Creating Visibility Throughout the Service Chain

Leading manufacturing and capital equipment firms are now "playing offense" and engaging with their customers in a truly interactive fashion. Customer dashboards, key performance indicators (KPIs), and customized reports have long been available to internal account teams. Now, however, leading edge organizations are making these same tools and data available to their suppliers and customers through business portals with aggregated information from multiple enterprise and transactional data systems. Internal service personnel, service-chain partners, and customer personnel can all now see the same view of service performance and activity. This new interactivity, which is the next frontier of business intelligence (BI), can generate not only internal efficiency but also create opportunities for real customer "stickiness" and business growth.

Account management teams that are armed with metrics, reports and analyses populated from cross-department sources, processes, and databases can have more immediate impact. By definition, the team's information is richer, providing for a better customer experience and easier identification of growth opportunities.

As an example, consider the experience of a multi-billion-dollar OEM of laboratory analytical equipment. The OEM recently formulated cross-functional account teams for its strategic customers and is proactively evaluating how to empower these teams with a reporting and dashboard solution that leverages data from multiple sources. The solution would likely include installed equipment utilization data, service revenue data, service delivery and call center performance data, service supply-chain spare parts and consumable data, and customer survey/satisfaction scoring. This information currently resides in at least three disparate systems.

A reporting solution must provide the ability to investigate and analyze (that is "slice and dice") the data across multiple business hierarchies (regions, segments, customers, product lines, fiscal periods). Anticipated benefits to customer-facing teams and account managers are numerous, and include the ability to:

• Quickly determine how well the most strategic and largest revenue sites are being serviced
• Map actual service delivery performance to perceived customer satisfaction
• Access actual equipment utilization and analyze it against contract terms and design intent
• Proactively monitor equipment usage and synchronize this information with inventory and services supply-chain orders and partners. This opens the opportunity to offer an outsourced material procurement service
• Drive better customer integration by providing direct access and views of the data and reports

The ability to associate intelligent machine data and remote diagnostics with other service-relevant data is perhaps the best example of the power of aggregated data and context. The above example of linking equipment usage (measured by cycles, hours, samples, etc.) to supply-chain and service contract fulfillment is just one of many envisioned scenarios. Many have wondered why remote diagnostic-enabled equipment technology, as compelling as it appears in theory, has not become ubiquitous. One explanation might be that this rich machine information largely sits alone and is not connected to other transactional and execution data elements within the service and product enterprises. Aggregating this data with other service ecosystem data in a business intelligence framework that account teams, service personnel, and customers can access, will clearly help to facilitate the intelligent machine vision.

In addition, most organizations clearly understand the need to prioritize and segment their accounts to properly stratify service offerings, align appropriate resources, and drive growth initiatives. The opportunity to visualize the customer's perceived perception (Loyalty Index) against actual service delivery performance (Operational Index) provides a very powerful capability. Loyalty Index -- now very topical as a result of the highly promoted and deployed Net Promoter Score (NPS) -- is really a proxy for whatever means an organization is using to calibrate and measure their customers' opinions of them (NPS metrics, surveys, focus groups, and so forth).

But how do organizations measure and capture a true "Operational Index," or readiness to serve indicator? To be effective, one would argue that this metric should be multi-dimensional and encompass data from cross-department processes and multiple customer "touch-points." Service metrics that comprise this score might include overall equipment utilization (OEE), MTBF, first-time fix rates, on-time delivery performance, service-event resolution times, call center performance, service supply-chain order-fill-rates, warranty compliance, and invoice accuracy, among other metrics. The challenge is in efficiently aggregating the data that is required to develop this composite score. Unfortunately, most manufacturers forego this strategic mapping simply because of the effort required to mine and assemble this data. Others conduct arduous and sporadic manual exercises to create this view, but it is not scalable or systemic, and consequently, it has been used very infrequently.

Further, account teams interested in growing their accounts and expanding their relationship from commodity supplier to strategic service partner understand the critical need to understand their customers' total-cost-of-ownership and key success factors. To do this properly, the service provider perspective needs to morph. Metrics that are tracked and monitored on customer dashboards need to reflect the real impact on a customer's business and processes. For example, instead of measuring classic repair depot turn-around-time (TAT) from shop induction to shipment from the depot, a service provider might calculate end-to-end TAT as the time measured from unit shipment from the customer facility until the time it was received back at the customer facility for re-installation (dock-to-dock). Additionally, customer-dashboard related metrics should be mutually defined with your customers and include process variation as well as average indicators.

While the above discussion may be intriguing, the execution is in the details. Data integration and visibility from multiple sources -- omnipresent in a service environment with "best-of-breed" transactional and execution tool proliferation -- is a key success factor. Extended service-chain access to data must be seamless and part of the account team's rhythm of execution. It is imperative that a reporting and analytics solution be deployed that can:

• Be easily accessed and used both internally and externally
• Leverage data from multiple departments and source systems
• Provide the ability to slice and dice data across business dimensions and down to transactional levels

The importance of a robust business intelligence/analytics solution within the service organization is critical and further validated by the Aberdeen Research Study (Aberdeen Group, November 2007, "Get Smart: Business Intelligence for Service Organizations") highlighting that nearly 80% of service executives either have in place or plan within the next twelve months to implement a business intelligence /analytics solution for their service operations. The good news is that today it is easier than ever before to leverage technology to conduct analytics and reporting. A growing number of on-demand business intelligence solutions, are less expensive than previous generations of tools, and can be now operational within weeks instead of months.

Here's to taking your customers to the next level of success!

Steve Morandi is the vice president of manufacturing solutions of Oco, Inc., a Software-as-a-Service (SaaS) provider of business intelligence and data integration solutions. http://www.oco-inc.com/