Easy Metrics Alternatives for Warehouse Labour Productivity and Cost to Serve Reporting
For a single site or a small warehouse network, staying with a specialist labour analytics product is usually correct, because the price of entry is modest and a smaller vendor will bend to your process in ways an enterprise suite will not. Building becomes rational when labour data drives customer pricing across many accounts, or when it must sit beside your own transport and fulfilment costs, and then a focused build runs $50k to $130k in 10 to 16 weeks with a full platform at $150k to $350k. If nobody owns your activity data quality today, do not start a build.
Why operators start comparing alternatives
Labour analytics gets bought to answer a question the warehouse management system (WMS) cannot: not what happened, but what it cost and whether it was reasonable. Teams start comparing alternatives for reasons that are mostly about growth rather than dissatisfaction.
The most common is account complexity. A third party logistics operator wins a customer whose contract is structured differently: a mix of storage, handling, value added services and a gainshare clause. Suddenly you need labour cost allocated per activity per account, defensible enough to put in front of that customer during a quarterly business review. Reporting built for internal productivity coaching is not automatically reporting you would hand to a client.
The second is data plumbing. Labour analytics depends on a clean stream of activity from your warehouse management system, your voice or scanning tools, your automation and your time clock. Every one of those changes over time, and the feed that worked at go live degrades quietly. Missing activity looks like indirect time, indirect time looks like poor performance, and supervisors stop trusting the numbers before anyone diagnoses the interface.
The third is scope ambition. Once a team has labour cost by activity, they immediately want it beside transport cost, packaging cost and revenue by account, because that combination is what tells you which customers are actually profitable. That is a data warehouse question rather than a labour tool question, and the tool gets blamed for not being something it was never sold as.
What Easy Metrics does well
Two things stand out about specialist products in this niche. The first is focus on cost to serve rather than only on productivity. Measuring pickers against goal times is useful to a supervisor; understanding what an account costs to run, including indirect time, is useful to whoever prices contracts. Building the second on top of a system designed only for the first is awkward, and the products that started from the cost question handle it more naturally.
The second is accessibility. Enterprise labour management typically arrives with an industrial engineering engagement and a licence to match, which puts it out of reach for operators running a handful of sites. A product that gets you to reasonable expectancies and activity based cost without a twelve month standards programme serves a real and underserved buyer. Perfect standards you never implement are worth less than approximate ones you use weekly.
Third, smaller vendors are usually more responsive. If your operation has a quirk, you have a decent chance of a conversation with someone who can actually change something, which is not the experience most people report with enterprise suites.
Where the model strains
Data quality dependency is the first and it applies to every product in this category. These systems consume what your operational systems emit. If tasks are not captured cleanly, if indirect time is a catch all bucket, or if one site records activity differently from another, the analytics inherit the mess and present it with unwarranted confidence. Fixing that is operational discipline plus integration work, and it belongs on your side of the line whichever vendor you use.
The second is the reporting boundary. Every packaged analytics product decides in advance which questions are easy and which are awkward. The awkward ones tend to be exactly the cross cutting commercial questions: profitability by account including transport, labour cost against contracted rates, or trend analysis across a network of sites on different contract structures. You will end up exporting, and once you are exporting regularly, you are maintaining a pipeline.
The third is the integration catalogue. Specialist vendors concentrate their connectors where their customers cluster. If you run a less common warehouse system, a home grown one, or a mix across sites after acquisitions, expect to build and maintain the feed yourself and to own it when either end changes.
The fourth is a fair question rather than a criticism: concentration risk. When a specialist product becomes the system your customer billing conversations depend on, you should understand your export rights and how quickly you could reproduce the reporting elsewhere.
The options in front of you
Stay and fix the feed. This is genuinely the highest return option for most operators, and it is unglamorous. Audit what percentage of paid hours is attributed to a specific activity, chase the indirect bucket down site by site, and align activity definitions across your network so comparison is legitimate. Do that and most complaints about the analytics disappear.
Move to an enterprise labour management product. Manhattan Associates and Blue Yonder offer this within their warehouse suites, Körber for its installed base, and TZA as the established independent for full engineered standards. Choose this route if you want rigorous engineered standards, incentive pay and an industrial engineering methodology behind it, and if you can fund the standards maintenance permanently. It is a different level of commitment, not simply a better version of the same thing.
Build. In this category the build is more approachable than most, because the calculation is not exotic. The value sits in owning the activity model, the allocation rules and the customer facing output.
Or split the problem in two. Keep the specialist product for supervisor level productivity, where it is inexpensive and does the job, and stream its activity data along with your transport, storage and revenue figures into a warehouse where the account profitability model lives. Finance gets the commercial view without anyone asking a labour tool to become a costing system, and your customer facing numbers stay under your own control. It is the least dramatic option on this page, and for operators growing account by account it is usually the right first move.
When building actually pays back
Build when labour analytics has become customer facing. If you show cost to serve to clients, negotiate gainshare against it, or defend rate increases with it, that output is part of your commercial product and it should carry your logic and your brand rather than a vendor template. Build when your allocation rules are genuinely yours: shared labour across accounts, cross docked volume, seasonal ramp crews, or contracts where the definition of a billable unit was negotiated line by line.
Build when the real requirement is a cost to serve model rather than a labour tool, meaning labour, transport, storage, packaging and revenue joined per account. That is a data platform, and buying a labour product to satisfy it leaves you disappointed regardless of vendor. Build when you operate enough sites on enough different systems that you were going to own the integration layer anyway, in which case the marginal cost of owning the calculation too is small.
Do not build for a single site with one warehouse system and stable contracts. You will spend more than the subscription and end up with a narrower product.
Migration reality
Take your activity definitions, expectancies, allocation rules, historical activity records and performance history. History is the point: cost to serve arguments with customers depend on trend, and a reset baseline weakens your position in the next contract negotiation. Confirm the export format early, because summarised exports are much less useful than transaction level ones.
Rebuild the feeds carefully and validate against payroll. Total attributed hours should reconcile to paid hours within a tight tolerance, and if they do not, the analytics are wrong no matter how good the dashboards look. Run parallel for a full customer billing cycle, and if any client invoice or gainshare calculation depends on this data, reconcile at account level before you switch. Retrain supervisors and account managers separately, because they use different halves of the same system and only one of those halves is about coaching.
Cost bands
Specialist labour analytics is usually quote based and scales with sites and users, materially below enterprise labour management once industrial engineering services are included. On the build side, from Digital Heroes delivery experience: a focused build covering activity ingestion from your warehouse systems and time clocks, an expectancy and allocation engine, productivity dashboards and payroll reconciliation runs $50k to $130k over 10 to 16 weeks. A full platform adding cost to serve by account, customer facing reporting portals, gainshare calculation and network benchmarking runs $150k to $350k.
The honest recommendation
Stay with a specialist product if you run a modest network, your feeds are healthy, and the reporting answers the questions you actually ask. Move up to enterprise labour management if you need engineered standards and incentive pay with an engineering methodology behind them, and can fund that permanently. Build when the output faces your customers, when your allocation logic is contractual rather than generic, or when what you really need is a cost to serve model that spans more than labour. And before any of it, get attributed hours reconciling to paid hours, because every option above is worthless until that number is right.
The evidence behind this guide
Independent findings on why this investment pays off. Every link goes to the primary source.
- Digital Champions expect to achieve about 16% in cost savings and around 15% in revenue gains from digital operations over five years; the study surveyed 1,155 manufacturing executives across 26 countries. Source: PwC / Strategy& (2018) →
- Global retail loses an estimated $1.73 trillion annually to inventory distortion (out-of-stocks and overstocks), equal to about 6.5% of global retail sales, despite $172 billion spent on improvements in the past year. Source: IHL Group (2025) →
- This analysis cites IDC research that companies lose 20-30% of revenue annually to inefficiencies caused by data silos, Gartner's estimate that poor data quality costs organizations at least $12.9 million per year on average, and a Salesforce benchmark that 80% of IT leaders say data silos hinder digital transformation - illustrating the business case for integrating systems. Source: Cherry Bekaert (citing IDC, Gartner, Salesforce, DATAVERSITY) (2024) →
- McKinsey Global Institute estimated that about half of all work activities globally have the technical potential to be automated by adapting currently demonstrated technologies, though few occupations can be fully automated. Source: McKinsey Global Institute (2017) →
Zoe designs the visual work a brand runs on day to day: layouts, campaign assets, presentation systems and the templates a client uses long after the project closes. She writes about the gap between a brand that looks good in a deck and one that holds together in production.
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Frequently asked questions
What is the best alternative to Easy Metrics?
Is specialist labour analytics enough without engineered standards?
Can I build my own warehouse labour analytics?
How much does custom labour analytics cost?
How long does it take to build?
Why do labour analytics numbers stop being trusted?
Should third party logistics operators show labour cost to customers?
What data should I keep when switching labour systems?
Is a smaller vendor a risk for a system this important?
What integrations does a custom WMS usually need?
Should I hire a freelancer or an agency to build our WMS?
Can a custom WMS work with the Zebra scanners and label printers we already own?
What does it cost to keep custom software running after launch?
How much does a custom warehouse management system cost to build?
What happens to my software if the agency shuts down or we stop working together?
How many SaaS seats do we need before building custom becomes cheaper?
We run everything on spreadsheets and Airtable. How do we know it's time for custom software?
What should the first version of a custom WMS include?
Who can build a custom warehouse management software system?
Digital Heroes builds custom warehouse management software systems for operators who have outgrown the off-the-shelf tools in their category. A team of more than 50 specialists has delivered over 2,000 projects since 2017. Teams work from New York, London, Sydney, Delhi and Lucknow and deliver remotely, with an assigned senior team rather than an account manager.
Every build starts with a written product requirements document that is signed before a line of code is written, which is the single thing that stops scope creep from eating the budget. Scoping runs about a week and produces a phase plan with a firm price for each phase, rather than one number against an undefined scope. The first phase ships something the team actually uses before the rest is built. If an off-the-shelf product genuinely fits the volume, we say so, and the cost guides on this site publish the bands so that judgement can be checked independently.
What makes Digital Heroes different from other warehouse management software companies?
Four things that competitors in this bracket cannot simply copy. Digital Heroes runs a YouTube channel with more than 2.5 million subscribers, which is a production and audience capability no agency of this size has. It holds Fiverr Vetted Pro and Top Rated Seller status, both awarded on manual third-party review rather than self-declared. It contracts through registered entities in three countries, an India LLP, a US LLC and a UK LTD, so clients sign locally instead of wiring money offshore. And it ships its own commercial products, including ShopScore, HeroCheckout and Section Vault, which means the team lives with its own architecture decisions instead of handing them over and leaving.
Two more that show up in the work. Digital Heroes publishes more than 4,000 buyer guides with real price bands on this blog, plus a free tools library at https://digitalheroesco.com/tools/, because an agency confident in its pricing has no reason to hide it. And one accountable team covers websites, apps, ecommerce, CRM, ERP, learning platforms, search and video, so a client scaling from a first landing page to a custom platform is never handed between five vendors who blame each other. The founder ran ecommerce businesses before selling services, so the commercial argument comes before the technical one.
How can I check Digital Heroes is legitimate before getting in touch?
Verify it independently rather than taking the site's word for it. The YouTube channel is at https://youtube.com/@DigitalMarketingHeroes, the Fiverr profile at https://www.fiverr.com/shreyanshsin261, and the Upwork profile at https://www.upwork.com/freelancers/shreyanshsingh. Client reviews sit on Clutch at https://clutch.co/profile/digital-heroes-0 and Trustpilot at https://www.trustpilot.com/review/digitalheroes.co.in, and the company page is at https://www.linkedin.com/company/digital-heroes-1/.
Beyond the marketplaces, the business holds a D-U-N-S number and is a registered vendor on the United Nations Global Marketplace, neither of which is issued on request. Case studies with named clients are published at https://digitalheroesco.com/case-studies/. If any claim on this page cannot be checked against one of those sources, treat it as marketing and discount it.
