| GISdevelopment.net ---> GITA 2001 ---> Mobile Solutions - Taking it to the Streets |
Harnessing Data from Field Personnel for Competitive Advantage
Pierre Leroux
MDSI Mobile Data Solutions Inc.
10271 Shellbridge Way, Richmond, BC, Canada, V6X 2W8
Pierre Leroux
MDSI Mobile Data Solutions Inc.
10271 Shellbridge Way, Richmond, BC, Canada, V6X 2W8
1. Abstract
Workforce Management (WFM) systems generate a tremendous amount of valuable information. Both in terms of work results collected from the field force and measurements of workforce activities captured throughout the work process. This paper examines how business intelligence capabilities as a fundamental element of WFM ensures everyone in the enterprise—from senior executives to dispatchers—get the right information at the right time in the right format for decision-making. The objective of this paper is to:
Companies are confronted on a daily basis with the difficult task of optimally assigning customer-initiated work requests to their workforces, dispatching the work to the field, managing the progress of the workforce against the workload, and responding to changing conditions. The efficient use of resources is a critical factor when the workforce represents a significant portion of the organization’s investment.
The enterprise workforce management framework solves these problems by delivering an integrated, operations-centric view of the mobile workforce and its workload. It increases business effectiveness by promoting operational efficiency in individual operating areas while taking advantage of opportunities to manage work across departmental boundaries. The result is:
Scheduling
Scheduling is the efficient assignment of planned work to the best available resources. It determines the staff that should perform given jobs in a defined order at specified times on specific days. Scheduling ensures that technicians are where they are supposed to be with the proper equipment at the right time, thus eliminating multiple visits and improving customer service. Scheduling works within the bounds of workforce availability and defined workload to optimize the assignment of work according to modifiable optimization criteria based on client business goals and in response to resource and work order status changes in real-time.
Scheduling includes the ability to book appointments based on the appointment criteria (e.g., time, location and job type), organizational work practices (e.g., offered appointment windows) and the availability of resources in that location, at that time, with the appropriate skill set. Scheduling also includes the ability to assign orders to technicians. The assignment engine matches the business unit, priority, location, job type, appointment time (or early start/late finish window), and duration of orders with the business unit, location, available time, skills and equipment of resources. Different rules can also be defined to handle specific scenarios such as storm condition.
Resource Management
Effective resource management means that the planned workforce is appropriate for the anticipated workload and is the most efficient resource allocation within the constraints of company policies and union rules. Resource management is a pre-requisite for efficient assignment of work to workforce—the work assignment process cannot effectively assign work if the scheduled workforce is a poor match for the workload. Resource management not only provides the framework for minimizing overtime and meeting appointments, it also identifies resource under utilization. This creates the opportunity to perform more work or reduce the resource profile within the bounds of organizational work practices. This is particularly important consideration for contractor workforces.
The resource management process involves allocating technicians and equipment to work areas and shifts based on historical workload (e.g., what happened last year), planned workload (e.g., building a new subdivision), and expected but unpredictable events (e.g., a bad storm). Resource management defines, plans, controls and tracks the technicians and crews that perform work and their attributes that affect work assignment. It addresses the long-term allocation of resources to locations, crews and shifts, the short-term adjustment of resource allocation to address unexpected conditions such as sickness and unplanned work, and the real-time tracking of resource status and location.
Order Management
Orders management cooperates with enterprise applications such as Customer Information System (CIS) create, manipulate, control and complete work. Order management automates the work order life cycle from the time the service orders are released from the CIS until they are completed by technicians. It provides technicians with timely access to all the information they need to complete work right the first time. It collects accurate and timely work results from the field. It provides stakeholders in the order process (e.g., technicians, call takers, managers, customers) with real-time information on service order requirements and work results.
Order management provides a platform for viewing and manipulating work spanning the entire enterprise. In combination with resource management and scheduling this represents a tremendous opportunity to more effectively manage work. It separates work orders attributes that affect assignment and control of the work from those that are instructions to technicians responsible for performing the work.
Dispatch Management
Dispatch management is the real-time monitoring of the work force as it processes work requests. Timely feedback of work status and work results minimizes end-of-day effort, increases the accuracy of the information, informs dispatchers of work progress, and alerts them to unusual circumstances requiring attention. When the work force is ahead of schedule, timely feedback provides a means to make the necessary adjustment to offer more service appointments to customers. Likewise if the work force falls behind schedule, the adjustment of appointment offerings, overtime, and/or changing the sequence of the load is necessary to meet customer expectations and cost constraints.
Dispatch management delivers both a macro view of the progress of work across the organization as well as a detailed view of the status of individual work orders. It is real-time status information on technician activities and order status drives workload balancing. Unusual or high priority events requiring special handling (e.g., emergencies) are dealt with expeditiously.
Time Reporting
Time reporting is the tracking and adjustment of employee time information for export to enterprise applications such as payroll and billing. Time reporting is all about accountability. It is the basis for accountable work practices and billing. Tracking actual employee time stamps as work progresses encourages timely updates of technician status. Allowing audited adjustments of actual time stamps allows technicians to explain deviations from standard work practices (e.g., why it took longer than normal to travel to a job). Accurate and accountable time reporting is critical when performing billable work or when working with contractor workforces.
Operations Analysis
Operations analysis is the on-line tracking, monitoring and study of key business indicators to aid management decision-making. The goal of Operations Analysis is to increase the effectiveness of the decision-making and direction setting process related to workforce management. Operations Analysis allows companies to improve insights into trends in their operations and increase the accuracy of forecasts and plans.
Mobility Management
Mobility management is about eliminating the barrier between field resources and the corporate information they need to perform their work. It deals with the unique problems of operating remotely in a wireless environment. In addition to providing field workers with access to workforce management capabilities, it enables access to other corporate applications, manage connectivity to handle wireless constraints, and present an integrated mobile desktop for the field worker.
3. Delivering the Right Field Information at the Right Time for Decision-Making
In order to respond quickly to market opportunities and competitive pressures, organizations are moving toward knowledge that empowers people throughout the enterprise to make rapid front-line adjustments or long-term strategic corrections. This requires fast, easy access to the right information in the right format.
As businesses collect and maintain more and more operational data, extracting the “right field information” and presenting it in time for decision-making is a difficult task for most managers. For effective and efficient decision-making, managers need the assistance of decision support solutions. It is imperative to recognize that the spectrum of “information interaction” is very broad (See Figure 1), ranging from simple data access and status reporting, to data exploration and knowledge discovery, to advanced data interpretation and predictive business modeling. Therefore, a true end-to-end operational decision support solution provides the right business intelligence tools, the right interface, and the right access to data to address these user activities.
Figure 1 Spectrum of Information Interaction
Source: The Applied Technologies Group, 1999.
Purpose of a WFM Decision Support System
The main purpose of a WFM decision support system is to provide information to business users for decision-making. It should let knowledge workers access data in a manner that supports the "unique" way they approach their operations, but it should also meet the following business requirements:
Automate Data Collection—A WFM decision support system should automate the collection of workforce management data for reporting purposes. By automating the data collection, it eliminates inefficiency and wasted time involved in manually merging several data sources (paper or digital). The primary data source, the foundation of a WFM decision support solution, should be a normalized relational database.
Extract and Transform the Relevant Workforce Management Data—Relevant data should be extracted from the primary database, transformed and delivered to the target data mart at a specified time interval. The process creates a logical, multi-dimensional model of the target data mart, aggregates the data for this model in a single pass, and delivers it to the target data mart suited for enterprise reporting and trend analysis.
Supply a Set of Key Performance Indicators—KPIs are business measures that can be used to compare and contrast various dimensions to uncover the true drivers of the business. KPIs as dynamic business measures should enable multi-dimensional analysis and performance reporting through an On-Line Analytical Processing (OLAP) module and let users “slice and dice”, “drill down”, and view these KPIs in any combination they want.
Self-Service Information Access—The solution should serve as an easy self-service portal where KPIs should be instantly available in the right format for decision-making. Self-service information access should be provided to users on thin-client computers. This means that every user in the enterprise can turn to the solution as a way of managing and organizing the KPIs they wish to scan and view with single-click web access.
4. Decision Support System Architecture
A data mart is a collection of subject areas organized for decision support based on the needs of a given department. Finance has their data mart, marketing has theirs, operations has theirs and so on. The data mart is designed to suit and satisfy the needs of each department with very different objectives. This is why there are many different data marts in the corporation, each with its own distinctive look and feel. Data marts can be used as a stand-alone configuration or linked to an enterprise warehouse. A data mart is an essential component of any end-to-end decision support system and is often referred as the data storage element of the solution. A decision support solution encompasses several critical components, each of which is described in the following subsections.
Figure 2 Decision Support System Architecture
Field Data Collection
Many decisions within the utility industry are driven by data collected in the field. Field locations are often remote, so data must be transferred from the field to the front office. Timely decisions rely on data moving swiftly from the field to the office but speed is not the only criteria. Collecting quality field data in an efficient manner is of paramount importance because it often represents the only record of work done in the field and is the foundation of any decision support system.
The mobile computer and WFM application transform the way technicians process orders. Instead of receiving paper or voice-dispatched orders, technicians receive all of their orders through wireless data transmission to a mobile computer. Direct data entry from the field into a mobile computer improves data handling by removing the time-consuming and error-prone transcription phase. The use of laptop or hand-held computers in the field allows direct data entry into a digital format. The time spent by technicians filling out work is eliminated and there is no need for manual posting of paper documents. Data moves efficiently from the field to the office and into the WFM database.
Data sources are critical in that they provide access to the detailed information required for more routine user interaction with WFM data—such as status reporting. In addition, relational data plays an important role in performance traceability because it houses the details behind the trends discovered through exploration of the data. The WFM system should track the operational data (transactions and configuration information) generated throughout the workforce management process. The data sources should include the following types of data:
Before raw data can be stored in a data mart, it must be transformed and cleansed so it has consistent meaning. This transformation may involve restructuring, redefining, filtering, combining, recalculating, and summarizing data fields from different data sources. During the cube-building process, aggregates are automatically incorporated, dramatically reducing the time and resources required for ongoing aggregate table creation and maintenance in the relational database. In fact, cube updates can be scheduled to run automatically. Cubes can also be automatically updated with new information on an incremental basis, which saves valuable processing time.
Metadata is reusable information about data structures, objects, applications, and business rules in the data mart that is defined once and is centrally stored. This allows all tools and applications accessing the data mart to use a common set of conventions which greatly reduces maintenance and assists both users and information technology professionals in finding the information they need and understanding what it means. Data mart metadata is created by and updated from the load programs that move data into the data marts. Data mart metadata usually contains the following components:
As data is moved from various data sources into the data mart, it must be stored in a way that maximizes system flexibility, manageability, and overall accessibility. The answer: OLAP or On-Line Analytical Processing. OLAP data plays a key role in any successful data mart initiative because it is optimized to support “high-ROI” interaction with data—such as multi-dimensional analysis and business performance reporting.
OLAP data is presented in a way, which reflects multiple business dimensions such as work orders by quarter, by technician, or by business unit. This type of information allows managers to conduct effective comparison and trend analysis. Multi-dimensional data presents information within the context of business—not necessarily the way it is stored within the data source. Users have at their fingertips all the information they need to immediately conduct comparison and trend analysis. Furthermore, on the occasions when managers need detailed data —when summarized multi-dimensional analysis points to a specific trend that needs further investigation—they simply drill through to detail. This minimizes uncontrolled query traffic.
This model takes advantage of the ability to build OLAP cubes comprised of carefully selected "sweet spots" of information that have the highest impact on managers' decision-making. The provision of summarized data eliminates 80% of typical query activity, such as look-up or ad hoc queries. When managers drill through from OLAP data to actual transaction records, they query a relational database within this focused context. Drill-through access from cube to detail is pre-planned by the system administrator and limits access to rows and columns in the data mart, which ensures fast response times.
Analysis
This component provides a means to understand what is driving business performance. The analytic component must support sophisticated, autonomous end-user queries, rapid calculation of key business metrics, planning and forecasting functions, and what-if analysis on large data volumes. While the data mart storage component is read-only, the analytic solution must support multiple users simultaneously updating and recalculating information to enable “what-if ” and “what-next” modeling and planning applications. The OLAP server is the best technology for the analytic engine in the data mart.
When end-users access OLAP data, they are able to explore data mart information freely, in a manner that is simply not possible within the relational paradigm. For example, a business manager can quickly retrieve summarized data that highlights services orders by type of order by business unit. This data can then be dynamically explored. The business manager can drill down on the business unit dimension to review precisely which type of service orders within the business unit are problematic. Or, they may wish to slice and dice information by selecting an alternative business dimension—like total duration—to compare against type of orders and business unit.
Business Intelligence Reporting Tools
The robust reporting and analysis capabilities of business intelligence tools are the key to achieving maximum return on investment because they provide access to both OLAP and relational data sources. They address the different ways that people throughout the enterprise work with data to achieve results within their business context. OLAP Data Presentation and Access—An analytical reporting solution should allow powerful, interactive analysis. This means the ability to perform on-report drill, on-report pivot, on-report calculations, and direct report manipulation and formatting using a web browser. It should provide an easy-to-use interface that allows non-technical business people to be productive immediately.
Conventional Reporting Tools—Data query and reporting tools deliver data access through simple interfaces that hide the SQL language from end-users. These tools are designed for list-oriented queries, basic drill-down analysis, and report generation. Though they provide a view of simple historical data, these tools do not address the need for multi-dimensional reporting, analysis, modeling, and planning. They are also not capable of computing sophisticated metrics that users need to understand what is driving the business.
Self-Service Information Access
The decision support solution should serve as an easy self-service portal to reports, data in corporate databases, data on the Internet, and data in legacy systems. Self-service information access should be provided to existing users as well as new users, on thin-client computers. This means that every user in the enterprise can turn to the analytical reporting solution as their portal of choice to scan and view existing reports.
5. Key Performance Indicators
Key performance indicators are measures that can be used to compare and contrast various dimensions of the business. They are also used to gauge the operational performance of the organization. For example, the resource performance indicators can be used to compare actual and estimated duration of work orders for all technicians in a specific dispatch area. They could also be used to analyze work duration variance between dispatch areas. KPIs are made available through a ubiquitous web browser. This provides greater flexibility to organizations interested in distributing operational information across numerous business units. Immediate end-users are people involved in the management of the mobile workforce and its activities such as:
Resource Performance Indicators
Resource Productivity Indicator—The Resource Productivity Indicator compares and contrasts time measurements (Time En route, Time On site, Overall duration, Average Time, Variance, etc.).
Dispatch Efficiency Indicator—The Resource Dispatch Efficiency Indicator compares and contrasts the efficiency of all tasks initially dispatched to technicians or crews. A task is considered efficient if the initial dispatched technician or crew is the one completing it as well.
Work Quality Indicator—The Work Quality Indicator compares and contrasts the efficiency of all tasks initially dispatched to technicians or crews. If a repeated dispatch is reported within thirty days of prior completion, the task is flagged.
Overall Performance Indicators
Missed Commitments Indicator—The Missed Commitments Indicator compares and contrasts task measurements (tasks committed, completed, not completed, percent completed, percent missed commitment).
Overtime Indicator—The Overtime Indicator compares and contrasts overtime measurements (number of overtime hours required prior day, prior week, etc.).
Load Balance Indicator—The Load Balance Indicator compares and contrasts the number of hours to clear the workload for a given period of time in the past.
Root Cause Analysis Indicators
Overall Duration Indicator—The Overall Duration Indicator compares and contrasts time measurements from the time the customer notified the company to the actual completion of the work.
6. Conclusion
In an era of fast industry changes such as deregulation, privatization, mergers and acquisitions, utility companies recognize their competitiveness in the marketplace depends on accessing the critical information and leveraging it to maker better and faster decisions. Companies’ greatest challenge is transforming their WFM data into meaningful information to deliver the required knowledge in order to compete.
This challenge explains the shift from traditional reporting and query to the on-line tracking, monitoring and study of key performance indicators in a collaborative environment connected to the Internet and the interest in decision support system. A decision support solution that melds data mart, business intelligence, performance metrics, and the browser metaphor offers every manager the opportunity to get the right operational information at the right time in the right format. By tapping into the power of decision support, organizations implementing a decision support system can attain the following benefits:
Workforce Management (WFM) systems generate a tremendous amount of valuable information. Both in terms of work results collected from the field force and measurements of workforce activities captured throughout the work process. This paper examines how business intelligence capabilities as a fundamental element of WFM ensures everyone in the enterprise—from senior executives to dispatchers—get the right information at the right time in the right format for decision-making. The objective of this paper is to:
- Introduce the business value and capabilities of WFM (Section 2).
- Describe how a business intelligence solution can leverage and complement the field data collected by a WFM system. (Section 3 and 4).
- Outline several key performance indicators used for tactical adjustments or strategic corrections (Section 5).
- Present the key benefits of using a WFM decision support system (Section 6).
Companies are confronted on a daily basis with the difficult task of optimally assigning customer-initiated work requests to their workforces, dispatching the work to the field, managing the progress of the workforce against the workload, and responding to changing conditions. The efficient use of resources is a critical factor when the workforce represents a significant portion of the organization’s investment.
The enterprise workforce management framework solves these problems by delivering an integrated, operations-centric view of the mobile workforce and its workload. It increases business effectiveness by promoting operational efficiency in individual operating areas while taking advantage of opportunities to manage work across departmental boundaries. The result is:
- Optimal assignment of work to workforce
- On-line field access to enterprise data
- Real-time feedback on work progress
- Automated processes enforcing best practices
- Enterprise view of overall work status and workforce performance.
Scheduling
Scheduling is the efficient assignment of planned work to the best available resources. It determines the staff that should perform given jobs in a defined order at specified times on specific days. Scheduling ensures that technicians are where they are supposed to be with the proper equipment at the right time, thus eliminating multiple visits and improving customer service. Scheduling works within the bounds of workforce availability and defined workload to optimize the assignment of work according to modifiable optimization criteria based on client business goals and in response to resource and work order status changes in real-time.
Scheduling includes the ability to book appointments based on the appointment criteria (e.g., time, location and job type), organizational work practices (e.g., offered appointment windows) and the availability of resources in that location, at that time, with the appropriate skill set. Scheduling also includes the ability to assign orders to technicians. The assignment engine matches the business unit, priority, location, job type, appointment time (or early start/late finish window), and duration of orders with the business unit, location, available time, skills and equipment of resources. Different rules can also be defined to handle specific scenarios such as storm condition.
Resource Management
Effective resource management means that the planned workforce is appropriate for the anticipated workload and is the most efficient resource allocation within the constraints of company policies and union rules. Resource management is a pre-requisite for efficient assignment of work to workforce—the work assignment process cannot effectively assign work if the scheduled workforce is a poor match for the workload. Resource management not only provides the framework for minimizing overtime and meeting appointments, it also identifies resource under utilization. This creates the opportunity to perform more work or reduce the resource profile within the bounds of organizational work practices. This is particularly important consideration for contractor workforces.
The resource management process involves allocating technicians and equipment to work areas and shifts based on historical workload (e.g., what happened last year), planned workload (e.g., building a new subdivision), and expected but unpredictable events (e.g., a bad storm). Resource management defines, plans, controls and tracks the technicians and crews that perform work and their attributes that affect work assignment. It addresses the long-term allocation of resources to locations, crews and shifts, the short-term adjustment of resource allocation to address unexpected conditions such as sickness and unplanned work, and the real-time tracking of resource status and location.
Order Management
Orders management cooperates with enterprise applications such as Customer Information System (CIS) create, manipulate, control and complete work. Order management automates the work order life cycle from the time the service orders are released from the CIS until they are completed by technicians. It provides technicians with timely access to all the information they need to complete work right the first time. It collects accurate and timely work results from the field. It provides stakeholders in the order process (e.g., technicians, call takers, managers, customers) with real-time information on service order requirements and work results.
Order management provides a platform for viewing and manipulating work spanning the entire enterprise. In combination with resource management and scheduling this represents a tremendous opportunity to more effectively manage work. It separates work orders attributes that affect assignment and control of the work from those that are instructions to technicians responsible for performing the work.
Dispatch Management
Dispatch management is the real-time monitoring of the work force as it processes work requests. Timely feedback of work status and work results minimizes end-of-day effort, increases the accuracy of the information, informs dispatchers of work progress, and alerts them to unusual circumstances requiring attention. When the work force is ahead of schedule, timely feedback provides a means to make the necessary adjustment to offer more service appointments to customers. Likewise if the work force falls behind schedule, the adjustment of appointment offerings, overtime, and/or changing the sequence of the load is necessary to meet customer expectations and cost constraints.
Dispatch management delivers both a macro view of the progress of work across the organization as well as a detailed view of the status of individual work orders. It is real-time status information on technician activities and order status drives workload balancing. Unusual or high priority events requiring special handling (e.g., emergencies) are dealt with expeditiously.
Time Reporting
Time reporting is the tracking and adjustment of employee time information for export to enterprise applications such as payroll and billing. Time reporting is all about accountability. It is the basis for accountable work practices and billing. Tracking actual employee time stamps as work progresses encourages timely updates of technician status. Allowing audited adjustments of actual time stamps allows technicians to explain deviations from standard work practices (e.g., why it took longer than normal to travel to a job). Accurate and accountable time reporting is critical when performing billable work or when working with contractor workforces.
Operations Analysis
Operations analysis is the on-line tracking, monitoring and study of key business indicators to aid management decision-making. The goal of Operations Analysis is to increase the effectiveness of the decision-making and direction setting process related to workforce management. Operations Analysis allows companies to improve insights into trends in their operations and increase the accuracy of forecasts and plans.
Mobility Management
Mobility management is about eliminating the barrier between field resources and the corporate information they need to perform their work. It deals with the unique problems of operating remotely in a wireless environment. In addition to providing field workers with access to workforce management capabilities, it enables access to other corporate applications, manage connectivity to handle wireless constraints, and present an integrated mobile desktop for the field worker.
3. Delivering the Right Field Information at the Right Time for Decision-Making
In order to respond quickly to market opportunities and competitive pressures, organizations are moving toward knowledge that empowers people throughout the enterprise to make rapid front-line adjustments or long-term strategic corrections. This requires fast, easy access to the right information in the right format.
As businesses collect and maintain more and more operational data, extracting the “right field information” and presenting it in time for decision-making is a difficult task for most managers. For effective and efficient decision-making, managers need the assistance of decision support solutions. It is imperative to recognize that the spectrum of “information interaction” is very broad (See Figure 1), ranging from simple data access and status reporting, to data exploration and knowledge discovery, to advanced data interpretation and predictive business modeling. Therefore, a true end-to-end operational decision support solution provides the right business intelligence tools, the right interface, and the right access to data to address these user activities.
Figure 1 Spectrum of Information Interaction
Source: The Applied Technologies Group, 1999.
Purpose of a WFM Decision Support System
The main purpose of a WFM decision support system is to provide information to business users for decision-making. It should let knowledge workers access data in a manner that supports the "unique" way they approach their operations, but it should also meet the following business requirements:
Automate Data Collection—A WFM decision support system should automate the collection of workforce management data for reporting purposes. By automating the data collection, it eliminates inefficiency and wasted time involved in manually merging several data sources (paper or digital). The primary data source, the foundation of a WFM decision support solution, should be a normalized relational database.
Extract and Transform the Relevant Workforce Management Data—Relevant data should be extracted from the primary database, transformed and delivered to the target data mart at a specified time interval. The process creates a logical, multi-dimensional model of the target data mart, aggregates the data for this model in a single pass, and delivers it to the target data mart suited for enterprise reporting and trend analysis.
Supply a Set of Key Performance Indicators—KPIs are business measures that can be used to compare and contrast various dimensions to uncover the true drivers of the business. KPIs as dynamic business measures should enable multi-dimensional analysis and performance reporting through an On-Line Analytical Processing (OLAP) module and let users “slice and dice”, “drill down”, and view these KPIs in any combination they want.
Self-Service Information Access—The solution should serve as an easy self-service portal where KPIs should be instantly available in the right format for decision-making. Self-service information access should be provided to users on thin-client computers. This means that every user in the enterprise can turn to the solution as a way of managing and organizing the KPIs they wish to scan and view with single-click web access.
4. Decision Support System Architecture
A data mart is a collection of subject areas organized for decision support based on the needs of a given department. Finance has their data mart, marketing has theirs, operations has theirs and so on. The data mart is designed to suit and satisfy the needs of each department with very different objectives. This is why there are many different data marts in the corporation, each with its own distinctive look and feel. Data marts can be used as a stand-alone configuration or linked to an enterprise warehouse. A data mart is an essential component of any end-to-end decision support system and is often referred as the data storage element of the solution. A decision support solution encompasses several critical components, each of which is described in the following subsections.
Figure 2 Decision Support System Architecture
Field Data Collection
Many decisions within the utility industry are driven by data collected in the field. Field locations are often remote, so data must be transferred from the field to the front office. Timely decisions rely on data moving swiftly from the field to the office but speed is not the only criteria. Collecting quality field data in an efficient manner is of paramount importance because it often represents the only record of work done in the field and is the foundation of any decision support system.
The mobile computer and WFM application transform the way technicians process orders. Instead of receiving paper or voice-dispatched orders, technicians receive all of their orders through wireless data transmission to a mobile computer. Direct data entry from the field into a mobile computer improves data handling by removing the time-consuming and error-prone transcription phase. The use of laptop or hand-held computers in the field allows direct data entry into a digital format. The time spent by technicians filling out work is eliminated and there is no need for manual posting of paper documents. Data moves efficiently from the field to the office and into the WFM database.
Data sources are critical in that they provide access to the detailed information required for more routine user interaction with WFM data—such as status reporting. In addition, relational data plays an important role in performance traceability because it houses the details behind the trends discovered through exploration of the data. The WFM system should track the operational data (transactions and configuration information) generated throughout the workforce management process. The data sources should include the following types of data:
- Order Activity contains information captured from all operations performed on a given order.
- Mobile User Activity contains information captured from all operations involving a mobile user’s activity (for example, sign on and sign off forms and times, en route times, on site times).
- Miscellaneous Forms Activity contains information captured from all operations performed on miscellaneous forms.
Before raw data can be stored in a data mart, it must be transformed and cleansed so it has consistent meaning. This transformation may involve restructuring, redefining, filtering, combining, recalculating, and summarizing data fields from different data sources. During the cube-building process, aggregates are automatically incorporated, dramatically reducing the time and resources required for ongoing aggregate table creation and maintenance in the relational database. In fact, cube updates can be scheduled to run automatically. Cubes can also be automatically updated with new information on an incremental basis, which saves valuable processing time.
Metadata is reusable information about data structures, objects, applications, and business rules in the data mart that is defined once and is centrally stored. This allows all tools and applications accessing the data mart to use a common set of conventions which greatly reduces maintenance and assists both users and information technology professionals in finding the information they need and understanding what it means. Data mart metadata is created by and updated from the load programs that move data into the data marts. Data mart metadata usually contains the following components:
- Identification of the source of data
- Description of the customization that has occurred as the data passes from the database to the data mart
- Simple descriptive information about the data mart, including tables, attributes, relationships, etc.
As data is moved from various data sources into the data mart, it must be stored in a way that maximizes system flexibility, manageability, and overall accessibility. The answer: OLAP or On-Line Analytical Processing. OLAP data plays a key role in any successful data mart initiative because it is optimized to support “high-ROI” interaction with data—such as multi-dimensional analysis and business performance reporting.
OLAP data is presented in a way, which reflects multiple business dimensions such as work orders by quarter, by technician, or by business unit. This type of information allows managers to conduct effective comparison and trend analysis. Multi-dimensional data presents information within the context of business—not necessarily the way it is stored within the data source. Users have at their fingertips all the information they need to immediately conduct comparison and trend analysis. Furthermore, on the occasions when managers need detailed data —when summarized multi-dimensional analysis points to a specific trend that needs further investigation—they simply drill through to detail. This minimizes uncontrolled query traffic.
This model takes advantage of the ability to build OLAP cubes comprised of carefully selected "sweet spots" of information that have the highest impact on managers' decision-making. The provision of summarized data eliminates 80% of typical query activity, such as look-up or ad hoc queries. When managers drill through from OLAP data to actual transaction records, they query a relational database within this focused context. Drill-through access from cube to detail is pre-planned by the system administrator and limits access to rows and columns in the data mart, which ensures fast response times.
Analysis
This component provides a means to understand what is driving business performance. The analytic component must support sophisticated, autonomous end-user queries, rapid calculation of key business metrics, planning and forecasting functions, and what-if analysis on large data volumes. While the data mart storage component is read-only, the analytic solution must support multiple users simultaneously updating and recalculating information to enable “what-if ” and “what-next” modeling and planning applications. The OLAP server is the best technology for the analytic engine in the data mart.
When end-users access OLAP data, they are able to explore data mart information freely, in a manner that is simply not possible within the relational paradigm. For example, a business manager can quickly retrieve summarized data that highlights services orders by type of order by business unit. This data can then be dynamically explored. The business manager can drill down on the business unit dimension to review precisely which type of service orders within the business unit are problematic. Or, they may wish to slice and dice information by selecting an alternative business dimension—like total duration—to compare against type of orders and business unit.
Business Intelligence Reporting Tools
The robust reporting and analysis capabilities of business intelligence tools are the key to achieving maximum return on investment because they provide access to both OLAP and relational data sources. They address the different ways that people throughout the enterprise work with data to achieve results within their business context. OLAP Data Presentation and Access—An analytical reporting solution should allow powerful, interactive analysis. This means the ability to perform on-report drill, on-report pivot, on-report calculations, and direct report manipulation and formatting using a web browser. It should provide an easy-to-use interface that allows non-technical business people to be productive immediately.
Conventional Reporting Tools—Data query and reporting tools deliver data access through simple interfaces that hide the SQL language from end-users. These tools are designed for list-oriented queries, basic drill-down analysis, and report generation. Though they provide a view of simple historical data, these tools do not address the need for multi-dimensional reporting, analysis, modeling, and planning. They are also not capable of computing sophisticated metrics that users need to understand what is driving the business.
Self-Service Information Access
The decision support solution should serve as an easy self-service portal to reports, data in corporate databases, data on the Internet, and data in legacy systems. Self-service information access should be provided to existing users as well as new users, on thin-client computers. This means that every user in the enterprise can turn to the analytical reporting solution as their portal of choice to scan and view existing reports.
5. Key Performance Indicators
Key performance indicators are measures that can be used to compare and contrast various dimensions of the business. They are also used to gauge the operational performance of the organization. For example, the resource performance indicators can be used to compare actual and estimated duration of work orders for all technicians in a specific dispatch area. They could also be used to analyze work duration variance between dispatch areas. KPIs are made available through a ubiquitous web browser. This provides greater flexibility to organizations interested in distributing operational information across numerous business units. Immediate end-users are people involved in the management of the mobile workforce and its activities such as:
- Manager / Dispatcher
- District Manager
- Business Analysts and Operations staff
- Executives.
Resource Performance Indicators
Resource Productivity Indicator—The Resource Productivity Indicator compares and contrasts time measurements (Time En route, Time On site, Overall duration, Average Time, Variance, etc.).
Dispatch Efficiency Indicator—The Resource Dispatch Efficiency Indicator compares and contrasts the efficiency of all tasks initially dispatched to technicians or crews. A task is considered efficient if the initial dispatched technician or crew is the one completing it as well.
Work Quality Indicator—The Work Quality Indicator compares and contrasts the efficiency of all tasks initially dispatched to technicians or crews. If a repeated dispatch is reported within thirty days of prior completion, the task is flagged.
Overall Performance Indicators
Missed Commitments Indicator—The Missed Commitments Indicator compares and contrasts task measurements (tasks committed, completed, not completed, percent completed, percent missed commitment).
Overtime Indicator—The Overtime Indicator compares and contrasts overtime measurements (number of overtime hours required prior day, prior week, etc.).
Load Balance Indicator—The Load Balance Indicator compares and contrasts the number of hours to clear the workload for a given period of time in the past.
Root Cause Analysis Indicators
Overall Duration Indicator—The Overall Duration Indicator compares and contrasts time measurements from the time the customer notified the company to the actual completion of the work.
6. Conclusion
In an era of fast industry changes such as deregulation, privatization, mergers and acquisitions, utility companies recognize their competitiveness in the marketplace depends on accessing the critical information and leveraging it to maker better and faster decisions. Companies’ greatest challenge is transforming their WFM data into meaningful information to deliver the required knowledge in order to compete.
This challenge explains the shift from traditional reporting and query to the on-line tracking, monitoring and study of key performance indicators in a collaborative environment connected to the Internet and the interest in decision support system. A decision support solution that melds data mart, business intelligence, performance metrics, and the browser metaphor offers every manager the opportunity to get the right operational information at the right time in the right format. By tapping into the power of decision support, organizations implementing a decision support system can attain the following benefits:
- Business indicators are available in the right format for your decision-making needs—All the information you need about your mobile workforce and its ability to deliver on your commitments is available for short-term tactical adjustments or long-term strategic corrective action.
- Key performance indicators maximize the utilization of your workforce—Dispatchers, managers, and executives are able to effortlessly answer questions such as –What is the average amount of time that technicians spend travelling by dispatch area? What service types are causing multiple visits, etc. Using KPIs, decisions-makers are able to determine changes in productivity for technicians, and make the appropriate changes to maximize their utilization.
- Tailored views of your operations—A flexible browser-based system allows users to customize and save new views and reports based on standard KPIs. Managers can narrow the focus of their attention to specific areas of interest. For example, a business unit manager can tailor one report specific to work duration in one of their dispatch areas.
- Improve insights—Allows everyone in your enterprise to improve insights into the trends in your operations, and increases the accuracy of your forecasts and plans. Changes to standard views or reports made on the web server are instantly available.
- Create a historical archive of the field transactions—Fulfills requirements for having information on hand. A WFM decision support also has the ability to examine a completed order processed by the workforce management system.