What is a continuous innovation programme?

It is a permanent process for identifying, testing and scaling new technologies, rather than a series of one-off projects. It relies on a shared data foundation and clear criteria for deciding which pilots move to production.

What is the difference between a proof of concept and a proof of value?

A proof of concept confirms that a technology works. A proof of value confirms that it delivers measurable business benefits, based on KPIs agreed before the project starts, which makes it a stronger basis for an investment decision.

What is pilot purgatory in manufacturing?

Pilot purgatory describes pilots that succeed technically but never reach production scale. Common causes are unclear business objectives, missing value estimates and pilots that were not designed for deployment across lines or plants.

Why is PLM important for digital manufacturing in aerospace?

PLM holds product definitions, configurations and change history. Integrating it with ERP, MES and other enterprise systems creates a digital thread, so production, quality and supply chain teams work with the same up-to-date product data.

Digital Transformation in Aerospace: From PoC to Value

Digital transformation in aerospace and defence rarely stalls because of technology. It stalls when pilots are launched faster than the business can absorb them. This case study shows how an aerospace and defence manufacturer built a Continuous Innovation Programme on integrated systems, PLM and cloud-based supply chain orchestration, and how a shift from proof of concept to proof of value turned a crowded pilot portfolio into digital manufacturing projects that deliver measurable value.

In short: running many pilots at once only pays off when every pilot starts with a defined business objective, an estimated value and a clear path to scale.

The challenge: faster technology adoption in aerospace and defence manufacturing

The client operates in the aviation and defence industry, a sector with long product lifecycles, strict quality and traceability requirements, and intense competition for technological leadership. Its key challenge was how to accelerate the adoption of modern technologies and remain competitive.

The answer was a Continuous Innovation Programme, set up as the foundation of a new business model. Its core principle was the continuous testing of state-of-the-art technologies, so that the company could bring increasingly innovative products to market.

Why digital transformation in aerospace needs a continuous innovation programme

In many manufacturing sectors, digital transformation is delivered as a sequence of separate projects. In aerospace and defence, that model struggles to keep pace. New materials, connected equipment, simulation tools and AI models appear faster than a traditional project cycle can evaluate them.

A continuous innovation programme works differently. It is a permanent process for selecting, testing and scaling technologies across engineering, production and the supply chain. To work, it needs a shared data foundation. Without integrated systems, every pilot starts from scratch and every successful result remains an isolated experiment.

The solution: systems integration as the foundation for digital manufacturing

To reach this goal, the company partnered with TT PSC, a systems integration specialist. The work covered three areas that together form the backbone of connected operations.

Integrating enterprise systems with PLM

Together, the teams integrated all enterprise solutions with a product lifecycle management (PLM) system. In aerospace and defence, PLM sits at the centre of the digital thread. It holds product definitions, configurations and change history, the data that systems such as ERP, MES and quality management depend on. With PLM connected to the rest of the enterprise, every innovation project can work with consistent, up-to-date product data. Our article on PLM in aerospace explains this role in more detail.

Orchestrating the supply chain in the cloud

Another key element was orchestrating the supply chain using cloud technologies. A shared cloud environment enabled smooth collaboration among all stakeholders, which is a prerequisite for supply chain digitalisation in a sector with complex, multi-tier supplier networks.

Applying Industry 4.0 technologies

The company also used a wide range of Industry 4.0 technologies to increase process efficiency and drive innovation. In a smart factory, this typically means Industrial IoT connectivity for machines and equipment, production analytics, and data and AI models that turn operational data into decisions.

Implementation challenge: ten pilots at once and the risk of pilot purgatory

Despite ambitious goals, the programme soon met an obstacle. The company was running at least 10 proof of concept (PoC) initiatives simultaneously, and some of them were launched without sufficient business preparation.

As a result, many PoCs had little chance of evolving into valuable final solutions, which limited their effectiveness and relevance to the company. This pattern is often called pilot purgatory: pilots that succeed technically but never reach production scale, because nobody defined what success should mean for the business.

The correction: from proof of concept to proof of value

In response, the company shifted its focus to clearly defined business objectives and justification of project value. The most important change was accurately estimating the value of each project before initiation. This led to better resource management and higher success rates.

In practice, the key question changed from 'does the technology work?’ to 'is it worth deploying?’. The table below summarises the difference.

Aspect	Proof of concept (PoC)	Proof of value (PoV)
Key question	Does the technology work?	Does it deliver measurable business value?
Success criteria	Technical feasibility	Business KPIs agreed before the start
Scope	Isolated test	Designed with scaling and deployment in mind
Main risk	Getting stuck in the pilot phase	A longer preparation phase
Outcome	A technical verdict	An investment decision

For a wider view of how pilots reduce investment risk, see our guide to proof of concept projects.

Want to know the value of a pilot before it starts?

Use the ROI estimator on our Digital Manufacturing page to size savings in downtime, OEE, maintenance, energy and quality, then see how TT PSC takes manufacturers from connected systems to AI-driven operations, one measurable phase at a time.

Estimate your ROI

Results: a more agile innovation programme

Launching multiple PoC projects without proper business preparation had initially caused inefficiencies. Once the company prioritised business goals and project value, it was able to manage its innovation initiatives better. Resources were used more efficiently, project outcomes improved significantly, and projects became more impactful and delivered greater value to the company.

Key lessons for digital transformation in aerospace and defence

Four lessons from this programme apply to any manufacturer building an innovation pipeline:

Define business objectives precisely. Realistically assessing expected results, with a focus on proof of value rather than proof of concept, clarifies the benefits of implementing new technology.
Define the technical scope accurately. Effective budget and schedule management ensures a favourable cost-to-value ratio, optimises resources and minimises unnecessary expenses.
Make innovation serve business needs. New technologies are exciting, but their practicality and usefulness in day-to-day operations should be the primary motivation. This avoids the risk of getting stuck in the pilot phase.
Design pilots for scale. Even pilot initiatives should be planned with future scalability and deployment in mind.

Scaling digital manufacturing beyond the pilot phase

A pilot designed for scale needs an architecture to scale into. In most plants, that means connected operations in which each layer has a clear role:

PLM and the digital thread provide a single source of truth for product data and configurations.
Manufacturing execution systems (MES) and manufacturing operations management (MOM) turn that data into production orders, work instructions and quality records on the shop floor.
Industrial IoT connects machines and industrial automation, so production data is collected automatically and in context.
Data and AI turn this data into production analytics, predictive maintenance and quality forecasts.
Digital twins let teams test changes to products and processes virtually before committing resources.

When these layers are integrated, a successful pilot can be rolled out across lines and plants without rebuilding integrations each time. This is how a smart factory grows: step by step, with each proven use case adding to a shared foundation. Our digital transformation in manufacturing roadmap describes this path phase by phase, and our overview of Industry 4.0 use cases shows which applications deliver results first.

Summary

Digital transformation in aerospace and defence depends as much on disciplined portfolio management as on technology. By integrating its enterprise systems with PLM, orchestrating the supply chain in the cloud and applying Industry 4.0 technologies, the client built a strong foundation for continuous innovation. The decisive step was the shift from proof of concept to proof of value, so that every pilot started with a clear business objective and a path to scale.

If you are planning a similar programme, TT PSC can help you connect engineering, production and supply chain data into one digital manufacturing foundation.

Frequently asked questions

It is the integration of digital technologies such as PLM, cloud platforms, Industrial IoT and data analytics across engineering, production and the supply chain. The goal is to shorten development cycles, improve quality and traceability, and help manufacturers adopt new technology faster.

Digital Transformation in Aerospace and Defence: Scaling a Continuous Innovation Programme