Service Lifecycle Management (SLM): The New Competitive Frontier Part 1 Setting the Stage Whitepaper by: Michael R. Blumberg, CMC President Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 0
Table of Contents The SLM Opportunity 3 Tech Trial & Error 5 The Answer: Systemic Optimization 8 Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 1
Service Lifecycle Management (SLM) is the profit-driven optimization of the system of processes employed by durable goods manufacturers and their service network partners to ensure products perform as promised after the sale. In every manufacturing segment today, the competitive battleground is changing dramatically. Customers will be won or lost and financial targets will be hit or missed based on the efficiency and quality of service delivery. What s driving this shift towards service-based value creation? A number of factors, including the following: Increased global competition has squeezed product-driven margins. Trying economic times have trimmed capital budgets, forcing companies to extend the usable lives of existing capital equipment. Equipment buyers are increasingly demanding total outcome-oriented business solutions comprised of products, services, and performance commitments. In anticipation of and response to this shift, leading OEMs have begun to organize and optimize the various service business processes under the umbrella of SLM in much the same way as they ve done in the past in areas like Supply Chain Management and Product Lifecycle Management. These processes include the following: Call Management Warranty Entitlement Help Desk/Technical Support Remote Diagnostics Field Dispatch Dynamic Scheduling Spare Parts Management Mobile Communications Knowledge & Content Management Returns Management Depot Repair Reporting & Analytics To aid in these SLM optimization efforts, these companies have invested in enterprise technology solutions. But despite major advancements in and deployments of service-related technologies, there is a general sense that these investments have not produced the level of benefits that were promised by the vendor. For example, research over the period of 2001 to 2009 shows failure rates associated with Customer Relationship Management (CRM) deployments have been as high as 70% and are currently hovering at 50%. According to a 2010 market study, nearly two-thirds (63%) of respondents surveyed indicated that their ERP implementations have failed to realize the benefits that were anticipated. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 2
The SLM Opportunity These statistics are closely aligned with real world experiences within the SLM market. We recently surveyed 250 end-users to determine their level of satisfaction with their existing systems in managing critical operational and financial performance metrics. Our findings revealed a 40% to 50% level of satisfaction. This lukewarm response is due, in large part, to the disjointed nature of the business processes and technologies that govern today s service and support environments. The primary pains encountered by service executives tend to revolve around the following issues: Balancing resources to maximize both customer satisfaction and service business profitability in a rapidly changing market environment. Controlling the allocation and scheduling of individual resources, in both the long-term and real-time. Operating under business rules and models designed for a product environment. (Figure 1) Figure 1 PAIN POINT INABILITY TO MANAGE OR CONTROL SERVICE BUSINESS ON DAY-TO-DAY BASIS LABOR COSTS TOO HIGH AND SERVICE PERSONNEL INEFFECTIVELY DEPLOYED LOGISTICS & INVENTORY COSTS TOO HIGH OR INEFFICIENTLY USED LACK OF REAL-TIME CONTROL OVER FIELD PEOPLE & PARTS SPECIFIC CUSTOMER OR CUSTOMER SEGMENTS NOT SATISFIED WITH SERVICES FIELD SERVICE NOT OPTIMIZED LOGISTICS NOT OPTIMIZED INABILITY TO CONTROL AND MANAGE BUSINESS STRATEGICALLY SYMPTOM ATTEMPT TO RUN AS A PRODUCT BUSINESS ON A DECENTRALIZED BASIS LITTLE OR NO ACCURACY ON TIMELY DATA SERVICE PERSONNEL OVERWORKED SERVICE PERSONNEL UNDERWORKED CONSTANTLY BUYING NEW PARTS PARTS NOT AT RIGHT PLACE AT RIGHT TIME CUSTOMER DISSATISFACTION SLOWNESS IN RESPONSE TO CUSTOMER REQUIREMENTS IN FIELD NO COMPLIANCE OF PORTFOLIO WITH DIFFERENT DELIVERY LEVELS AT DIFFERENT PRICES FIRST COME, FIRST SERVED PROCESSES LOW PROFITABILITY AND/OR CUSTOMER SATISFACTION LOW PROFITABILITY AND/OR CUSTOMER SATISFACTION LOW MARGINS LOW CUSTOMER SATISFACTION LOW REVENUE GROWTH MORALE ISSUES Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 3
Unaddressed, these pains worsen in the context of the full service lifecycle. Figure 2 depicts the typical process flows involved in service delivery and how common challenges are exacerbated by the process fragmentation that typifies the service value chain. Figure 2: The Issue Without an integrated, lifecycle view of service, OEMs incur unnecessary costs, miss revenue opportunities, and risk customer attrition. Pain: Pricing managers are not aware that spare part price cut requires 20% increase in inventory to meet gross profit target. Stock-out occurs, gross profit goal missed. Pain: Pricing managers lock in spare part price for next two quarters, unaware that excess inventory of end-oflife part is bloating the balance sheet. Pain: Repair depot diagnostic technician only has access to As-Designed BOM; cannot access As-Maintained BOM for asset-specific service guidance. Repair yields and turn-around-times suffer. Pain: Part planners over-estimate repair yield rates, under-purchase new parts, and miss contracted service level. Pain: Field technician replaces part and adds it to growing stockpile of defective FRUs in trunk stock, triggering unnecessary new spare part purchases, and eroding service margins. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 4
Technology Trial & Error Respondents to our survey reported that they use a number of different types of solutions to automate and optimize service business processes (Figure 3). The survey results reveal that no single category of enterprise system dominates the SLM market. Levels of satisfaction with these systems deteriorate further due to the fact that most systems have evolved over time and are comprised of disparate and often antiquated systems. Figure 3 Types of Systems Companies Use to Manage Service Operations Enterprise Resource Planning (ERP) 41% Customer Relationship Management (CRM) 26% Field Service Management System (FSMS) 17% Supply Chain Management (SCM) 22% Enterprise Returns Management (ERM) 11% Enterprise Reverse Logistics Management 9% Warranty Management System 26% Warehouse Management System 36% Customized Specifically for Reverse Logistics 44% Other 10% Survey based on a poll of 250 professionals representing OEMs, Retailers, Carriers and other 3PRL organizations. Source: Blumberg Advisory Group The need for service optimization is particularly critical in organizations that operate Service & Support as a profit center or strategic line of business. In these cases, the objective is finding the best solution that meets various and often conflicting objectives associated with profitability, return on assets, customer satisfaction, and market share. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 5
As the example in Figure 4 shows, there are multiple ways a company can pursue profitability goals, but only one strategy the Optimum Solution will produce the maximum pay-off. In many instances, there may be restrictions preventing a company from achieving the optimum solution, in which case the optimal solution is preferred. Figure 4 General Examination of Alternative Strategic Solutions Source: D. F. Blumberg Associates, Inc. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 6
In the context of SLM, consider the trade-offs involved in trying to achieve the optimum solution for both response time measured in terms of an Average Response Time Index and profitability (Figure 5). While there are multiple strategies this company can pursue, only one is optimum for profitability (strategy D) and only one for response time (strategy H). Assuming the company was to pursue the optimum solution for the profit objective, it would result in negative consequences with respect to the response time objective and vice versa. As a result, neither strategy (D or H) can be pursued. The best choice is to find and select the strategy that produces an optimal pay-off for both objectives which is strategy E in this case. The optimization paradigm becomes even more complex when one considers the vast array of performance objectives and trade-offs in the SLM environment. Figure 5 The Service Management Problem: Optimization of Two or More Functions Source: D. F. Blumberg Associates, Inc. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 7
The Answer: Systemic Optimization Optimization produces superior results for a specific process when viewed individually or on a stand-alone basis. However, there are interdependencies among services processes. Since optimization technologies are typically designed for a single process, they do not account for these interdependencies. As a result, the service organization experiences sub-optimal results. This is true even if optimization is available throughout the entire service lifecycle and greatly magnified if optimization is lacking in a specific area. The Solution A contiguous technology and service process backbone that empowers service executives to run post-sales service as a profitable line of business. Solution: Pricing managers are automatically prevented from making spare part price cuts that require more than 15% increase in inventory to meet gross profit target. Gross profit goal ACHIEVED. Solution: Pricing managers authorize aggressive spare part price cuts, to liquidate excess inventory of end-of-life parts, keeping working capital requirements low. Solution: Field technician replaces part and delivers defective FRU to repair depot, maximizing use of repairables, and bolstering service margins. Solution: Repair depot diagnostic technician can access As-Maintained BOM for asset-specific service guidance. Repair yields and turn-around-times improve. Solution: Part planners have real-time visibility into current repair yield rates, optimize mix of new & repaired parts in stocking plan, and contracted service levels are exceeded. Common scenarios where a company may have optimization in one area but lacks in another: Company achieves a high on-site response time but the SLA compliance rate is low due to parts shortages caused by poor planning & forecasting and/or parts management. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 8
Parts Availability and Response Times are high but First Time Fix Rate is low due to a lack of knowledge management tools. Return Velocity Rate is high but so are the Warranty Claims Rejection Rates due to lack of poor Warranty Management capabilities. Parts Forecasts are accurate but parts income levels are low due to poor Parts Pricing capabilities. Rapid repair turnaround time (TAT) but high DOA rates due to lack of quality controls on the shop-floor. The list of scenarios identified above could continue ad infinitum as a result of the complex array of processes, resources, and information involved in Service Lifecycle Management. These trades-offs all have an impact on productivity, quality, and efficiency. Here s a practical example of how inter-process integration can leverage data obtained from each stage of the service operation to achieve optimal performance from the perspective of risk and financial returns. 1. In the initial stages of the service resolution process, critical information about the equipment condition is obtained in the CRM to determine: a. if the product is covered under warranty b. the nature of the problem 2. Once the problem is identified, the service provider will use Knowledge Management tools and go through a diagnostics process to determine if the unit can be resolved remotely or if the product needs to be returned. 3. The data on the equipment condition is then used to process a Returns Authorization. The RA will identify where the product should be returned, who should be responsible for return, and how it will be returned. 4. The data on the Return Authorization ticket is also leveraged by the work Order Management system to determine what should be done with the product once returned (i.e., repair, replace, destroy, etc.). 5. The data on the RA about the condition of the product will also help facilitate the test & repair process. 6. The results of Step 5 will determine which parts to use and where to send the product once it has been repaired. 7. Critical data obtained up to this point about the symptom, cause, and corrective action is updated in the Knowledge Management system so that the front-end diagnostics process can be more efficient in the future. 8. Meanwhile, all the data captured at every stage of the process is used to update and maintain various plans and forecasts the company has made regarding parts availability, inventory stocking levels, pricing, staffing, purchasing, etc. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 9
About the Author Michael R. Blumberg is a Certified Management Consultant (CMC) and President & CEO of Blumberg Advisory Group, Inc. His firm focuses on providing strategic and tactical assistance for improving the overall profitability and quality of aftermarket service operations. Mr. Blumberg has established himself as an expert and industry authority on Reverse Logistics and Closed Loop Supply Chain Management. Service Lifecycle Management (SLM): The New Competitive Frontier, Part 1 Setting the Stage 10