU outliers during weekly planning cycles. Finally, to support strategic exectuion, we developed a comprehensive scorecard for each engine line that measured each line's combined cost-service performance and then provided detail on specific cost and service issues.

The project yielded a SKU-specific reduction plan that identified $12 million in excess inventory that could be consumed over a six-month period, without harming service levels or incurring additional purchases. The total reduction potential was estimated at more than $50 million, and inventory turnover improvement was estimated to be 3.2 times. In the first month, the pilot program produced $1 million in deferred spend as the planners modified their reorder behavior.

Product Design for Serviceability

In Accenture’s experience, one of the most untapped improvement opportunities is product design for serviceability. For a host of process and organizational reasons, critical insights about product performance from the field force is never shared with development engineers back up the value chain. However, it makes perfect sense to do so – the technicians who service the installed base every day would have the experience to act as in-house focus groups to fine-tune designs. In fact, these technicians should be able to provide insights that would improve a number of design dimensions for serviceable equipment: materials of construction, component placement, configuration changes due to life cycle requirements, packaging, user documentation, ease of installation and so on.

To implement this capability, the new product process for the business should be modified to incorporate feedback from service personnel prior to functional design and prototype development. In fact, if the business uses a tool such as quality function deployment to identify and incorporate customer requirements into product designs, then service personnel should be assigned as one of the customer groups in that tool.

To leverage this knowledge in both directions, Accenture teamed with a global heavy equipment OEM to build a service diagnostic database that captured more than 140 data points for each field service event. The results were compiled and made available online, then shared both with design engineers and technicians as a knowledgeenhancement tool. Database tools summarized and generated conclusions across hundreds of service events. Engineers used it to fine-tune their designs before they became locked, and technicians used it for real-time troubleshooting. The OEM estimates this simple data sharing shaved 1.5 percent off total warranty costs due to decreased premature product failures.

The Path Forward

This capability list is by no means exhaustive, and not every service business should attempt to adopt all of these capabilities. On the contrary, we’re suggesting that a business should select the few critical capabilities that are required to execute their own business strategy – and pursue these capabilities vigorously to improve business performance. In other words, service executives should carefully focus their business strategy and ruthlessly deploy the operating model to help their businesses achieve high performance.