What are the 3 most important components of forecasting?

The following 3 components are the essential best practices of workforce forecasting that companies need to consider to optimize their staff scheduling processes. Demand Planning. ... Internal Supply Analysis. ... Gap Analysis and Action Planning.

zipforecasting.com - 3 Components of Data-Driven Workforce Forecasting

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Organizations can invest in workforce forecasting technology to support predictive supply analytics, bottom-up demand planning, and assess and solve internal workforce supply and demand gaps.

What is Workforce Forecasting?

The process of workforce forecasting aims to provide the necessary insight to optimally schedule employees based on peak seasons, staff qualifications, and cost reduction strategies. These forecasts can even be calculated daily or hourly for real-time indicators of performance. As the workforce is generally the largest expense incurred by the company, effective workforce planning is crucial for any organization to reduce their total expenditures. Workforce expenses can reach over 30-50% of gross sales depending on the industry. These expenses are comprised of salaries, benefits, taxes, commissions, and more. The most effective way to approach workforce optimization is to create a strategy based on accurate forecasts. Businesses need to leverage the use of historical data and sales trends to forecast fluctuations in workforce demand.

3 Key Components of Workforce Forecasting

The following 3 components are the essential best practices of workforce forecasting that companies need to consider to optimize their staff scheduling processes.

1. Demand Planning

This element of workforce planning is when a company decides on the headcount it will need for each role and each organizational unit. There are 2 key ways to execute demand planning to have the least amount of potential risk. The first strategy is based on organizational culture. Workforce management should understand that their labor costs estimations may be inaccurate due to unforeseen changes in demand. Therefore, the planning phase should be focused on a range of outcomes that allow for flexibility to manage uncertainty and efficiently work through challenges that may arise. The second element is the utilization of the bottom-up' technique. This requires technology that allows the users to create their own workforce plans and customized analysis. A technology-enabled bottom-up approach creates higher accuracy and enables a culture within the organization that is responsive to changes and is equipped to assess how these changes impact staffing levels. The ideal scenario is when a manager is provided with a plan for the staff demand, which describes the job roles and staffing levels needed based on how the company generally schedules shifts against demand drivers, such as work volumes.

The decision-making process is led by the answers to questions such as-

Does the company appropriately schedule shifts according to demand?

How can the business align staffing levels with the desired growth strategies?

Are there areas within the organization that pose low-risks when understaffed?

2. Internal Supply Analysis

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This phase of workforce planning involves an organization assessing whether the internal supply has the ability to meet demand. In this process, managers evaluate the talent supply by role, while considering retirement, internal job movement, and turnover. This will also require businesses to assess performance quality and capability within the roles. To find the supply forecast, predictive analytics is used to determine turnover risk, retirement, and workforce movement of individuals with the company. Statistical analysis with machine learning gives companies the opportunity to conduct complex analyses of employee demographics, workplace conditions, external conditions, economic circumstances, and employer actions. These insights, such as understanding which individuals are at the highest risk for turnover, can give a company clarity to address future gaps in the workforce with minimal business disruptions.

The following outcomes can be achieved using the internal supply analysis method-

Understand the largest talent gaps, which roles are the highest priority, and the most challenging positions to fill.

Create targeted replacement planning to transfer knowledge effectively for critical roles.

Proactive recruitment to prioritize gaps and source supply.

Plan for future open positions to fill through developmental assignments and promotions.

Attrition program creation to avoid expenses in workforce reductions for roles that have reductions in staff requirements.

Strategies of pay and bonuses

Working structures and career ladders

Transfers, promotions, and reorganization

This stage is where an organization evaluates its gaps to determine the actions that can be taken to close them. Companies can model the prospective impacts of situations beyond traditional recruitment, development, and transition contexts, to the impact of HR policy interventions and talent management responses.The combination of demand planning and internal supply analysis will highlight the gaps between demand and supply in terms of the size, type, and timing of these gaps. This allows for a directional recruitment plan to reallocate resources and avoid costly cycles of staffing levels that are too high or too low.An organization that utilizes this technology will come to understand that there are several factors that will drive retention, employee engagement, and workforce and company performance, including- Understanding these relationships can allow companies to close these gaps while achieving better retention rates and creating optimized policies for the workforce around desired outcomes. Technology is an essential enabler for demand planning, internal supply analyses, and gap analyses, as it provides real-time financial and demand projections. Businesses can utilize forecasting software to optimize their staffing levels and eliminate the guesswork in their labor budgets.

zipforecasting.com - 3 Components of Data-Driven Workforce Forecasting

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