Field Force Analytics-The Growth Potion for your Delivery Business
With technology steadily driving business operations, the previously cautious managers are now starting to transition towards digitization. Businesses are in a race, and the ones who constantly adapt to the environment will win. In order to win this race, it is necessary to match the productivity and efficiency to the ones that are using analytical metrics to form all operational and sales related decisions. This shift is one of the major reasons why business managers now are making decisions on the basis of past data and figures.
“Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.” - Geoffrey Moore
In a service industry; especially the ones constantly dealing with field force, it is essential to maintain the quality of service. In fact, the RoI of a business depends on how efficiently they reduce the consumer waiting time and how good the quality of their service actuality is. For a delivery business, this would mean timely orders by using GPS based tracking and automation of assignment of orders to different workforce.
The quality of service hence translates to more work and similarly, a delayed service or a service that is not up to the mark would mean less business in the future.
Optimum Utilization of Data
In a field force management industry, the multiplicity of order and service deliveries leads to heaps of data being generated by the management platform. This data is generated by different metrics and arises from the orders supplied in the past. The plethora of opportunities this data can offer to the business is slowly being realized. Data from previous services provides an opportunity to be implemented in the future. Additionally, this data can be used to optimize the service delivery for further orders, this further translates to the use of the data for future orders.
The study recently published by Aberdeen, a Harte-Hanks Company states the importance of business intelligence and data analytics technology to enable better and faster decisions.
This data, being easily available on the platform, can be converted to useful insights leading to informed and data-driven business decisions. Hence, it becomes important for managers to invest their time in order to channelize this data into metrics which will help in improving their productivity in the future.
Why Predictive Analysis?
With so much focus on workforce management, we are aware that the quality of service offered by the workforce is the one thing that can make or break your business, hence it is necessary to form decisions relating to the workforce with utmost precaution. The efficiency in business can hence be brought in by a clear focus on analytics and data generated and collected in the past.
The importance gained by predictive analysis can be understood by the following figures - 89% of marketers in the B2B industry plan to employ predictive analysis into their business, the study also states that of the managers employing these analytics into their business 90% are said to be 1.8 times more likely to achieve their organisational goal and 2.9 times more likely to see a growth in their revenue.
Predictive Analysis would mean analysis of the future conditions on the basis of past figures. This analysis is necessary to bridge the gap between the consumer needs and the solution that the company offers. It would mean that the company can prepare itself for future circumstances in the present. This, in turn, will help the managers to form different contingency plans or change their strategies on the basis of future predictions. All this would bring a little certainty to the chaotic environment business lives in.
The conclusion is simple, in order to not lose in this race against other businesses, it is important to consistently and rapidly adapt one’s organizations to the current needs, using analytics in the business is one such requirement which cannot be surpassed.