Service Matters from MCA Solutions

Traditional Supplier collaboration is transaction-based.  As the article "Enabling Collaboration," in Aviation Week describes, supplier collaboration in its basic form is a valuable tool for communicating orders and forecasts to suppliers and receiving a commitment, shipment notification or exception back from the supplier.  However in the aftermarket supply chain space, are traditional collaboration tools sufficient to meet the unique challenges of collaborative planning in this environment which is much more challenging than finished good production planning?

What are the critical attributes of collaboration platform for the aftermarket supply chain? 
Some of the challenging characteristics of the service supply chain to be addressed by a prime service provider and its suppliers include: demanding contracts with performance-based service level commitments, large numbers of parts with intermittent demand driven by unpredictable product failures, and global supply networks that must be highly responsive to restore product uptime. 

In response to the needs of key aftermarket service leaders, MCA has developed a process and next generation platform for customer collaboration that addresses these challenges.  Here are some key elements of a successful aftermarket collaboration framework:

• Shared incentives:  Aftermarket service contracts may specify a demanding customer-focused metric such as part fill rate, response time to repair, or equipment uptime.   If the prime's supplier has incentives for performance that are aligned with the objectives of both the prime service provider and the end customer, it is possible to create a "win-win" outcome where the supply chain moves towards an optimal solution.
• Secure information sharing: Information to enable advanced collaboration goes beyond orders and shipments and must include detailed product information such as failure rate observed in the field, supersession data, , customer forecast and causal data  that can help achieve mutual objectives.  Maintaining security and partitioning data to the appropriate suppliers is critical to a successful relationship.
• Coordinated decision making:  When each supplier optimizes its sub-set of the supply chain in isolation there are material flow and information lags which lead to a "bullwhip effect" across the supply chain.  To help alleviate this, the prime supplier must coordinate optimization across all of the suppliers and allocate metrics, appropriate service levels, and planning priorities through a global view of the supply chain and with the end customer objectives in mind.
• Supplier asset ownership:   The trend of Performance Based Logistics contracts has been to shift ownership away from the end customer and closer to the service provider and, by extension, onto its suppliers.  Determining who should own what level of inventory and providing the appropriate information to facilitate effective management of this is a critical decision that requires cooperation and trust.
• Closed loop performance management:  Appropriate performance metrics that monitor compliance to the contract terms are required across the extended supply chain.  The mechanism not only to monitor exceptions to performance, but to act upon and correct them on a real time basis, must be tightly integrated with the planning process.

Going from "combative" to "super collaboration" requires more than a "transaction-focused" collaborative IT tool.  MCA's planning and collaboration solution includes a consistent set of models to support planning, allocation, and execution decisions.   This platform allows sharing of information that includes the product structure and location hierarchy; and coordinated decision making across a complex network in different planning horizons, ranging from long term strategic and medium term tactical to short term event planning.

To ensure success, the collaborative process and platform must share risks and rewards across all of the parties to create a "win-win," with clearly defined outcomes for performance with a long-term view that generates an atmosphere of trust among all of the parties.

Managers in the service business deal with a much different environment than those in the production world.  Extended global networks, difficult to forecast intermittent demand, and very large volumes of parts for products in all stages of the product lifecycle make it difficult to effectively manage the service supply chain.  With inventory turns which can range from 1 to 5 in the service supply chain, versus much higher turns in the production supply chain, CFOs often ask why performance isn't better. 

The problem is that it's hard to find a fair point of comparison.

Service supply chain benchmarking studies from Deloitte, Bearing Point, Aberdeen, Wharton School of Business, and ServiceEdge consulting show a wide range of performance, not only of companies within one study, but the average performance benchmarked from one study to the other.  For example, the Wharton study conducted in showed that high tech companies with an enterprise business (the Wharton study was the only one that segmented results based on they type of business) had from 1.3 to 2 turns, while the Aberdeen study showed that high tech companies averaged 4.6 turns per year.

The reality is, benchmarking in isolation provides a basic guideline, but it doesn't help when it comes to identifying specific improvements for your business. 

Performance is driven by a wide range of characteristics specific to the service business which include:

• Varied service offerings (e.g. 4-hour response, next day, advanced exchange)
• Supported products with varying lifecycles, product complexity and failure rates
• Different supply chain configurations and supplier lead times

To really understand the optimal level of service performance, you have to analyze and model the specific characteristics of your business, and determine which parameters can be tweaked and what tradeoffs can be made to achieve business objectives.  A tool like MCA's Service Business Design allows companies to compare the cost and budget impact of business scenarios such as:

• Changes to physical supply chain configuration
• Design and pricing of service product
• Warranty and contract service-level offerings
• Assignment and realignment of customers to service contracts
• Lead time and cost trade-offs for new buy or repair
• Budget analysis of bid and proposal scenarios
• Product introduction and end-of-life

So, benchmarking has some use as a guideline, but its important to do deeper analysis to understand the dynamics of your own business.  By performing analysis specific to your business you can understand both the optimal levels of inventory and service delivery given your current environment, as well as which changes to business parameters should be made to reach the next level of performance.