At Smart Manufacturing Week 2026, Alex Lee, Data Governance Lead, Ops, British American Tobacco (BAT), sat down with The Manufacturer to discuss the role data is playing in shaping the company’s vision for the future.
At the turn of the decade, BAT launched its A Better Tomorrow vision to build a smokeless world, where smokers have migrated from cigarettes to smokeless alternatives. The company aims to be a predominantly smokeless business – and have 50% of revenue in non-combustible products – by 2035.
This strategy is built around three pillars of priorities: Delivering Quality Growth emphasises the transition to a more balanced focus on top-line and bottom-line delivery, centred around BAT’s brands and innovation, and continuing to seek long-term opportunities beyond nicotine.
Building a Sustainable Future is focused on seeking to actively migrate adult smokers, who would otherwise continue to smoke, from cigarettes to smokeless alternatives responsibly. Science will be a primary driver of BAT’s efforts, supported by more active external engagement with regulators and other key stakeholders, while embedding sustainability across the organisation.
And this is built around the third pillar of Dynamic Business; building a future-fit, organisation and ensuring the business is efficient and effective in all its operations.
To achieve its mission, BAT is focused and has invested heavily in becoming a truly data-driven organisation. And it’s here that Alex picks up the story.
BAT’s Sacheon factory in South Korea
What does good data governance look like?
AL: We use traditional KPIs and data quality reports. Every member of our business has access, so anyone can measure their own data quality and feed it into the leadership teams and systems. We also have our corporate identity elements, where we will look at improving the quality within those data sets, rather than just looking at completeness rules, and we’re using a variety of tools to help us do that, deploying AI and self-healing data models etc.
We’re obviously a huge company, with many different cultures and regional barriers, people working across borders, etc. As such, we have found that our data maturity within different areas varies, and so currently, we’re undertaking a really large upskilling project across the workforce, in particular within our factories.
Over the last three years, I’ve been working heavily on bringing all our factories up to the same base level of data maturity, and making sure that all our data sets are aligned. This will ensure that we’re measuring the same rules for each data set across the factories, so we have one source of truth for the organisation as far as manufacturing is concerned.
How is the use of data changing?
We’re always increasing our data sets, so when new technology comes into a factory, there’s obviously a new set of characteristics that we’ll need to maintain against, so that we have the required visibility of what that particular machine is doing within the manufacturing setting.
In addition, various end markets will have individual challenges; different legislation can come in, for example, where we’ll need to track the data and make sure that it’s adhering to that legislation. It’s these increased data sets that are essentially driving our programme of upskilling across the business to ensure we have the necessary capabilities to manage that extra workload.
And of course, a key part of that is around the ownership, responsibility and accountability for business critical data. Therefore, we’ve identified our critical data elements (CDEs), and we have clear owners and maintainers all mapped out within our global processes, top level domains (TLDs) and global standards. This means that, within our business, we know precisely the owner and maintainer of any given data set, and where that sits within the business.
Over the last three years, I’ve been working heavily on bringing all our factories up to the same base level of data maturity, and making sure that all our data sets are aligned.
This will ensure that we’re measuring the same rules for each data set across the factories, so we have one source of truth for the organisation as far as manufacturing is concerned.
Alex Lee, Data Governance Lead, Ops, British American Tobacco (BAT)
So when we come to spotting issues within that structure, we know who to go to straight away to get that corrected. We have very clear governance around our data, which is backed up by global standards and the individual teams managing it.
As data governance lead, if anything new comes into the business, it will pass through my team to create the governance frameworks around that and to back up any new data set.
What role is AI playing around data quality and governance?
At the moment we are operating quite traditionally, measuring compliance to certain rule sets. However, we’re also starting to deploy AI tools within our systems, not just to measure the quality of our data, but actually whether it’s the correct parameter to be maintained in the first place; it’s not just something that’s passing a rule.
We’re also working on process improvements within our material supply teams. For our ESG reporting, for example, we’re going out to our suppliers prior to SKU creation to get weights, dimensions etc, and that then feeds into our Scope 3 reporting. It’s part of our mission to try and do everything smarter and using AI to do the heavy lifting is a key part of this.
We’re not deploying what I would call ‘pretty AI’. Everything we do has to serve a purpose within the organisation. And, prior to deployment it will also need to pass through a rigorous and clear governance process.
That means that the sign-off for any AI deployment won’t be the sole domain of the data team. Rather, there will be a variety of different departments across the business who will be involved to ensure we have something that is fit for purpose, has a clear business case backing it up, and is suitable and future-proof for the business moving forward.
How is the workforce changing to adapt to an increasingly data-driven business?
We aren’t just administering training to certain areas. We are upskilling every member of the workforce, from our line leads in individual factories, all the way up to site managers, and then on to the leadership team. Everyone has to do a set amount of training.
This is also backed up by focus groups. These are both cross-functional, which will share best practice within departments, but will also be deployed across other areas of the business.
We also have lead SMEs and what we call ‘SPOCs – single points of contact’, which are sat within geographical locations. They are the real oracle of the data and are the ones that will assist with training and deploying new platforms, etc. within our wider teams.
It’s fair to say that everyone sees BAT as a tobacco company. In actual fact, it’s the data that is the backbone of our business, and without good data, we won’t be able to produce our products and get them to the consumer.
As mentioned, we now have a far greater emphasis on upskilling and training people, so that we are equipped with the necessary skills to be able to deploy these new tools and planning systems.
We’re also on the verge of migrating our planning system to one that is more fit for purpose, with our current legacy system approaching the end of life. This will enhance our ability to knowledge share across different teams and global locations, to gain business-wide access to process improvement ideas around key functions such as plant maintenance for example.
As a result we’re at a place where we’re collecting huge volumes of geographical information from all our facilities, handpicking what would fit best within the wider industry, and then deploying it. BAT is a really collaborative place to work at the moment, with lots of knowledge sharing, and cross functional teams working together on different projects.
We’re really not a tobacco company anymore; we’re more into digital, as that is what is driving our products, and moving us towards our better tomorrow.
Launched in 2018, Velo has grown to become a leading oral nicotine product now sold in 49 markets
A data-driven future
BAT’s ambition is to have 50 million consumers of its smokeless products by 2030 and the company has already made good progress towards these targets, with 34.1 million consumers of smokeless products thus far and revenue from these accounting for 18.2% of group revenue, as at 31 December 2025.
For some time manufacturers have known that data is the fuel that powers any digital transformation strategy but it’s clear that the focus has migrated beyond the mere numbers. A particularly insightful quote heard during Smart Manufacturing Week was that: “It used to be all about data, data, data. Now it’s about context, context, context.”
For BAT, data is becoming a critical enabler of the company’s transformation into a future-focused, predominantly smokeless business, but governance, quality and ensuring that the data is fit for purpose has shifted the whole conversation into another sphere of importance.
Data is proving to be far more than a supporting function; it is becoming a strategic asset that underpins decision-making, operational performance and future growth. From establishing robust governance frameworks and improving data quality to deploying AI-driven tools and building workforce capabilities, BAT is creating the foundations needed to operate effectively in an increasingly digital manufacturing environment.
For Alex, the success of this journey is not solely dependent on technology. Equally important is ensuring that employees across the organisation understand the value of data, have the skills to work with it effectively and take ownership of the information that drives business-critical processes. By creating clear accountability, standardising data across its global manufacturing network and investing heavily in upskilling programmes, BAT is working to embed a culture where trusted data sits at the heart of every decision.
The company’s approach to AI also reflects this philosophy. Rather than adopting new technologies for their own sake, BAT is focused on deploying solutions that solve real business challenges, improve efficiency and deliver measurable value, all within a robust governance framework. This disciplined approach ensures that innovation remains aligned with wider business objectives and long-term strategic goals.
With new planning systems on the horizon, increasing collaboration across global sites and a growing emphasis on knowledge sharing, BAT is positioning itself to take advantage of the opportunities that digital transformation presents. As the company progresses towards its A Better Tomorrow ambition, the ability to collect, govern and utilise data effectively will remain a key differentiator.
In an industry undergoing significant change, BAT’s experience demonstrates that strong data foundations, combined with skilled people and purposeful technology adoption, are essential for building a more future-ready manufacturing organisation.
FAQs
What is BAT’s “A Better Tomorrow” vision?
A: BAT aims to build a predominantly smokeless business by helping adult smokers migrate from cigarettes to smokeless alternatives. It targets 50% of revenue from non-combustible products by 2035.
Why is data governance important to BAT?
A: Strong data governance helps BAT maintain consistent, accurate and trusted data across its global manufacturing network. Clear ownership and common standards create a single source of truth.
How is BAT using AI?
A: BAT is using AI to improve data quality, identify whether data parameters are appropriate and automate processes such as gathering supplier information for ESG and Scope 3 reporting.
How is BAT preparing its workforce for digital transformation?
A: The company is upskilling employees across all levels, from factory line leaders to senior management. Focus groups, subject-matter experts and regional points of contact also support knowledge sharing.
What is the key message about BAT’s digital future?
A: Data is becoming a strategic asset rather than simply a support function. BAT believes trusted data, skilled employees, strong governance and purposeful technology adoption are essential to becoming a more future-ready manufacturer.