Astrologers and science-fiction writers have entirely lost their professional exclusivity with big data coming into action enabling anyone to predict the future backed by statistically analyzed complex data, that too in a matter of seconds. The key to the future lies in the past and the present has to connect the dots to make the time travel journey successful. Astonishingly, this entire process is reduced down to an operational duration of just a few minutes with advanced predictive analytics tools.
Field Service, in particular, is a goldmine of data from GPS and location to client details which had always been lying dormant inside company servers but are now, gradually, being channeled for greater purposes. Predictive analytics has become so important in field service because customers are, blatantly, expecting companies to understand their needs and customize their offerings before them expressing it. Companies can no more merely sell products and services and have to shift their focus to selling experiences to make a huge impact on the results.
These are the major impact points of predictive analytics in the field service sector:
Forecasting demand for products and services can support enterprises in better inventory management and help in calculating the number of staff required to meet a certain objective.
Although enterprises are still slow in adopting modern methods of pricing and still rely on the traditional ones, times have changed with predictive analytics making the pricing process much more accurate and flexible to various internal and external factors.
Superior performance strongly relies on actionable information which is why predicting KPIs has become so important for enterprises. The ability of predictive analytics to measure, monitor and react to KPIs becomes imperative in formulating both short-term and long-term strategies.
- Operational efficiency
Task scheduling and route optimization becomes much more efficient especially with a heavy reduction in unnoticed slack using the multifunctional aspects of predictive analytics.
Preventative maintenance becomes much more sensemaking with predictive analytics supporting accurate planning using historical data about when a part is likely to fail.
Although there are abundant benefits of using Predictive Analytics not just in field services but in any domain, however, we cannot shy away from the risks that it brings along with it. For Predictive Analytics to properly work, there should be a huge volume of relevant data sets from a wide range of activities and even with the availability of such heavy data sets, algorithms can fail in anticipating human behavior which in itself is full of complexities. If we bring time into the frame, it makes things even more completed. The analytics design might be successful at one point of time but it might falter with changes in variables with respect to time.
However, modern predictive analytics tools have managed to rise beyond the risks and have hit a very high accuracy mark in making analytical predictions. Especially in field services, the algorithms have been modified to adapt to the changes in location-based data and customer insights considering time intervals as well. Such level of accuracy becomes imperative in shaping how historical data is used in making business level and functional strategies for the organization.
Predictive Analytics platforms have started to become extremely prominent since 2017 with modern technology giving a push to business intelligence platforms supporting predictive analytics. Enterprises in the field service industry can look at platforms like Tookan and Kato to take a dive into predictive analytics and transform how they carry out their business.
Tookan is a robust one-stop shop for all the field service management problems. Its analytical prowess gives you a glimpse of the future. Tookan diagnoses and understands the business with the help of its data mining and analytical functions helping to make business intelligent decisions to thrive in this volatile industry.
Kato is a fully equipped analytical platform which has a wide range of analytical offerings from data preparation, analytics dashboard to predictive insights. It acts as an AI and predictive analytics tool by offering plug and play ML algorithms that solve specific use cases for your business model.
With predictive analytics supporting functional activities at every step, enterprises can, literally, visualize a better future and make business intelligent decisions based on historical data defining patterns of activities and behavior.