Why 93% of Companies Say They'll Automate Their Warehouse, But Only 43% Actually Do

In this episode of Rozmowy Logistyków, Piotr Skobało and Adam Sobolewski discuss 7 reasons why companies don't invest in warehouse automation. Drawing on knowledge from over a dozen projects, they also explain what makes even completed investments hard to call successful.

DECLARATIONS VS. REALITY: THE GAP BETWEEN 93% AND 43%

Industry research shows a striking gap: 84% of companies in Poland say they'll deploy warehouse automation within three years, and 93% of companies in Europe are already considering automating their warehouses — yet only 40-43% of large organizations actually have automated warehouses today. This gap between declaration and deployment has persisted for years, even though the market's voice on the need for automation has long been consistent.

BARRIER 1: SHORT CONTRACTS DON'T COVER A LONG ROI

Logistics operators work on contracts of around 2-3 years, and these have been getting shorter over the last decade — meanwhile, the return on a warehouse automation investment typically takes 5-7 years. The same problem affects retail companies working on annual or two-year contracts with retail chains: the decision horizon is structurally shorter than the investment payback horizon, which alone blocks investment decisions regardless of a project's actual profitability.

BARRIER 2: LOW BOARD TOLERANCE FOR A LONG PAYBACK PERIOD

A newly appointed board member with their own quarterly targets has a hard time accepting a project that will pay back in 4-7 years — even when industry reports (McKinsey, PwC) point to average returns of around 15-25% a year over the longer term. A real example: a retail organization in its fifth year of running automation still hadn't reached payback, which became a point of critical scrutiny for the head of logistics who deployed it — even though the original business plan had assumed exactly 5-6 years.

BARRIER 3: UNPREDICTABLE LABOR AND ENERGY COSTS

Most automation business cases rest on labor cost — but a roughly 50% rise in the minimum wage over the last several years makes long-term estimates highly uncertain, as does the shifting price of energy, which had a completely different weight in the profitability calculation just five years ago.

BARRIER 4: NO PROCESS STANDARDIZATION, AND TECHNOPHOBIA

Many companies run on processes that are the result of accidental growth ("we've always done it this way," piecemeal equipment purchases with no coherent concept) — without standardization, it's hard to even discuss automating a specific process. On top of that comes real, though rarely openly named, resistance from middle-management employees who fear automation means their positions get replaced.

BARRIER 5: UNPREDICTABLE VOLUMES AND ASSORTMENT

A company with revenue in the hundreds of millions of złoty, planning warehouse automation, couldn't answer the question of what it would be selling next year — it had value targets for revenue, but no volume targets broken down by product category. This is a fundamental problem: automation always has boundary conditions on the assortment it can handle (weight, size, shape — e.g. round items roll on conveyors and can't be processed through them), so without a stable assortment forecast, it's hard to even design the right system.

COSTLY LESSONS: WHEN ASSUMPTIONS DRIFT FROM REALITY

At one Polish retail company, an ASRS system deployed for tens of millions of złoty had to be weighted down with bags of salt — because the assortment the company started selling after choosing the technology turned out to be lighter than the detection threshold of the system's weight sensors. At ASOS, a simultaneous rollout of a new WMS and storage system at two locations (the US and Berlin) worked correctly for picking, but put-away took too long, causing delays in receiving and returns processing — the company estimated losses at 25-30 million pounds, and its market cap dropped 40% within a quarter after the delivery problems became public.

SEVEN STEPS TO A SUCCESSFUL ROLLOUT

1. An organized logistics strategy as part of the whole organization's strategy, formally written down with clear assumptions (labor cost growth, volumes) you can revisit years later. 2) Assessing and standardizing operational processes before automating — otherwise you risk "cementing" suboptimal processes into a rigid system. 3) Verifying warehouse infrastructure (floor load capacity, health, safety, and fire requirements) — sometimes this means needing a new location, a project that alone can take a year or longer. 4) A profitability analysis with multiple scenarios, not one rigid calculation. 5) Careful selection of technology and partners — good practice is seeking references beyond those the vendor itself provides, to see projects that aren't flagship case studies. 6) A phased rollout instead of a "big bang" approach — small, fast deployments build trust with the team and the board, making it easier to secure budget for subsequent phases. 7) A stable, competent team running the project — changing key people mid-rollout means losing knowledge of the original assumptions and a real risk to the end result.