If in the past you interviewed any great business leader about what it took to build a great business, they would probably have pointed to three (3) basic elements:
- People – Comprised of all layers of personnel, from C-suite executives to the warehouse clerks, who bring vision, creativity, leadership, and passion to bringing products and service to market, and pleasing customers.
- Process – The structured and disciplined series of actions, steps, and procedures personnel must complete to perform the work of the company. These processes are only as good the people who design, manage, and perform them.
- Technology – Systemic infrastructure that automates processes, tracks and controls transactions, and reports on the company’s operational and financial performance.
This statement is no longer complete to model modern day businesses, especially those involved in service. Why not? The statement doesn’t include the most crucial elements of managing a service business; data.
Data enables service companies to forecast and anticipate when, where, and how often service will be required. This in turn enables the provider to ramp up or scale down service resources (e.g., people, parts) based on demand patterns. In addition, it provides service providers with the business intelligence they need to guarantee specific levels of service to their customers. Furthermore, data forms the basis of a service company’s research and development efforts. By examining trends and patterns in the data, a service company can identify opportunities to help their customers in new and better ways. More importantly, data allows a service company to optimize (i.e., make the highest and best use of) service resources, improve service productivity, maximize efficiency, and enhance the customer experience.
Typically, when service businesses face financial troubles it is because they do not appreciate the importance of data to their business. Without the ability to utilize data to manage service capability, service quality (i.e., performance) suffers, customers become dissatisfied and eventually leave. In addition, service providers miss the opportunity to offer high margin, value-added services to their customers, such as 4-hour response time, remote telephone resolution, or overnight delivery of spare parts.
Data becomes ever more important as we consider one of the most significant trends impacting the Technology Industry, “Servitization”. This trend describes the transformation that many companies are undertaking as they move from primarily selling products to generating a sizable portion of revenue and profits from services. Ultimately, the path toward Servitization leads companies toward offering anything as a service (XaaS).
To deliver on this outcome in the high-tech industry (e.g., copiers), the provider of the XaaS solution must ensure the machine is available and running at optimal performance when the customer needs to use it. Otherwise, the provider cannot deliver on its promise. Neither the provider nor customer can afford extended periods of equipment downtime, or else they lose money since their revenue is tied to outcomes. This means the provider must be able to anticipate problems before they occur and avoid them, or quickly mitigate or resolve them once they do occur. With this data in hand, the provider can ensure resources are available when needed and that the customer receives the outcome it purchased.
Given the crucial aspect of data to managing a field service business, it is no wonder that Artificial Intelligence (AI) is becoming so popular in Field Service. These tools enable service providers to quickly and efficiency analyze large pools of data to diagnose, anticipate, and predict service events. Data, leveraged by AI, provides field service companies with the unique X-factor they need to achieve achieve exponential growth, exceed customer requirements, and maximize financial returns.
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