February 28, 2024
min read

How Precanto Solves: Contingent Worker Forecasting

Contract employees, seasonal employees, temporary visa holders, interns – such employees could fall under the rubric of contingent workers, and form a critical lever for many business leaders. When key business needs collide with the inability to add fulltime headcount, contract or contingent workers can fill the gap. 

The reasons for hiring contingent workers are varied – an equipment emergency that requires more hands on the IT desk, a temporary fill for an extended employee medical leave, or market pressures that make executives hesitant to add permanent headcount even as there’s work to be done. 

The result is often the same: Headcount forecasting mayhem. 

Realtime, data-based headcount forecasting is a big part of why I joined Precanto, an AI/ML headcount forecasting platform. In this series, we at Precanto are examining some of the key data that powers headcount forecasting, and how the intricacies of this data can contribute to missed forecasts.

The complexities of contingency worker forecasting often contribute to missed opportunities and budget overruns, and challenge finance leaders’ predictions. 

What is contingency worker forecasting?

Contingency worker forecasting refers to the planning involved with workers employed flexibly as a non-permanent resource at the behest of a company. These workers might have a fixed contract length, work only until a project is completed, or work ad hoc as needed.

For example, student internships often qualify as contingent worker arrangements, since an internship is temporary and often variable – running just for a summer, or for an academic period, with variable start and end dates, at the discretion of the company and the nature of the work. Foreign country contractors are another example of contingent workers who are not eligible for permanent hiring. Working on a contingent basis means they can avoid certain visa requirements and paperwork. 

In the current uncertain business environment, the flexibility of contingent workers has become a boon. Many businesses need top tier talent but can’t afford them, or need specific expertise, but only for a short-term project that doesn’t require long-term employment. Many contingent workers like the flexibility and variety. 

The trend toward leveraging contingent workers will only grow. A 2023 survey by Ceridian found that 80% of executives currently employ contingent workers, with 65% of those firms expected to increase their contingent workforce in the next two years. 

How contingent workers create forecasting obstacles

These workers do not have the benefits often required for full time employees, such as the health benefits, bonuses or stock based compensation that form a competitive full time employment package – so the data for contingent workers needs separate formulas and calculations in terms of budgeting and forecasting. 

Often business needs change – hence appreciating the flexibility of contingent workers — but the needs can be so changeable year over year that a simple extrapolation of previous year’s data as a default forecasting solution isn’t accurate. Meanwhile, specific contractor equipment purchases also need to be timed for when the resource is on site and available to work, thus allowing for efficient tool deployment.

One critical, but often overlooked, aspect of forecasting for contingent workers is allocating for new needs within a flat budget. If the baseline is incorrectly set, thereby incorrectly re-allocated against, then the investment asks will over- or under-compensate, resulting in unforeseen budget variances during the year. Coupled with the volatile nature of the starting and ending terms, forecasting can start to feel unpredictable. 

Meanwhile, business change factors and parameter shifts are difficult to reflect quickly and precisely in a spreadsheet, with endlessly appended lines of new contingent workers.

Precanto: Contractor forecasting for modern enterprises

Precanto transforms how companies manage their financials and automate contingency worker forecasting by applying automation and AI/ML with built-in finance context, to create the most accurate contingent worker outlay as possible.  

This will allow for leaders to properly plan across ever-changing macroeconomic conditions year over year.

Book a demo now.  

Tony Lin
Head of Customer Success
Forecasting best practices
Precanto Platform

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