Given the complexity of receiving, assigning, tracking, reporting, invoicing and billing field service work using a blended workforce (gig, part-time, full-time, and other workers), an efficient and effective way is needed to selectively see and analyze the company’s projects, resources, assets, and open quotes for future work. A dashboard that gives management the ability to quickly make decisions, identify issues, and understand the effect of potential opportunities will be key. Operational elements like work-order analysis, worker productivity, contracted cost versus actual spending, resource availability, quality control and other important measures must be monitored in real-time to avoid negative impact on the company’s operations and business metrics. The project management system must be able to provide a way to visualize the status of the company’s projects, the workforce, pending/future work, resources and assets, as well as assess the issues and impact of things happening in society, the workforce, project locations, related areas of business, and government.
The integration, programmability, and automation of productivity analysis functions and reports is very important in a project management system for field service work using a gig-workforce. Any loss in time to assign, track, complete, and/or report on a project equates to increased cost, decreased profits, inefficient use of resources, and a loss in future opportunities. Also, the integration with data visualization tools like Microsoft Power BI, Tableau, Sisense, Chartio, Salesforce Einstein Analytics and SAP Analytics Cloud will allow management insight into key components of their business without reviewing raw numbers or complex reports.
We will call the ability to analyze and visualize a company’s business operations “business intelligence”. Wikipedia (https://en.wikipedia.org/wiki/Business_intelligence) defines business intelligence (BI) as follows: “comprises the strategies and technologies used by enterprises for the data analysis of business information.” BI technologies can take structured and unstructured data and provide insights into ongoing business operations. Most modern BI tools also provide data visualization capabilities. Data visualization is the ability to represent BI data in a human readable format. The ability to visualize data in a way that enables effective decision making is an important attribute of BI tools. Other functions provided by BI tools include reporting, analytics, data mining, business performance management, and predictive analytics. This list of functions and capabilities is applicable to the needs of our field services project management system.
We must recognize that every client and project is different. But field service projects, in fact projects in general, carry some common attributes. Therefore, some BI and visualization actions can be programmed to provide high-level operational insights, while others will be created for a specific project, client, or type of work. Management must establish what they would like to see in real-time at the corporate, client, project, project type, work-order and work-order type level. Decisions must be made on how management wishes to view the availability, workload, productivity, and attributes of the workforce. And the project management system must provide support for the different reports and views of interest, as well as making all possible elements programmable.
Now, while ultimate programmability of views and reports is valuable, the system must provide some standard reporting and visualization capabilities as part of its base functionality. From this base capability, the project management team can customize the system to deliver specific monitoring and decision-making insights.
The challenge for most project management systems, and their integration with BI tools, is dealing with the volume, variety and veracity of the data collected. Another challenge is handling real-time operations and concurrency in the data collection and processing. Finally, identification and notifying the user of anomalies and outliers in the data and/or resulting analysis will be important, helping the management team to avoid inaccurate and/or poor decisions.