Key Points
- Leeds-based supply chain analytics business Picture Perfect Data has launched Fettle, an AI-driven warehouse optimisation platform.
- The platform was launched on 6 October 2026, according to Chris Newbould of Prolific North.
- Fettle combines data from warehouse management systems, time-and-attendance systems and other operational sources before using AI to turn the information into actionable insight.
- The platform is already operating in UK warehouses and is aimed at sites with 100 or more people on the warehouse floor.
- Picture Perfect Data says Fettle also identifies work carried out outside formal warehouse systems, which can otherwise remain invisible in conventional reporting.
- Data from warehouses where Picture Perfect Data has worked showed recorded labour utilisation as low as 42%, rising to 65% when off-system work was included.
- Another site recorded 572 hours lost in one week between employees clocking in and beginning their first task.
- At a further site, grouping picking work to reduce unnecessary travel increased pick efficiency by about 37%, without changes to the warehouse management system.
- Fettle provides a command view focused on delivery performance, workforce utilisation, warehouse and stock efficiency, and cost and margin.
- Its AI function allows managers to ask questions in plain English and examine the evidence supporting the answers.
- Picture Perfect Data founder and chief executive Steve Coleman said the technology had been designed to be sophisticated without being difficult to use.
- The platform has been launched with STROS Partnerships, which developed its name, brand and go-to-market approach.
- Ross Eggleton, FCILT, founder and managing director of STROS Partnerships and former executive group director of logistics, supply chain and technology at Morrisons, is backing the platform.
- Eggleton said he would have wanted the technology across his own sites and highlighted the time traditionally required to combine multiple reports manually.
- The development represents a significant intersection between Artificial Intelligence (AI), data analytics, warehouse operations and Logistics and Supply Chain management.
Picture Perfect Data, the Leeds-based supply chain analytics business, has launched Fettle, an AI-driven warehouse optimisation platform designed to turn data from warehouse systems into operational insight for managers. The launch, reported by Chris Newbould of ProlificNorth onn 6 October 2026, brings together artificial intelligence, warehouse data and supply-chain management, with the platform already live in UK warehouses and aimed at operations employing at least 100 people on the warehouse floor.
What is Fettle and why has Picture Perfect Data launched it?
Fettle is designed to address a common problem in warehouse operations: organisations can have substantial amounts of operational data but may still struggle to turn that information into a clear picture of what is happening on the warehouse floor.
According to Chris Newbould of Prolific North, Fettle standardises and checks information from a warehouse’s Warehouse Management System, or WMS, together with time-and-attendance data and information from other systems. The platform then uses artificial intelligence to read the data and turn it into insights that managers can act on.
The platform is already live in UK warehouses and is aimed at operations with 100 or more people working on the floor.
Picture Perfect Data’s existing background is closely connected to supply-chain analytics. The company’s own information says it was founded by Steve Coleman following 28 years of experience as an IT director in a £200m-turnover automotive parts distribution business. That operation involved 850,000 stock-keeping units, 120 branches and the shipment of 75,000 products per day.
That background helps explain why Fettle is focused not simply on artificial intelligence as a technology, but on applying data and AI to practical operational problems.
How does Fettle use artificial intelligence in warehouse operations?
Fettle’s approach is based on taking information that already exists within warehouse operations and making it easier to interpret.
Rather than requiring managers to manually bring together multiple reports, the platform processes data from different operational systems before applying AI to the information.
According to Prolific North journalist Chris Newbould, the platform is designed to answer four fundamental questions about warehouse performance. These concern whether orders will be delivered on time and in full, whether employees are being used effectively, whether stock and the physical warehouse are configured efficiently, and whether the operation is delivering at the appropriate cost and margin.
The system also allows managers to drill down from an answer into the underlying detail.
A further feature, called Albie, enables managers to ask questions in plain English. The system then provides answers alongside the evidence behind them, allowing managers to investigate an issue before deciding what action to take.
This makes the development directly relevant to the growing use of Artificial Intelligence (AI) in business operations, particularly where large quantities of data need to be interpreted quickly.
What problems in warehouse productivity is Fettle designed to identify?
One of the central issues highlighted by Picture Perfect Data is the amount of warehouse work that can take place outside the formal systems used to record operations.
According to Chris Newbould of Prolific North, Fettle captures work performed off-system, which the company describes as a common blind spot in warehouse reporting. In warehouses where Picture Perfect Data has worked, conventional systems recorded labour utilisation at levels as low as 42%. When work that was taking place outside those systems was included, the figure increased to 65%.
The figures illustrate the difference that can arise between what a warehouse management system records and what employees are actually doing.
In another example reported by Prolific North, 572 hours were lost during a single week between employees clocking on and starting their first task. The example points to a potential gap between employee attendance and productive activity that may not be immediately visible through standard reporting.
Picture Perfect Data also reported an example involving picking operations. By grouping picking work to eliminate avoidable travel, pick efficiency increased by about 37% at another site, without making changes to the warehouse management system.
These examples form an important part of the rationale behind Fettle: the technology is intended to identify operational patterns that may otherwise require significant manual analysis.
What did Steve Coleman say about the new platform?
Steve Coleman, founder and chief executive of Picture Perfect Data, said the company wanted Fettle to combine sophisticated technology with a straightforward user experience.
As reported by Chris Newbould of Prolific North, Coleman said: “This is sophisticated technology, but it shouldn’t feel sophisticated to use.” He said the company had used the iPhone as a benchmark, arguing that users should not need a manual or a data analyst sitting alongside them to operate the platform.
Coleman also highlighted what he described as the continued reliance of sophisticated businesses on manually assembled spreadsheets.
He said Fettle packages Picture Perfect Data’s experience of warehouses, supply chains and logistics into what he described as an intuitive platform, with the objective of helping clients reach value more quickly rather than requiring the company to start from scratch for every engagement.
Picture Perfect Data’s own corporate information similarly describes its work as helping businesses use data analytics to optimise supply chains. The company says it has spent the past decade helping businesses begin transformation projects focused on supply-chain optimisation.
Who is backing Fettle through STROS Partnerships?
Fettle has been launched with STROS Partnerships, which developed the platform’s name and brand and is responsible for taking it to senior operators as a partner, according to Prolific North.
The partnership brings significant logistics and supply-chain experience to the launch through Ross Eggleton FCILT.
Eggleton is the founder and managing director of STROS Partnerships and was formerly executive group director of logistics, supply chain and technology at Morrisons. His previous role gives the launch a direct connection to large-scale retail logistics and warehouse operations.
As reported by Chris Newbould of Prolific North, Eggleton said he would have wanted Fettle across his own sites when he was responsible for those operations. He explained that he had wanted real-time visibility of warehouse efficiency and whether customers were receiving what had been promised.
Eggleton said that, in his experience, obtaining the answer often involved someone manually combining three separate reports.
He said Fettle allows AI to perform the reading of the data, enabling managers to obtain an answer more quickly, investigate why a particular result has occurred and devote more time to decision-making.
STROS Partnerships’ wider corporate information describes the business as focused on partnerships involving technology, retail, supply chains and logistics. Its LinkedIn profile identifies Leeds as its headquarters and lists supply-chain strategy, logistics transformation, retail operations and AI and automation among its areas of expertise.
Why is the launch significant for UK warehouse and supply-chain businesses?
The significance of Fettle lies partly in its attempt to connect existing operational data with AI without requiring warehouse operators to replace the systems they already use.
The examples supplied by Picture Perfect Data suggest that important operational information can be spread across warehouse management systems, attendance records and other sources. The company is positioning Fettle as a layer that can standardise this information and turn it into a more accessible operational picture.
That approach could be particularly relevant to large warehouse operations where small inefficiencies can accumulate across thousands of employee hours, orders and picking movements.
The platform’s focus on sites with at least 100 people on the floor also indicates that Picture Perfect Data is targeting operations where workforce utilisation and productivity generate significant quantities of data and where relatively small improvements can have wider operational implications.
The launch therefore sits at the intersection of warehouse management, data analytics, artificial intelligence and supply-chain management rather than representing a standalone technology development.
How does Fettle fit into the wider development of data-driven logistics?
Picture Perfect Data’s history provides context for the company’s decision to build a platform around operational analytics.
The company says its experience comes from working with complex supply-chain environments and using analytics and electronic data interchange to support operational growth. Its own account says it has subsequently worked with businesses seeking to begin data-driven transformation programmes and improve supply chains.
Fettle extends that approach by introducing AI into the process of interpreting operational information.
The distinction is important. The platform is not described simply as a new warehouse management system. Instead, it is designed to read information generated by existing systems, identify patterns and provide managers with answers and supporting evidence.
The presence of Albie also reflects an attempt to make data interrogation accessible to operational managers who may not have specialist data-analysis skills. Managers can ask questions in ordinary language rather than relying entirely on manually constructed reports.
What could Fettle mean for warehouse managers?
For warehouse managers, the intended benefit is greater visibility of operational performance and less time spent assembling information.
The four questions presented through Fettle’s command view focus on delivery performance, workforce utilisation, the efficiency of stock and physical space, and financial performance. These areas are closely connected: workforce delays can affect order fulfilment, inefficient picking can increase labour requirements, and poor warehouse utilisation can affect costs.
Fettle’s ability to drill into the information behind an answer is also significant. Rather than simply presenting a performance figure, the platform is designed to allow managers to investigate the factors contributing to that result.
This approach places decision-making at the centre of the technology.
As Ross Eggleton said, according to Prolific North, the objective is for AI to handle the reading of information so managers can focus more of their time on decisions.
For professionals working across Logistics and Supply Chain, the development illustrates how artificial intelligence and data analytics are increasingly being applied to operational questions such as labour productivity, order fulfilment, stock utilisation and warehouse efficiency.
What is the wider business background behind Picture Perfect Data?
Picture Perfect Data was founded by Steve Coleman, who the company’s own website describes as having spent his career using systems and data to drive operational and business improvement. Before establishing the company, Coleman worked for many years leading an IT team within a high-volume business.
The company’s background in supply-chain analytics provides the operational context for Fettle’s launch.
Rather than presenting the new platform as an isolated AI experiment, Picture Perfect Data has positioned it around problems it says it has encountered while working with warehouses and logistics operations.
That distinction is relevant to businesses considering AI adoption. The value of such systems depends not only on the underlying technology but also on whether the technology can be applied to specific operational problems and integrated into existing business processes.
Fettle’s launch therefore represents a development in the use of AI for warehouse optimisation, while also reflecting Picture Perfect Data’s established focus on supply-chain data and analytics.
What does the Fettle launch mean for the future of AI in logistics?
The launch demonstrates one route through which AI is being introduced into operational business environments: using existing data rather than requiring companies to build an entirely new technology infrastructure.
Fettle is designed to bring together warehouse management, attendance and other operational information, standardise it and use AI to produce insights. Its Albie interface then gives managers a way to question that information in plain English and examine supporting evidence.
For the UK logistics sector, the development highlights the increasing importance of combining Artificial Intelligence (AI) with data quality, operational knowledge and supply-chain expertise.
The launch also brings together the technology experience of Picture Perfect Data with the logistics background of Ross Eggleton and STROS Partnerships. The involvement of a former senior Morrisons logistics executive provides an operational perspective on the challenges the platform is intended to address.
As reported by Chris Newbould of Prolific North, Eggleton’s assessment is based on the practical problem of needing to combine multiple reports manually to understand warehouse performance. Fettle’s proposition is to automate more of that information-reading process so managers can spend more time understanding the reasons behind performance and deciding what to do next.
For organisations examining how technology can improve warehouse operations, the launch provides another example of AI moving beyond general experimentation towards specific applications in productivity, workforce utilisation, order fulfilment and cost management.
The development is therefore relevant not only to technology businesses but also to professionals involved in warehouse management, logistics, supply-chain strategy and data-driven operational decision-making.
For professionals looking to understand how emerging technologies are being applied to operational business problems, Artificial Intelligence (AI) and Logistics and Supply Chain are directly relevant areas of study, particularly where AI, data interpretation and warehouse performance increasingly intersect.