Many companies are realizing that relying on their products and attractive pricing models to appeal to consumers is no longer sufficient. With the rapidly shifting digital transformation leading to disruption in nearly all business sectors, companies hoping to survive and thrive need to set themselves apart. The best-in-class have realized that improving the customer experience is a key factor. And one of the most effective ways to satisfy customers is to excel in field services. 86% of best-in-class companies have turned to predictive analysis to achieve this goal.
Companies already using predictive analysis to improve the customer experience have witnessed steady annual improvements in numerous areas including performance, revenue and costs. However, the main impetus for making the transition is a pressing need to offer customers something more than the competition. Predictive technology offers improvement in uptime and the prevention of lost assets due to unexpected system failures. This is a strong draw for customers looking for the next best thing when it comes to field services.
However, installing predictive analysis tools is only the first step. Without effective data management, there is little to be gained from this technology, which relies on the collection and analysis of massive amounts of information across different systems. Here are some strategic steps for managing this data:
Integrate all available customer data
Companies using predictive analysis are 33% more likely to integrate all their available data. This includes but is not limited to customer data, product information, product/customer history. By having all this data in one central location, it becomes possible to analyze trends and potential bottlenecks in order to ensure the seamless provision of services and increase first-time-fix rates.
Data access for technicians
When field service technicians arrive for a job with all the information available, they are better equipped to successfully perform the task at hand and find a quick solution.
Standardized customer data capture and management
Companies implementing predictive analysis are 39% more likely to have systems in place to standardize the capturing and management of customer data like: customer reliance on self-service tools, communications with service representatives across different communication channels, previous field service visits. With different systems in place for grabbing and storing data in various formats, it is essential that all this data be uniformly readable and accessible.
Consolidating all accumulated knowledge – for example articles, tutorials, manuals, case studies – in one centrally accessible location makes it possible for technicians to quickly and easily locate helpful information for solving field service issues.
Companies that have already realized the necessity for data management when using predictive technology are also more likely to rely on external tools to ensure that all of the abovementioned steps are addressed. For example:
- 89% of companies using predictive analysis are more likely to depend on data quality and integration tools to make data from different sources and in different formats uniform.
- 69% of companies using predictive analysis take advantage of the exhaustive amounts of available data to integrate automated billing management systems that rely on amassed information about past field services to predict pricing. This means that bills can be sent to clients almost simultaneously.
- Many companies are now also turning to predictive technology powered partner relationship management. By coalescing data from partners, technicians and service providers, a better view of customer needs and desires emerges.
Predictive analysis offers the potential to redefine how companies interact with customers. However, when optimally utilized, it can transform the entire field services sector. And this is exactly how best-in-class companies are setting themselves apart from the competition.
Aberdeen, CEM Executive's Agenda 2017: A Data-Driven Approach To Delight Customers, February 2017
Aberdeen, Use Predictive Analytics To Drive Field Service Excellence, June 2017