Tapping into the gig economy

Roy Bridgland at Blue Yonder explains how technology can help logistics firms make smarter workforce planning decisions

The UK currently has a workforce of an estimated 1.44 million temporary workers. Representing a rich potential resource for logistics service providers (LSPs), in recent years many industries have looked to temporary workers to resolve short term skills gaps or enhance staffing levels during peak demand periods.

However, before introducing temporary workers into their organisational workforce strategy, warehouses and distribution centres should be mindful of three key considerations.

1. Implementation challenges

While temporary work may be ideal for certain industries such as delivery service businesses, firms operating in the logistics sector face a number of safety and training challenges that can significantly inhibit their ability to hire temporary workers off an app and get them up and running fast.

Without the right training, machinery such as conveyor belts and forklifts pose a serious danger to new or inexperienced employees undertaking a variety of roles. Indeed, hiring workers that lack the appropriate qualifications or licenses needed to operate warehouse equipment and machinery will expose the business – and the entire workforce – to significant risk. 

As a consequence, new personnel will need a minimum of 24 hours training before they can safely go onto the floor to work as a picker or packer who doesn’t operate specialist equipment. This means their onboarding process needs to incorporate an appropriate period of training, followed by a rigorous assessment of their understanding of safety controls and capacity to work on machines or lines.

How much training individuals will need to familiarise themselves with the working environment and be ‘safe’ on the job is a relative unknown that can’t be easily predetermined. Something that makes timelines difficult to manage when order volumes are mounting.

2. Dealing with disruption

As many logistics executives have discovered to their cost, planning strategies that focus primarily on peak and seasonal demands means the business is often unprepared to handle unexpected disruptions created by geo-political events or extreme weather phenomena.

For example, the current Red Sea crisis continues to severely disrupt the supply chains around the globe. In response, firms are scrambling to identify alternative shipping routes at significant additional cost in order to circumvent delays. 

Similarly, a short term focus on Q4 demands means organisations can be caught out by the impact of other seasonal strains. For example, the uptick in requirements during Q1 when suppliers and retailers conduct their annual inventories and make tactical decisions around last-minute holiday clearances and restocking goods.

Organisations that leverage artificial intelligence (AI) and machine learning to determine customer behaviours, market demands, potential risks and future scenarios will be better placed to assess and anticipate staffing capacities in advance of potential disruptions. Armed with these insights, organisations can determine how best to allocate existing personnel and when an expanded workforce will be needed.

Utilising this data in the cloud will also make it easier to engineer real-time integrations with other supply chain operators and share relevant intelligence in a strategic and applied way. For example, when potential disruptions to the supply chain are identified on the horizon, logistics teams can prepare in advance and hire and train any additional staff needed to minimise stoppages or delays.

3. Using AI to augment staffing needs

Rather than looking to always boost its workforce with temporary workers to cope with peak season demands, the logistics sector should instead evaluate how today’s AI technologies could drive enhanced flexibility for both existing and incoming workforces.

Today’s generative AI-powered co-pilots are capable of guiding front-line teams efficiently and accurately through a variety of inventory management, data analysis and order processing tasks. This in turn enables logistics firms to focus its current workforce on tasks that require a higher degree of skill.

Similarly, emerging AI technologies such as robotics are making it easier to streamline how goods are organised, stored and transported and to accommodate dynamic workforce needs. For example, if staff are required to work second shifts due to parenting commitments, robotics can be onboarded to assist with first shifts and deployed as required to work around the scheduling needs of employees. 

Alongside helping to boost productivity and retention rates for existing staff, this flexibility also makes organisations more appealing to potential new employees.

Enabling a smarter workforce strategy

While the gig economy may appear an attractive short term solution for warehouses, distribution centres and logistics teams experiencing ongoing talent shortages, it is not without its risks.

Using AI, the data cloud and robotics, logistics professionals will be able to enhance workflows and undertake the strategic workforce planning needed to address potential demands and disruptions on the horizon. They will also be able to better predict if, when, and how they need to address manpower gaps.

This is a move that could help eliminate the constant need to engage in temporary worker recruitment and deliver a more controlled and productive environment that supports both core and temporary workers to perform.

Roy Bridgland is senior industry strategies director EMEA at Blue Yonder

Main image courtesy of iStockPhoto.com and ArtemisDiana