At Clarus WMS, the focus is on practical levers like walk sequences, demand pick faces, accurate master data, and clean operational workflows that reduce travel and idle time. As our in?house expert notes, the system treats \u201ca SKU as a SKU\u201d, the physical design, replenishment rules, and pick?face strategy determine the true cost to serve.<\/p>\n\n\n\n
![\"4](\"https:\/\/stg-khh4l5.elementor.cloud\/wp-content\/uploads\/2023\/03\/Gemini_Generated_Image_knnfy6knnfy6knnf-1024x559.webp\")
<\/figure>\n\n\n\nThe result of traditional methods:<\/strong><\/h2>\n\n\n\n\n- Delays in fulfilment due to inefficient picking and high travel time
<\/li>\n\n\n\n - Inefficiencies in labour utilisation, leading to overtime and poor cross?training
<\/li>\n\n\n\n - Lost revenue from non?optimised slotting and lack of analytics for forecasting
<\/li>\n<\/ul>\n\n\n\nThis article breaks down the failures of outdated labour management methods and explores how Clarus WMS rethinks the process with modern, cloud?based practices for better visibility and audit trails. We add evidence and clarifications to support decisions in live operations.<\/p>\n\n\n\n
<\/div>\n\n\n\nWhat is Labour Cost Management and How Do I Optimise It?<\/strong><\/h2>\n\n\n\nLabour cost management means measuring and improving the time your team spends creating value, then removing or reducing non?value activities like unnecessary walking and rework. Practical steps include analysing travel paths, implementing sensible slotting rules, and forecasting labour for peaks to reduce overtime reliance. The wage environment has been inflationary since 2020, so even modest process gains convert quickly to savings. (McKinsey & Company<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cYou must pair system capability with physical reality. If you add SKUs without space, rethink pick faces, replenishment mins and maxes, and whether tote?picking or pallet pick faces suit the demand pattern.\u201d<\/p>\n\n\n\nWhere organisations do adopt voice?directed work, industry data indicates meaningful accuracy and productivity gains, but suitability varies by site. Honeywell reports up to 35 percent productivity improvement from legacy methods and up to 50 percent error reduction where voice fits the use case. (Honeywell Automation<\/a>)<\/p>\n\n\n\n<\/div>\n\n\n\n![\"Hidden](\"https:\/\/stg-khh4l5.elementor.cloud\/wp-content\/uploads\/2023\/03\/Gemini_Generated_Image_eug7yreug7yreug7-scaled.webp\")
<\/figure>\n\n\n\n<\/div>\n\n\n\nDo I Need Automation for My Warehouse Operations?<\/strong><\/h2>\n\n\n\nAutomation should follow a clear cost case. In many mid?sized facilities, process discipline, data?driven slotting, and cross?training can deliver quick wins. For higher volumes or SKU complexity, goods?to?person and AMR solutions can provide variable capacity and remove walking from the process, with retail examples showing payback in roughly two to three years when consumption is structured as Robotics?as?a?Service. (McKinsey & Company<\/a>)<\/p>\n\n\n\nAdoption intent remains high across logistics. The 2024 MHI Annual Industry Report, produced with Deloitte, shows strong five?year plans for AI and robotics across respondents, reinforcing the importance of a roadmap rather than piecemeal pilots. (Locus Robotics<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cAutomation\u2019s trade?off is upfront capex against storage density, throughput, and reduced manual handling. You still need a realistic payback plan, not just a machine.\u201d<\/p>\n\n\n\n![\"Reducing](\"https:\/\/stg-khh4l5.elementor.cloud\/wp-content\/uploads\/2023\/03\/Gemini_Generated_Image_cnny9zcnny9zcnny-1024x559.webp\")
<\/figure>\n\n\n\n<\/div>\n\n\n\nHow Does Voice?Picking Improve Productivity?<\/strong><\/h2>\n\n\n\nVoice?directed picking is an established option that can keep hands and eyes free, reduce scanning steps, and improve first?time accuracy. Vendor benchmarks cite up to 35 percent productivity improvement and up to 50 percent error reduction versus legacy methods when correctly deployed. Suitability depends on product mix, ambient noise, and the maturity of existing RF processes. (Honeywell Automation<\/a>)<\/p>\n\n\n\n<\/div>\n\n\n\nWhat Role Does Slotting Play in Travel?Time Reduction?<\/strong><\/h2>\n\n\n\nSlotting is one of the most reliable levers for cutting labour cost because travel time typically accounts for around half of manual order?picking time. Placing high?velocity SKUs closer to despatch and co?locating items that are often picked together reduces walking and truck movements, which directly lowers labour minutes per line. (informs-sim.org<\/a>)<\/p>\n\n\n\nModern 3PL slotting programmes analyse 52 weeks of rolling demand and apply per?SKU forecasting, then assign locations using distance?minimising rules to cut travel and congestion. This approach is increasingly common in large 3PLs. (geodis.com<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cUse transactional pick data through BI to identify fastest movers, then physically place them near your goods-out and set walk sequences accordingly. The physical layout still governs your cost.\u201d<\/p>\n\n\n\n<\/div>\n\n\n\nTraditional Methods vs. Clarus WMS for Labour Management<\/strong><\/h2>\n\n\n\nTraditional time?and?motion exercises are slow and quickly outdated. A better approach is continuous measurement of lines per labour hour, travel sequences, and replenishment triggers, then weekly slotting adjustments. Clarus WMS supports this by giving teams real?time visibility and clean data for BI, so you can act on facts rather than periodic studies.<\/p>\n\n\n\n
Where organisations implement voice in suitable contexts, independent vendor data suggests up to 35 percent productivity uplift. Treat these as industry comparators rather than a guarantee, and validate with a pilot in your process. (Honeywell Automation<\/a>)<\/p>\n\n\n\n<\/div>\n\n\n\nWhy Teams Struggle with Labour Cost<\/strong><\/h2>\n\n\n\n\n- Limited automation in picking, causing high travel time and overtime reliance
<\/li>\n\n\n\n - Manual slotting processes that increase errors and ergonomic strain
<\/li>\n\n\n\n - Poor analytics for forecasting that weaken incentive programmes
<\/li>\n\n\n\n - Inadequate cross?training that reduces flexibility during peaks
<\/li>\n<\/ul>\n\n\n\n<\/div>\n\n\n\nHow Does WMS Handle Labour Cost?<\/strong><\/h2>\n\n\n\nClarus WMS emphasises real?time visibility, accurate master data, and configurable walk sequences to reduce travel and waiting. It also supports demand pick faces to balance replenishment effort with pick density for each client account in 3PL settings. In one recent customer story, Interspan reports cutting reporting time by about 90 percent after moving from on?premises WMS to Clarus, which freed leaders to focus on operational improvement. (Clarus WMS<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cDemand pick faces help absorb seasonal spikes, but you must plan space, replenishment rules, and staffing, otherwise you simply move the bottleneck.\u201d<\/p>\n\n\n\n<\/div>\n\n\n\n![\"Don't](\"https:\/\/stg-khh4l5.elementor.cloud\/wp-content\/uploads\/2023\/03\/Gemini_Generated_Image_8yvh058yvh058yvh-1024x559.webp\")
<\/figure>\n\n\n\n<\/div>\n\n\n\nReal?Time Monitoring<\/strong><\/h3>\n\n\n\nDashboards should surface exceptions such as mispicks, repeated long walks, and slow replenishments. Tracking these in real time enables you to correct before overtime accrues and before errors cascade into rework. This is where clean, timely WMS data pays for itself.<\/p>\n\n\n\n
Scalable Adaptation<\/strong><\/h3>\n\n\n\nWhen SKU counts grow, process rules remain the same, the cost impact depends on space, pick?face design, and replenishment settings. Use min?max and demand?triggered pick?faces to keep fast movers accessible as accounts scale.<\/p>\n\n\n\n
Full Visibility<\/strong><\/h3>\n\n\n\nEnd?to?end visibility across inbound, storage, and outbound helps you prevent idle walking, align labour with demand, and maintain audit trails. This enables realistic incentive schemes and kaizen cycles based on facts, not averages.<\/p>\n\n\n\n
<\/div>\n\n\n\nReady to See It in Action?<\/strong><\/h2>\n\n\n\nImplementing labour cost optimisation with Clarus WMS can transform warehouse productivity, reducing overtime and improving ergonomics with fewer surprises. Imagine a weekly cadence of small, data?driven slotting moves that compound into lasting savings. Contact Clarus WMS for a demo to explore these benefits.<\/p>\n\n\n\n
<\/div>\n\n\n\nReferences<\/strong>
<\/p>\n\n\n\nUsing digital twins to unlock end-to-end supply chain growth, McKinsey<\/a><\/p>\n\n\n\nAverage Weekly Earnings, series K5B7 (Transport and storage)<\/a><\/p>\n\n\n\nAverage weekly earnings in Great Britain: December 2024, ONS<\/a><\/p>\n\n\n\nHoneywell Guided Work Software (voice picking benchmarks)<\/a><\/p>\n\n\n\nTravel time\u2019s share of picking time, Elbert & M\u00fcller citing Bartholdi and Hackman, 2017 IEEE WSC<\/a><\/p>\n\n\n\nWarehouse & Distribution Science, Bartholdi & Hackman <\/a><\/p>\n\n\n\nGEODIS slotting optimisation, 52-week rolling analysis <\/a><\/p>\n\n\n\nMHI Annual Industry Report 2024 (with Deloitte)<\/a><\/p>\n\n\n\nAI in distribution operations, McKinsey<\/a><\/p>\n\n\n\nAutomation payback and RaaS, McKinsey<\/a> <\/p>\n\n\n\nHSE Key figures for Great Britain 2023\/24, including MSDs and total cost<\/a> <\/p>\n\n\n\nInterspan to cut reporting time by 90%, Clarus WMS customer story<\/a> <\/p>","protected":false},"excerpt":{"rendered":"Cut warehouse labour costs by reducing travel time, smarter slotting and data-driven planning, not rushed automation, for safer faster fulfilment now.<\/p>","protected":false},"author":207386994,"featured_media":26596,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1578],"tags":[1679],"class_list":["post-10356","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","tag-article-new"],"acf":{"faq_new":"
What is the single biggest lever to reduce warehouse labour cost in picking?<\/b><\/h3>\r\nCut walking. Research shows travel between locations is responsible for about half of manual order-picking time, so minimising distance through slotting, batching, and sensible routing yields immediate savings. Start by placing highest-velocity SKUs near despatch and co-locating common pairs.<\/span> (informs-sim.org)<\/span><\/a>\r\nIs voice-directed picking still worth considering in 2025?<\/b><\/h3>\r\nIt can be, if your environment suits it. Benchmarks from Honeywell indicate up to 35 percent productivity improvement versus legacy methods and up to 50 percent fewer errors, although results vary with product mix, ambient noise, and existing RF processes. Validate with a pilot before scaling.<\/span> (Honeywell Automation)<\/span><\/a>\r\nHow long is a realistic payback for warehouse automation like AMRs or goods-to-person?<\/b><\/h3>\r\nPayback depends on volumes and labour intensity, but several retailers have achieved two to three-year paybacks by using Robotics-as-a-Service to align costs with usage. A structured network-wide approach and clear vendor scope are critical to hit those returns. <\/span>(McKinsey & Company)<\/span><\/a>\r\nHow should 3PLs adjust slotting for seasonality without overstaffing?<\/b><\/h3>\r\nUse rolling demand horizons and per-SKU forecasting to refresh slot assignments before peaks. Leading 3PL approaches analyse 52 weeks of order history and then place higher-velocity items closer to outbound to cut travel and congestion.<\/span> (geodis.com)<\/span><\/a>\r\nHow do ergonomics issues drive labour cost, and what can I track?<\/b><\/h3>\r\nPoor ergonomics increases walking, handling, and rework, which elevates time per line and sick leave. The HSE reports 543,000 workers with work-related musculoskeletal disorders and an estimated \u00a321.6 billion annual cost of work-related ill health and injury, so track walk distance, lift frequency, and near-misses alongside lines per hour. <\/span>(HSE)<\/span><\/a>\r\nAre wage pressures easing in UK transport and storage?<\/b><\/h3>\r\n<\/b>Earnings have remained elevated. ONS Average Weekly Earnings series for transport and storage shows continued increases through 2024 and 2025, so labour-efficiency initiatives remain a priority. <\/span>(Office for National Statistics)<\/span><\/a>"},"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t
<\/li>\n\n\n\n
<\/li>\n\n\n\n
<\/li>\n<\/ul>\n\n\n\n
This article breaks down the failures of outdated labour management methods and explores how Clarus WMS rethinks the process with modern, cloud?based practices for better visibility and audit trails. We add evidence and clarifications to support decisions in live operations.<\/p>\n\n\n\n
What is Labour Cost Management and How Do I Optimise It?<\/strong><\/h2>\n\n\n\nLabour cost management means measuring and improving the time your team spends creating value, then removing or reducing non?value activities like unnecessary walking and rework. Practical steps include analysing travel paths, implementing sensible slotting rules, and forecasting labour for peaks to reduce overtime reliance. The wage environment has been inflationary since 2020, so even modest process gains convert quickly to savings. (McKinsey & Company<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cYou must pair system capability with physical reality. If you add SKUs without space, rethink pick faces, replenishment mins and maxes, and whether tote?picking or pallet pick faces suit the demand pattern.\u201d<\/p>\n\n\n\nWhere organisations do adopt voice?directed work, industry data indicates meaningful accuracy and productivity gains, but suitability varies by site. Honeywell reports up to 35 percent productivity improvement from legacy methods and up to 50 percent error reduction where voice fits the use case. (Honeywell Automation<\/a>)<\/p>\n\n\n\n<\/div>\n\n\n\n<\/figure>\n\n\n\n<\/div>\n\n\n\nDo I Need Automation for My Warehouse Operations?<\/strong><\/h2>\n\n\n\nAutomation should follow a clear cost case. In many mid?sized facilities, process discipline, data?driven slotting, and cross?training can deliver quick wins. For higher volumes or SKU complexity, goods?to?person and AMR solutions can provide variable capacity and remove walking from the process, with retail examples showing payback in roughly two to three years when consumption is structured as Robotics?as?a?Service. (McKinsey & Company<\/a>)<\/p>\n\n\n\nAdoption intent remains high across logistics. The 2024 MHI Annual Industry Report, produced with Deloitte, shows strong five?year plans for AI and robotics across respondents, reinforcing the importance of a roadmap rather than piecemeal pilots. (Locus Robotics<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cAutomation\u2019s trade?off is upfront capex against storage density, throughput, and reduced manual handling. You still need a realistic payback plan, not just a machine.\u201d<\/p>\n\n\n\n<\/figure>\n\n\n\n<\/div>\n\n\n\nHow Does Voice?Picking Improve Productivity?<\/strong><\/h2>\n\n\n\nVoice?directed picking is an established option that can keep hands and eyes free, reduce scanning steps, and improve first?time accuracy. Vendor benchmarks cite up to 35 percent productivity improvement and up to 50 percent error reduction versus legacy methods when correctly deployed. Suitability depends on product mix, ambient noise, and the maturity of existing RF processes. (Honeywell Automation<\/a>)<\/p>\n\n\n\n<\/div>\n\n\n\nWhat Role Does Slotting Play in Travel?Time Reduction?<\/strong><\/h2>\n\n\n\nSlotting is one of the most reliable levers for cutting labour cost because travel time typically accounts for around half of manual order?picking time. Placing high?velocity SKUs closer to despatch and co?locating items that are often picked together reduces walking and truck movements, which directly lowers labour minutes per line. (informs-sim.org<\/a>)<\/p>\n\n\n\nModern 3PL slotting programmes analyse 52 weeks of rolling demand and apply per?SKU forecasting, then assign locations using distance?minimising rules to cut travel and congestion. This approach is increasingly common in large 3PLs. (geodis.com<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cUse transactional pick data through BI to identify fastest movers, then physically place them near your goods-out and set walk sequences accordingly. The physical layout still governs your cost.\u201d<\/p>\n\n\n\n<\/div>\n\n\n\nTraditional Methods vs. Clarus WMS for Labour Management<\/strong><\/h2>\n\n\n\nTraditional time?and?motion exercises are slow and quickly outdated. A better approach is continuous measurement of lines per labour hour, travel sequences, and replenishment triggers, then weekly slotting adjustments. Clarus WMS supports this by giving teams real?time visibility and clean data for BI, so you can act on facts rather than periodic studies.<\/p>\n\n\n\n
Where organisations implement voice in suitable contexts, independent vendor data suggests up to 35 percent productivity uplift. Treat these as industry comparators rather than a guarantee, and validate with a pilot in your process. (Honeywell Automation<\/a>)<\/p>\n\n\n\n<\/div>\n\n\n\nWhy Teams Struggle with Labour Cost<\/strong><\/h2>\n\n\n\n\n- Limited automation in picking, causing high travel time and overtime reliance
<\/li>\n\n\n\n - Manual slotting processes that increase errors and ergonomic strain
<\/li>\n\n\n\n - Poor analytics for forecasting that weaken incentive programmes
<\/li>\n\n\n\n - Inadequate cross?training that reduces flexibility during peaks
<\/li>\n<\/ul>\n\n\n\n<\/div>\n\n\n\nHow Does WMS Handle Labour Cost?<\/strong><\/h2>\n\n\n\nClarus WMS emphasises real?time visibility, accurate master data, and configurable walk sequences to reduce travel and waiting. It also supports demand pick faces to balance replenishment effort with pick density for each client account in 3PL settings. In one recent customer story, Interspan reports cutting reporting time by about 90 percent after moving from on?premises WMS to Clarus, which freed leaders to focus on operational improvement. (Clarus WMS<\/a>)<\/p>\n\n\n\nExpert insight:<\/strong> \u201cDemand pick faces help absorb seasonal spikes, but you must plan space, replenishment rules, and staffing, otherwise you simply move the bottleneck.\u201d<\/p>\n\n\n\n<\/div>\n\n\n\n<\/figure>\n\n\n\n<\/div>\n\n\n\nReal?Time Monitoring<\/strong><\/h3>\n\n\n\nDashboards should surface exceptions such as mispicks, repeated long walks, and slow replenishments. Tracking these in real time enables you to correct before overtime accrues and before errors cascade into rework. This is where clean, timely WMS data pays for itself.<\/p>\n\n\n\n
Scalable Adaptation<\/strong><\/h3>\n\n\n\nWhen SKU counts grow, process rules remain the same, the cost impact depends on space, pick?face design, and replenishment settings. Use min?max and demand?triggered pick?faces to keep fast movers accessible as accounts scale.<\/p>\n\n\n\n
Full Visibility<\/strong><\/h3>\n\n\n\nEnd?to?end visibility across inbound, storage, and outbound helps you prevent idle walking, align labour with demand, and maintain audit trails. This enables realistic incentive schemes and kaizen cycles based on facts, not averages.<\/p>\n\n\n\n
<\/div>\n\n\n\nReady to See It in Action?<\/strong><\/h2>\n\n\n\nImplementing labour cost optimisation with Clarus WMS can transform warehouse productivity, reducing overtime and improving ergonomics with fewer surprises. Imagine a weekly cadence of small, data?driven slotting moves that compound into lasting savings. Contact Clarus WMS for a demo to explore these benefits.<\/p>\n\n\n\n
<\/div>\n\n\n\nReferences<\/strong>
<\/p>\n\n\n\nUsing digital twins to unlock end-to-end supply chain growth, McKinsey<\/a><\/p>\n\n\n\nAverage Weekly Earnings, series K5B7 (Transport and storage)<\/a><\/p>\n\n\n\nAverage weekly earnings in Great Britain: December 2024, ONS<\/a><\/p>\n\n\n\nHoneywell Guided Work Software (voice picking benchmarks)<\/a><\/p>\n\n\n\nTravel time\u2019s share of picking time, Elbert & M\u00fcller citing Bartholdi and Hackman, 2017 IEEE WSC<\/a><\/p>\n\n\n\nWarehouse & Distribution Science, Bartholdi & Hackman <\/a><\/p>\n\n\n\nGEODIS slotting optimisation, 52-week rolling analysis <\/a><\/p>\n\n\n\nMHI Annual Industry Report 2024 (with Deloitte)<\/a><\/p>\n\n\n\nAI in distribution operations, McKinsey<\/a><\/p>\n\n\n\nAutomation payback and RaaS, McKinsey<\/a> <\/p>\n\n\n\nHSE Key figures for Great Britain 2023\/24, including MSDs and total cost<\/a> <\/p>\n\n\n\nInterspan to cut reporting time by 90%, Clarus WMS customer story<\/a> <\/p>","protected":false},"excerpt":{"rendered":"Cut warehouse labour costs by reducing travel time, smarter slotting and data-driven planning, not rushed automation, for safer faster fulfilment now.<\/p>","protected":false},"author":207386994,"featured_media":26596,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1578],"tags":[1679],"class_list":["post-10356","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","tag-article-new"],"acf":{"faq_new":"
What is the single biggest lever to reduce warehouse labour cost in picking?<\/b><\/h3>\r\nCut walking. Research shows travel between locations is responsible for about half of manual order-picking time, so minimising distance through slotting, batching, and sensible routing yields immediate savings. Start by placing highest-velocity SKUs near despatch and co-locating common pairs.<\/span> (informs-sim.org)<\/span><\/a>\r\nIs voice-directed picking still worth considering in 2025?<\/b><\/h3>\r\nIt can be, if your environment suits it. Benchmarks from Honeywell indicate up to 35 percent productivity improvement versus legacy methods and up to 50 percent fewer errors, although results vary with product mix, ambient noise, and existing RF processes. Validate with a pilot before scaling.<\/span> (Honeywell Automation)<\/span><\/a>\r\nHow long is a realistic payback for warehouse automation like AMRs or goods-to-person?<\/b><\/h3>\r\nPayback depends on volumes and labour intensity, but several retailers have achieved two to three-year paybacks by using Robotics-as-a-Service to align costs with usage. A structured network-wide approach and clear vendor scope are critical to hit those returns. <\/span>(McKinsey & Company)<\/span><\/a>\r\nHow should 3PLs adjust slotting for seasonality without overstaffing?<\/b><\/h3>\r\nUse rolling demand horizons and per-SKU forecasting to refresh slot assignments before peaks. Leading 3PL approaches analyse 52 weeks of order history and then place higher-velocity items closer to outbound to cut travel and congestion.<\/span> (geodis.com)<\/span><\/a>\r\nHow do ergonomics issues drive labour cost, and what can I track?<\/b><\/h3>\r\nPoor ergonomics increases walking, handling, and rework, which elevates time per line and sick leave. The HSE reports 543,000 workers with work-related musculoskeletal disorders and an estimated \u00a321.6 billion annual cost of work-related ill health and injury, so track walk distance, lift frequency, and near-misses alongside lines per hour. <\/span>(HSE)<\/span><\/a>\r\nAre wage pressures easing in UK transport and storage?<\/b><\/h3>\r\n<\/b>Earnings have remained elevated. ONS Average Weekly Earnings series for transport and storage shows continued increases through 2024 and 2025, so labour-efficiency initiatives remain a priority. <\/span>(Office for National Statistics)<\/span><\/a>"},"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t
Expert insight:<\/strong> \u201cYou must pair system capability with physical reality. If you add SKUs without space, rethink pick faces, replenishment mins and maxes, and whether tote?picking or pallet pick faces suit the demand pattern.\u201d<\/p>\n\n\n\n Where organisations do adopt voice?directed work, industry data indicates meaningful accuracy and productivity gains, but suitability varies by site. Honeywell reports up to 35 percent productivity improvement from legacy methods and up to 50 percent error reduction where voice fits the use case. (Honeywell Automation<\/a>)<\/p>\n\n\n\n Automation should follow a clear cost case. In many mid?sized facilities, process discipline, data?driven slotting, and cross?training can deliver quick wins. For higher volumes or SKU complexity, goods?to?person and AMR solutions can provide variable capacity and remove walking from the process, with retail examples showing payback in roughly two to three years when consumption is structured as Robotics?as?a?Service. (McKinsey & Company<\/a>)<\/p>\n\n\n\n Adoption intent remains high across logistics. The 2024 MHI Annual Industry Report, produced with Deloitte, shows strong five?year plans for AI and robotics across respondents, reinforcing the importance of a roadmap rather than piecemeal pilots. (Locus Robotics<\/a>)<\/p>\n\n\n\n Expert insight:<\/strong> \u201cAutomation\u2019s trade?off is upfront capex against storage density, throughput, and reduced manual handling. You still need a realistic payback plan, not just a machine.\u201d<\/p>\n\n\n\n Voice?directed picking is an established option that can keep hands and eyes free, reduce scanning steps, and improve first?time accuracy. Vendor benchmarks cite up to 35 percent productivity improvement and up to 50 percent error reduction versus legacy methods when correctly deployed. Suitability depends on product mix, ambient noise, and the maturity of existing RF processes. (Honeywell Automation<\/a>)<\/p>\n\n\n\n Slotting is one of the most reliable levers for cutting labour cost because travel time typically accounts for around half of manual order?picking time. Placing high?velocity SKUs closer to despatch and co?locating items that are often picked together reduces walking and truck movements, which directly lowers labour minutes per line. (informs-sim.org<\/a>)<\/p>\n\n\n\n Modern 3PL slotting programmes analyse 52 weeks of rolling demand and apply per?SKU forecasting, then assign locations using distance?minimising rules to cut travel and congestion. This approach is increasingly common in large 3PLs. (geodis.com<\/a>)<\/p>\n\n\n\n Expert insight:<\/strong> \u201cUse transactional pick data through BI to identify fastest movers, then physically place them near your goods-out and set walk sequences accordingly. The physical layout still governs your cost.\u201d<\/p>\n\n\n\n Traditional time?and?motion exercises are slow and quickly outdated. A better approach is continuous measurement of lines per labour hour, travel sequences, and replenishment triggers, then weekly slotting adjustments. Clarus WMS supports this by giving teams real?time visibility and clean data for BI, so you can act on facts rather than periodic studies.<\/p>\n\n\n\n Where organisations implement voice in suitable contexts, independent vendor data suggests up to 35 percent productivity uplift. Treat these as industry comparators rather than a guarantee, and validate with a pilot in your process. (Honeywell Automation<\/a>)<\/p>\n\n\n\n Clarus WMS emphasises real?time visibility, accurate master data, and configurable walk sequences to reduce travel and waiting. It also supports demand pick faces to balance replenishment effort with pick density for each client account in 3PL settings. In one recent customer story, Interspan reports cutting reporting time by about 90 percent after moving from on?premises WMS to Clarus, which freed leaders to focus on operational improvement. (Clarus WMS<\/a>)<\/p>\n\n\n\n Expert insight:<\/strong> \u201cDemand pick faces help absorb seasonal spikes, but you must plan space, replenishment rules, and staffing, otherwise you simply move the bottleneck.\u201d<\/p>\n\n\n\n Dashboards should surface exceptions such as mispicks, repeated long walks, and slow replenishments. Tracking these in real time enables you to correct before overtime accrues and before errors cascade into rework. This is where clean, timely WMS data pays for itself.<\/p>\n\n\n\n When SKU counts grow, process rules remain the same, the cost impact depends on space, pick?face design, and replenishment settings. Use min?max and demand?triggered pick?faces to keep fast movers accessible as accounts scale.<\/p>\n\n\n\n End?to?end visibility across inbound, storage, and outbound helps you prevent idle walking, align labour with demand, and maintain audit trails. This enables realistic incentive schemes and kaizen cycles based on facts, not averages.<\/p>\n\n\n\n Implementing labour cost optimisation with Clarus WMS can transform warehouse productivity, reducing overtime and improving ergonomics with fewer surprises. Imagine a weekly cadence of small, data?driven slotting moves that compound into lasting savings. Contact Clarus WMS for a demo to explore these benefits.<\/p>\n\n\n\n References<\/strong> Using digital twins to unlock end-to-end supply chain growth, McKinsey<\/a><\/p>\n\n\n\n Average Weekly Earnings, series K5B7 (Transport and storage)<\/a><\/p>\n\n\n\n Average weekly earnings in Great Britain: December 2024, ONS<\/a><\/p>\n\n\n\n Honeywell Guided Work Software (voice picking benchmarks)<\/a><\/p>\n\n\n\n Travel time\u2019s share of picking time, Elbert & M\u00fcller citing Bartholdi and Hackman, 2017 IEEE WSC<\/a><\/p>\n\n\n\n Warehouse & Distribution Science, Bartholdi & Hackman <\/a><\/p>\n\n\n\n GEODIS slotting optimisation, 52-week rolling analysis <\/a><\/p>\n\n\n\n MHI Annual Industry Report 2024 (with Deloitte)<\/a><\/p>\n\n\n\n AI in distribution operations, McKinsey<\/a><\/p>\n\n\n\n Automation payback and RaaS, McKinsey<\/a> <\/p>\n\n\n\n HSE Key figures for Great Britain 2023\/24, including MSDs and total cost<\/a> <\/p>\n\n\n\n Interspan to cut reporting time by 90%, Clarus WMS customer story<\/a> <\/p>","protected":false},"excerpt":{"rendered":" Cut warehouse labour costs by reducing travel time, smarter slotting and data-driven planning, not rushed automation, for safer faster fulfilment now.<\/p>","protected":false},"author":207386994,"featured_media":26596,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1578],"tags":[1679],"class_list":["post-10356","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","tag-article-new"],"acf":{"faq_new":"<\/figure>\n\n\n\nDo I Need Automation for My Warehouse Operations?<\/strong><\/h2>\n\n\n\n
<\/figure>\n\n\n\nHow Does Voice?Picking Improve Productivity?<\/strong><\/h2>\n\n\n\n
What Role Does Slotting Play in Travel?Time Reduction?<\/strong><\/h2>\n\n\n\n
Traditional Methods vs. Clarus WMS for Labour Management<\/strong><\/h2>\n\n\n\n
Why Teams Struggle with Labour Cost<\/strong><\/h2>\n\n\n\n
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<\/li>\n<\/ul>\n\n\n\nHow Does WMS Handle Labour Cost?<\/strong><\/h2>\n\n\n\n
<\/figure>\n\n\n\nReal?Time Monitoring<\/strong><\/h3>\n\n\n\n
Scalable Adaptation<\/strong><\/h3>\n\n\n\n
Full Visibility<\/strong><\/h3>\n\n\n\n
Ready to See It in Action?<\/strong><\/h2>\n\n\n\n
<\/p>\n\n\n\nWhat is the single biggest lever to reduce warehouse labour cost in picking?<\/b><\/h3>\r\nCut walking. Research shows travel between locations is responsible for about half of manual order-picking time, so minimising distance through slotting, batching, and sensible routing yields immediate savings. Start by placing highest-velocity SKUs near despatch and co-locating common pairs.<\/span> (informs-sim.org)<\/span><\/a>\r\n
Is voice-directed picking still worth considering in 2025?<\/b><\/h3>\r\nIt can be, if your environment suits it. Benchmarks from Honeywell indicate up to 35 percent productivity improvement versus legacy methods and up to 50 percent fewer errors, although results vary with product mix, ambient noise, and existing RF processes. Validate with a pilot before scaling.<\/span> (Honeywell Automation)<\/span><\/a>\r\n
How long is a realistic payback for warehouse automation like AMRs or goods-to-person?<\/b><\/h3>\r\nPayback depends on volumes and labour intensity, but several retailers have achieved two to three-year paybacks by using Robotics-as-a-Service to align costs with usage. A structured network-wide approach and clear vendor scope are critical to hit those returns. <\/span>(McKinsey & Company)<\/span><\/a>\r\n
How should 3PLs adjust slotting for seasonality without overstaffing?<\/b><\/h3>\r\nUse rolling demand horizons and per-SKU forecasting to refresh slot assignments before peaks. Leading 3PL approaches analyse 52 weeks of order history and then place higher-velocity items closer to outbound to cut travel and congestion.<\/span> (geodis.com)<\/span><\/a>\r\n
How do ergonomics issues drive labour cost, and what can I track?<\/b><\/h3>\r\nPoor ergonomics increases walking, handling, and rework, which elevates time per line and sick leave. The HSE reports 543,000 workers with work-related musculoskeletal disorders and an estimated \u00a321.6 billion annual cost of work-related ill health and injury, so track walk distance, lift frequency, and near-misses alongside lines per hour. <\/span>(HSE)<\/span><\/a>\r\n
Are wage pressures easing in UK transport and storage?<\/b><\/h3>\r\n<\/b>Earnings have remained elevated. ONS Average Weekly Earnings series for transport and storage shows continued increases through 2024 and 2025, so labour-efficiency initiatives remain a priority. <\/span>(Office for National Statistics)<\/span><\/a>"},"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t