Page 6 - NM811

SCloud Based GeoCall Analytics by Bluenet
ince May 2020, Bluenet has types of projects: This analysis aims centers can identify peak call hours, been actively engaged with to quantify the level of risk associated days, or seasons. This information helps 4 members (GA, TN, MS, with potential damage in various call centers anticipate high-demand
and AL) of P2 Progressive regions or project types. It involves periods and allocate staffing resources
Partnering Consortium to provide them considering factors like environmental accordingly, ensuring that customer
with a robust analytical capability to analyze their historical damage ticket data, which are records of physical
or operational damage to property, equipment, infrastructure, or other assets. The GeoCall Analytics platform built by Bluenet provides in-depth analysis against tens of millions of “historical” damage tickets created over the years. A few examples of analysis related to identifying and assessing potential damage or risks in certain areas or projects are described as the following. These examples revolve around risk assessment, damage prediction, and incident analysis.
• Identifying areas or types of projects with a higher likelihood of causing damage: This analysis involves studying historical data and factors associated with projects to determine which areas or types of projects are more likely
to lead to damage. By identifying the historical patterns and correlations, 811 centers can proactively allocate resources or take precautions to minimize potential harm.
• Assessing the risk level of damage in different regions or for different
conditions, project specifications, and historical incident data to determine the likelihood and severity of damage occurring.
• Identifying geographical areas with a higher likelihood of damaging incidents: This analysis involves geospatial mapping and data visualization to identify specific geographical areas that have experienced a higher frequency of damaging incidents. By understanding these hotspots, 811 centers can focus
on targeted interventions or safety measures to mitigate potential damage.
• Analyzing seasonality of the incidents: This analysis examines patterns related to specific times of the year or days when damaging incidents are more likely to occur. By studying seasonality, 811 centers can anticipate when risks are higher and allocate resources or adjust project schedules accordingly to minimize potential damage.
• Trending and Time-Based Ticket Analysis for Call Center Staffing: This analysis involves studying trends in call volume and ticket submissions over time. By analyzing historical data, 811
service remains efficient and responsive.
• Analyzing Responsiveness to Damaged Tickets: This analysis
focuses on evaluating how quickly
and effectively damaged tickets are addressed and resolved. By tracking the time it takes to respond and resolve these tickets, 811 centers can ensure timely customer service and identify potential bottlenecks or areas.
In all these scenarios, data analysis and performance metrics, such as damage ratios (%), emergency ticket volume, response timeliness, etc. play a crucial role in damage prevention activities. By leveraging data-driven insights provided by GeoCall Analytics platform, 811 call centers can optimize their operations, enhance member satisfaction, and
make informed decisions about staffing, resource allocation, and process improvements.
The GeoCall Analytics platform is a shared cloud-based platform dedicated to the participating 811 Call Centers on an annually subscribed SaaS model. Inspired by Progressive Partnering’s (P2) GeoCall Software development efforts, this complimentary add-on
4 • West Virginia 811 2023, Issue 4