When develop- ing the cost, scope and schedule, and writing the programming document, each division generates its estimated support needs. There is no one proscribed method for doing so.
The Construc- tion Division in the Central Region of California a Cooperative of capital functions for Districts 5, 6, 9 and 10 uses a method that is similar to the other districts and regions in the state. A centralized support squad starts the process by taking the basic job information, location, length, description of work to be performed, and capital cost estimate, and then generates a straw man type estimate.
Factors for weather day disruptions are also applied, as well as any anticipated logistic factors for remote location projects. These initial estimates are made with our his- torical usages in mind, but are not solely based on our historical project spending data. This base workplan is then sent to the Resident Engineer RE and Construction Manager that will most likely be assigned to the project when it goes to construction.
They review the esti- mate and suggest changes based on their experience with similar projects, the anticipated breakdown and experience level of their staff, any area specific conditions, as well as potential economies of scale due to their overall workload from other projects. When completed, this workplan is sent to the project manager PM.
They review and if necessary meet with the Construction team to negotiate the final workplan details for the Construction Division. XPM lists all scheduled projects and can generate estimated resource needs for a project, series of projects or program in a specified geo- graphic area, or for an individual RE or PM. Each district has its series of projects at all stages of develop- ment entered into XPM, and can use the system to analyze and break down resource needs now and in the future for all divi- sions.
As with any system, the projections are only as good as the assumptions they are based on. As each project is developed, after its initial scoping, more information about the details of the project is generated, and therefore a more refined estimate of the resources needed in Construction can be made. At least once a year, and at important programmatic milestones during the year, the Construction Division reviews its upcoming projects, and requests any updates to the estimates it feels are necessary.
This budget information is converted to personnel require- ments based on the specific needs of the project. The number of personnel and hours worked by each is adjusted during the project to reflect needs and budget requirements. Budgets are estab- lished for agency construction staffing requirements and the specific personnel requirements are determined by project needs and budgetary guidelines. During this visit the team reviewed several projects with BART representatives.
Because of the size of the projects, extensive use is made of outside consultants for construction staffing. For example, on the Oakland Air- port Connector project, there are 17 full-time construction management services personnel, but only two of these are BART employees. Staffing plans are developed individu- ally for each project based on the project schedule, budget, and characteristics.
As each new fiscal year approaches, a new allocation is made by combining the resource needs generated by the XPM system, and the estimates of non- workplanned projects and other non-project direct needs train- ing, safety programs etc. One important omission in the system is the estimation of the number of vehicles and types of equipment needed, and other cost information necessary to properly anticipate support spending on the project. As a result, there are times when the equipment needed is not available or is in the wrong locations, resulting in inefficient use of the personnel resources.
At any point in time, you can get a project direct workload estimate for Construction for the next several years. Using aver- age percentages for the non-project direct resource needs, you can estimate your total Personnel Equivalents for any given future year. It must be noted that the group of projects shown in XPM to be worked on in any given year are subject to change as funding levels for future years become more accurate, and as the development of the projects proceeds, and the final delivery date to construction becomes more predictable.
The agency does not utilize a model or formula to determine project staffing. A resident engineer is appointed to a project. This analysis includes an assessment of issues such as: Does the project have unique storm water impacts or implications? Is there a potential for archeological issues? Will the project have significant noise impacts that must be addressed and moni- tored? Is the project in a politically sensitive area? The resi- dent engineer then determines the nature and number of staff required for the project.
Los Angeles County Metropolitan Transportation Authority Team members met with the project manager for a large construction project, the director for program management, and the Principal Technical Estimator for Program Manage- ment Oversight.
Los Angeles County Metropolitan Trans-. It divides flight segments into disjoint sets of pairings where no two pairings have the same flight segment. No more pouring over different spreadsheets for hours trying to figure things out. Patient care facilities rely on our applications to show them how they are doing in meeting the documented and required hourly care needs of their patients. These facilities not only need to ensure they are managing their staffing according to their own company policies, but they also have to maintain adequate staffing to meet regulatory requirements.
Contact us today for a free chat regarding your Microsoft Excel consulting needs. Microsoft and Microsoft Excel are registered trademarks of Microsoft corporation. Google Rating. Similar volumes were noted in four day-of-the-week data groupings:.
Based on these groupings of days representing different ED volume patterns, it was possible to enhance the existing validated labor forecasting tool to create a more reliable forecast of patient arrivals according to typical seasonal hourly patterns within these four time frames.
The rationale was that forecasting volume in smaller increments of time would provide charge nurses more opportunities throughout the day to adjust staffing to anticipated demand. The exhibit below compares a Monday four-hour forecast produced prior to the enhancement by the labor forecasting tool with an enhanced two-hour forecast and an enhanced two-hour average forecast.
The enhanced two-hour average forecast—produced by averaging a two-hour and three-hour forecast based on historical data specific to the particular season and day of the week—was found to provide the best result.
To determine the most highly correlated forecasting model, the study used an average arrival quantity for Mondays from July through August. Four-hour intervals demonstrated strong correlation, and further refinement at two-hour intervals demonstrated no statistical significance between actual and forecasted arrival times within any of the seasons. To achieve the most efficient and effective staffing hours per patient visit, a staffing model was implemented that matched the staffing schedule to the seasonal forecast specific to each day of the week.
The exhibit below, for example, shows an improvement in hours per patient visit HPPV over the summer season June, July, and August that resulted from implementation of the new staffing model. The forecasts under the model proved accurate for all days except Sunday. Prior to the implementation of this study, Butterworth Hospital had significant overtime costs. Time series techniques presented in this study allowed for the evaluation of seasonal patient arrival patterns by day of the week and hour of the day.
The significant results of this analysis led to the creation of baseline staffing templates and the enhancement of existing forecasting tools. As a result, the authors of this study generated an enhanced two-hour average forecasting tool to more closely align staffing models to meet the demand of fluctuating arrival quantities.
At the start of fiscal year , Butterworth Hospital ED management operationalized the findings of this study with validated and improved confidence. Baseline staffing templates for day of the week within a season of the year were created and uploaded into an electronic self-scheduling application. Charge nurses were then trained on how to generate the report, how to transfer the data, and how to use the data for algorithmic staff resource allocation decision making.
Lastly, a robust position control was created to ensure appropriate management of high-cost labor and variable FTEs. As demand for ED services continues to grow, appropriate allocation of resources to meet this demand will be an ongoing financial concern for management. This study provides a solution for implementing custom staffing solutions and improved resource allocation that provides a cost savings benefit.
Current healthcare technology poses a significant limitation to healthcare organizations for advancing continued growth in the use of predictive analytics. This study identified gaps related to the storage, access, and automation of EHR data and reporting. The use of real-time data and reporting would allow for enhanced modeling and the generation of automated, continuous hour forecasting.
The best way to determine this is whether or not data is available on how this software improves workplace performance. There should be some quantifiable and verifiable case studies for you to reference which shows the efficacy of the software to forecasting and planning. The main reason to upgrade your systems in the first place is to save money by increasing efficiency, so don't be afraid to ask how this ROI is to be realized. Integration with existing systems is a highly underrated feature that is crucial to preservation of data and seamless upgrades to any new system.
The ability to import data and work in concert with operating systems which will remain in use after an upgrade is perhaps the most important feature that any new software can have. Any implementation of a new system is bound to have a period of adjustment where the workforce familiarizes themselves with the new software and learns the ropes of using it to its fullest potential, and scalable integration is one of the best ways to ensure that there are as few bumps in this road as possible.
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