Operational management through a global pandemic

Thank you, Minister for the introduction there and the endorsement. I would just like to say, you know, under the leadership of Minister McKee, we managed to rally and a team together from SMAS and very quickly mobilize our resources. 

This is going to be a bit of a story of our journey, and, if we cast our minds back till April, May time, things were very different, very uncertain. The pace of change was very quickly that, you know, changing day in, day out.

This was very much in the media, spotlight as well in terms of the importance of testing and increasing testing capacity.

What we're going to try and pick out of here, is not so much the, let us say the clinical or the laboratory processes, but the operational management lessons that my team and I at SMAS have learned through working with Harper and his team. In what is now the UK's largest and most operationally effective COVID-19 test facility.

There's a quote there, “Plans are worthless, but planning is everything”. Is something that will rhyme through this whole presentation, in an emergency situation, in a crisis, which is one we were in a global pandemic. I don't need to tell anyone on the call. But sticking to plans can be quite dangerous.

Having the ability to be agile, and dynamic, and the process of planning, and as Gary will touch on later, the tools like plan, do check out, that we use day in, day out, were fundamental in achieving success and making traction.

I'm going to hand over to Harper before we go into the sort of operational management piece. Harper is going to bring the Lighthouse Lab in Glasgow to life a little bit.

Thank you, Jerome and Minister, for the introduction. It's really been a pleasure to work with the group. So happy to join today and share a little bit about the story over the last year.

To set the scene, a little bit of background, you know, something that will Purveyed, this entire discussion is the group effort of a lot of extremely motivated people coming from very different disciplines, which has been key to the success of the Lighthouse lab. So, shown here is the site that we're located, it's here in Goven, just on the South side of Glasgow, where the largest acute care hospital in Europe is located, the Queen Elizabeth University Hospital.

You can tell from my accent. I am not Scottish, I moved over here about three years ago to set up a business called BioClavis we're a precision medicine R&D company and we've had the fortune to work very closely with Scottish enterprise, both through R&D funding, as well as a number of activities they've helped us with, and things like export and working, navigating through the business ecosystem in Scotland.

So, I came into this with with good impression of Scottish enterprise. Also, having many colleagues across the sector, especially tied into the University, you'll see University of Glasgow logo there. There's a living laboratory project that we're working on with them where currently the room I'm in is 10 meters away from the lighthouse lab that was set up on the campus.

We at BioClavis, alongside the Scottish Government and the NHS, drove the overarching strategy, as it was being built from the Department of Health and Social Care, was key to all of this.

We're an industry participant - BioClavis was contracted to help the University run the lab, which they were contracted by DHSC to set up. Importantly, there was a company called BioAscent - another Scottish company, they do drug development work just a bit east of here. They set up the initial stages of the process, but they came on to do a short piece of work and then hand it off to someone to operationalise them. I was quite pleased to be asked to come in and help with that.

Thermo Fisher has been a good partner in addition to a vendor and so what I really want to get out of this slide is the massive amount of varied expertise that came to solve this problem. As Jerome said, one year ago, at this time, we were gearing up on this project. Nobody knew what the next year was going to bring, and nobody knew anything other than we had to go fast, and we had to go as powerfully as we could to solve the problem. That was true all throughout last year. Things are starting to feel like they're a little more stable, but maybe that's only relative.

What we've done is build the Lighthouse lab from scratch. We had to take a lab that was previously used for other testing and research, basically clear it out and reset it. We've now grown to take up the entire building.

Some of the pictures on the right, we had helped by the military, moving around Equipment, borrowed from the university, acquiring new materials from all around the country. It was really a broad project, constant theme through this. I think the important thing there is, translating it to maybe more standard business practices. Typically, you have several years to scale a project of this size.

You have a plan in mind and intent, we really didn't have that advantage. We just needed to go. In a situation like that, we needed as many people, with the different areas that they could contribute. That's really the story of how we got here.

You'll see, in the green graph, the individual numbers aren’t particularly important, but, you'll see there's a couple of inflection points. We've now tested over 10 million samples. These are patient samples that we got reported out. This includes swabs that any of you, if you've gone to testing centers or you've gotten a home kit, they come to us for testing.

The tests come out of the double bagged and boxed samples that you see in the bottom left. They go into class 2 hoods to keep our people safe - but this also make it slightly difficult to operate within and is a tax on the efficiency of the process. Then the individual tube's go into the rest of our process for the PCR testing.

Now, if we look at the graph and the accumulation of cumulative samples, you see there's three phases. The first phase was really getting our feet underneath us. We started the first day with about 41 sample's going through, even before I got involved. Then, processing hundreds to thousands of tests which I consider a brute force effort of just getting the thing going, massive amounts of hours were put in by really dedicated people.

That would have broken everybody if we'd stayed at that sort of a pace. So, the time when I met Jerome, then Gary and their colleagues, was when we were starting this inflection point of really scaling up and we couldn't do it by just sheer force alone. We probably would have tried. We probably would have broken everybody, and then it would have been a sad story, but we needed to build in some efficiency.

We knew where our efficiency problems were, we knew where we didn't think they were but the important part for me in those early days, was having those discussions, brainstorming. Figuring out where we could work together, where we could get input from, for example, a totally different discipline of manufacturing. Ultimately aiming to gain an awareness of efficiency of moving product around an awareness of adding value at various steps along the journey of a workflow. Despite coming at the problem from a different direction, we very quickly got a common language and a common way of working. That's how we scaled up during this time.

We did it at a time we were just ahead of scaling up the number of people. We went from one shift that was doing 4 on 4 off, to two shifts during the day, working through the night, 24/7, scaling up to where we are now with about 750, headcount within.

In a 6- or 7-month timespan scaling up like that is pretty hectic. We've been very fortunate to have the university HR team helping us with that. But you can't just throw more people at a problem. That's inefficient and then you just scale your inefficiency.

We really benefited greatly by having the team come in and it's really these first steps you see down at the bottom of the screen where this was highly inefficient, manual operations.

Moving through getting samples out of the flow of Royal Mail deliveries and into what scientists are generally good at, which is doing the scientific experiments. So, we had equipment downstream of these steps. Jerome and I explored this in early days, my sense was that wasn't where the bang for the buck was. And so, we spent our time on these early manual steps, and we've been really successful.

All of our statistics and metrics demonstrate how successful this has been and the compliments we get from other labs really make me proud of what the team can do.

Just building on from Harper, these graphics show that, on a good day, the Lighthouse Lab was processing around 10 to 15,000 samples a day. Harper said this operation wasn't a sustainable method in some of the front-end processes. The stepping-stones set out there was a move to 30,000 as a milestone, 50,000, and then 80,000 and beyond, so that was the challenge. It was one of just, pure capacity build in a very short period of time whilst maintaining the quality and also the turnaround time of over 99% within 24 hours.

That was in the graphic that we were talking about, you know, 80,000 is testing a whole international arena of a football stadium every day - day in, day out, seven days a week and that was the challenge.

What was our approach? One of the first things in here was, was stealth. Because I remember the conversation with Harper and the team saying, if you tell too many people, you're working in one of the largest COVID-19 test facilities, you might have the press at your door.

We were also working for the Scottish government, and this was UK government funded. There had been some opportunities for consultants to support as well. So, we didn't want to raise the profile on this one too high, we just wanted to get in and do a good job.

The first part of this was really building engagement and trust. First of all, with Harper and the team because we were a group of manufacturing professionals and knew very little about a PCR COVID-19 test process. But we found out there were some transferable skills.

The ball of wool, in any complex problem like this. What we're not trying to do is solve the whole problem. We're trying to pick out the 1 or 2 strands that we can take out without untangling the whole mess in one go. And that was that was the key approach. We used lean principles tried and tested that we had in our toolkit.

We were experienced and using along with the TOC theory of constraints, in terms of the bottleneck management style was facilitative, but also directed because there was no time. So sometimes you know, you facilitate people to a conclusion. You need to get in there pretty quickly in this environment. So, there was a bit of direction, as well, in that regard.

It was also about learning about each other. When we reflected at the SMAS team, there was five of us living and working in the Lighthouse Lab for an intense period of time. We don't normally work like that, and we have different styles, and different ways of working too.

We were also learning about the virus. If you remember at this time, social distancing, wearing masks, how we operated internally in a facility that was growing largely, and new people coming in. That was something we were all learning and very aware of.

Harper: The learning was really key there was a bit of a culture clash between a group of very bright, generally academic scientists and a team of lean practitioners and manufacturing consultants which most scientists don't run across in everyday life.

So, one of the key pieces to our success was really that the teams recognized what each of the groups brought to the table and the direction that we want it to go.

We had a number of practitioners that were working with the Lighthouse lab, and we had years of manufacturing experience from them. I suppose in a pandemic you have to wipe the slate clean because the way we normally deliver projects has changed fundamentally - and no one had written the rule book for this one.

No one in the world had experience of a large scale with COVID-19 test facility because it's never been done. But we had already been working with some of the NHS Regional Labs. And that's where we first were introduced to the processes and started to get some understanding, so I think that helped. The most important thing was, we definitely had some transferable skills and experience. Credit to the whole SMAS team, how they repurposed themselves, and rose to the challenge in a very dynamic and an enthusiast purposeful way.

I think, we would bring in the operational practice, we have the clinical and the academic expertise and the synergy that was created between those three domains was really quite powerful.

So, our plan, we did go in with a plan, a very comprehensive plan on different work streams, and I remember, I think the first meeting with Harper was about six. I think I met you about six o'clock in the evening and we left about midnight. We talked about all things, lean and very quickly developed a plan.

I'm going to hand over to Gray now who's going to explain what we did with that plan. It didn't exactly go into plan, let's say, but that's in hindsight, that was a good thing.

We had our plan but very quickly realized, when we arrived on site, that we couldn't take weeks or months to try and do what we wanted to do. We distilled that down into a weeklong Kaizen event, which was about, I think, 10 hours on site with some focused improvement teams, that we generated from a group of 12 people.

Our four key main themes that we're trying to achieve was good tempo in that week of Kaizen, and about decentralization. There was a tendency to take things back up the chain for approval. But we wanted to try and get it down to the people that are working on the tools. Allowing them to apply their own intuition.

Some of the people that we were dealing with and these kinds of teams and had already had a couple of months expedients, and these process steps, so, why would we not less than to their natural gut instinct? We didn't have the time to potentially take as much data and the analytic point of view that which we normally take, and then bias for action, it was it was very fast and intense trying to get change put in place. By going from a huge, complicated plan, down to the weeklong Kaizen event, having those four key themes and everything that we were doing, we were able to instil good changes in the coming weeks.

We're only capable of doing that, because of the people that were there. I've worked enough a few businesses, and I've seen I've seen a few organizations and, nowhere that we go do people want to do a bad job. And it was evident from the first time walking through the front door to the Lighthouse that people had the sense of purpose, and the reason for them doing the shifts that they do, which are crazy times even in a normal situation was absolutely fantastic. So, the passion and enthusiasm and energy from the people and that we were dealing with, you couldn't ask for any better.

This is really key for all sectors and whether you're in a pandemic or not, having that sense of purpose, the direction that we all shared is how we got there and how we were successful. We were able to easily translate that to Gary and colleagues, but that's really a key, is to sync up on what we're trying to accomplish and why, in this case, it was easy.

Cause we were saving lives, and we had to scramble to do it. In other cases where it's incremental business improvements or getting things back on the rails.

It may be less obvious, but it's really important to translate that through. Make sure the team understands why both, you know, the colleagues that are helping lead it, but as well the people that are doing the work, there's nothing more important than that. I think to build a good project out of.

So, this is somebody's camera phone took a shot of a post it notes inside of one of our kits that arrives here. We used to get occasionally some abusive notes when people were frustrated with things, but far outweighed by great notes. This is one of my favourites of all time.

The fact that people took the time, in and amongst their own fears, after taking a test, they took the time to write a note, to one of our scientists in there. And these sorts of things are how you really galvanize the purpose. This is how the team grabbed onto this and moved as quickly as possible. As Jerome was saying, we still had to cut down the amount of work and get right to it. As, not only was there the sense of purpose, but there was also a lot of pressure, or let's be honest, to get things mobilized and grown as quickly as possible. All the pressure in the world doesn't work if people aren't inspired. 

This meaning and significance, for every single person in the lab, as well as knowing why they're doing it. Very few times in our lives, do we get a chance to really feel like we're saving lives on a day-to-day basis, and it's really a powerful, motivating factor.

This all brough us to the tools we decided upon, and we, we initially set off on looking at lean principles. We just went back to basics, and we've already talked about it a sense of purpose, identifying customer and specifying the value. The value, in the customer's eyes, as somebody at home, worrying whether they are ill and how it affects our livelihood, etc. So, the value is clear within that lighthouse.

We then help facilitate developing a visualization of the process, and specifically, the front-end part, which we were looking at, and to try and understand what parts of that process were the non-value-added aspects.

Following this we began developing the flow by eliminating wasteful activities and we try and put in some pool aspects into the front end of the process, and the crux of it all, was pursuing perfection. To do that process, normally, you would take a relative amount of time to try and do that. But in this instance, it was the tempo that was driving. The next tool used, in conjunction, were looking at these five elements were: plan, do, check, act. 

So, why use plan, do check act? In this instance predominantly it was used to manage risk. As, any change that we're going to help make the team at the lighthouse came with an inherent risk of ruining, potentially somebody's sample, or somebody not getting the result at the time they needed to get the result.

Taking the team through the plan, do, check, act tool gave them the structure and the confidence to look at any task that they were taking on and question themselves about the risk. Including the planning aspect. So if they are doing it, again, tempo bias for action. Let's get in and do what we call ‘Try storming’. Then the checking aspect: What happened? Did it go right? Did it go wrong if it didn't go right? What can we change in small, incremental, iterations and evolutions of changes to the front end of the process?

We could easily take a step back and change everything in one sweep but that isn't going to work in this instance because of the risks. So, plan, do, check, act in this context was a risk management tool that we implemented and that allowed us to, it allowed us to cycle through a potential changes and allow the team to execute them faster rate than what the environment was maybe dictating to them, and in terms of that ramp up for capacity.

Therefore, the next tool for us to use and help to team learn about, and engage with, was the one that's probably made the biggest impact and that's standard work. Standard works a funny tool because we can sometimes tend to try and introduce standard work to all aspects of processes, and it's not the case. It has to be right for the situation that you’re in. In this instance, there's obviously the before picture there and the team's taken out samples from boxes in cardboard, boxes and plastic bags, and the room was fairly small. There wasn't a clear flow, and it was a bit, mixed up, each shift in a different slightly different process, which is fine. It was getting them the results that they were needed at that point.

The key there is, it wasn't scalable for them to go to the capacity that it needs to go to. So, I'm taking a team out of that pressure situation, giving them the chance to look at from the outside, and then design and we're just facilitating a conversation on what that new process looks like, and leads to.

The after picture there where every workstation is the same, there's a defined process, and it's moved, that front end from a potentially chaotic situation to stability at the standard and never getting flow. The crux of all that is that the Lighthouse are able to recruit huge amounts of people, and get them effective, in a very, very short period of time whereas previously, that was a bigger challenge.

So, they're now able to get, and 30, 40, 50 people, and they are 80% effective within a day, because the standard work is doing that for them. A really important tool in any excellence model has to be executed and used at the right place but if done so properly it is very, very powerful.

Harper VanSteenhouse

Reflect on the context, a little bit also felt. So, we're obviously in the life sciences, we're all scientists here for the most part. I think this is true for a lot of technical. Disciplines, engineering, those sorts of things. The Plan, Do, Check, Act is a tool that fits very naturally when one thinks about it. So this is just science to us, I mean, this is what we do, this is the scientific method.

But I will tell you that when we're concentrating on getting the task at hand, completed, we don't always take that step back and think about our hands-on aspects of our work, in the same scientific way that we would if we had a written experiment. So, having the group come in as facilitators as to create that boundary step away from the work badge and think about what they were doing, and have it be explained to them as a tool to use, it fit very naturally once it was explained. 

I don't think it would have happened on its own as quickly and easily. The same thing happened with the things here and the standard work and those sorts of things, between the different teams, everybody had pushed forward, they were being effective. But, until you have sort of a third-party facilitator come in and ask, why are you doing it that way? Or have you thought about it doing it this way, and pull those things together? We didn't have that real catalyst. That was key to making it all work. So, really appreciate the work there.

That's something I think, everybody should take away from this, is having that outside point of view, even if these concepts are ones that you're already working on; having an outside force come in and just ask the questions, is really powerful method in management.

Gary Aitchison

Yeah, absolutely, then moving from, getting stability into, understanding are we having a good day, or a bad day. When we first arrived at the Lighthouse, the team knew that they were doing good. They knew that they were achieving something, but it was hard to sometimes contextualise or visualise what that looked like.

The introduction of short interval control was another key tool that we helped facilitate the introduction of. This tool allows us to take a moment in time now, we take a look back at our previous day or previous week's performance, is there any actions we can take to try and improve the forward part. So, the next week or the next hour on the next day or what have you. 

With all these tools, it's not always the case to try and get them in the most perfect way. The picture in the bottom left, believe or not, is a short interval control board – it’s not the straightest lines in the world, but the tool works. 

It doesn't have to be nice and pretty, if the tool is in, and it's being used and it's practiced. Doing the basics right; when the volume goes up or chaos ensues or there's other issues, it means that you don't have to worry about you don’t need to commit capacity to think about those things because it's just happening. 

So, short interval control was absolutely one of the key tools for operational excellence, that in this context, a key tool for the team - to understand their performance and know whether or not they're having a good day or a bad day.

We're really getting into the guts of some of the tools and techniques. The other one is, as Harper alluded earlier, we don't need to fix the whole process or scale up capacity on the whole process. But it's about identifying the bottlenecks.

The theory of constraints, even though we didn't call it theory of constraints, we just called it we're trying to improve the bottleneck, was really about maximizing throughput. Managing inventory and the operational expense in this. 

Which, in this context, was time - really reducing the timeline between each of the process. Which was about identifying the constraints and exploiting the constraint. 

To explain the constraint in unboxing, for example, the question was – are we maximizing the operation that, running through breaks, having service operating speed, the value adding operations, minimizing the waste through transport and handling, and then subordinating all other processes. So, rather than prioritise and maximise capacity and other processes, which would create inventory and work in progress, is making sure that the pace was set by the bottleneck, then elevating that bottleneck by the modularity of standard work. 

As we know, if it takes 4 seconds to open a box, it should take 4 seconds on a Monday, Tuesday, Wednesday, Thursday, Friday across the four shifts. And that's building in the efficiency allowances to cope with those 4 seconds. But what we want to know is that we can modularized that to elevate that constrain.

Instead of having one table doing the boxing up and now has eight, or whatever it is now up to. There’s a modular build to get to the 85,000.

If you try modularized or elevate the constraint when you've got chaos or non stability, it just, it just gets worse. So, we must keep looking at where the constraint is - has the constraint moved from unboxing on bagging to somewhere else in the process. So that was a sort of theory of constraint.

Additionally, if you look at the supply, into the Lighthouse lab, it is totally unpredictable. As there are people who are symptomatic turning up to a regional test center all through a care home. The hours of the day, you don't get the same number of samples, but 85,000 samples a day is roughly 3,500 tests per hour.

We know that if we do the normal distribution of the hourly rate through the short interval control. Some hours we get 2,500, on some hours, we might get 4,500, so the average is 3,500.

But if we've got a bottleneck process like process B, let's say unboxing, in the hours that we only put 2,500 into that process will never recover that again because that process is not capable of going up to 4,500, it's bottlenecks at 3,500.

This is why it's really important to look at the bottleneck, maximise the capacity in there. So, it can cope with any variation in supply and output.

The short interval control is the tool to measure it. But the theory of constraint is the principle in which we take action based on those short interval control measures.

Gary: So, this is actually the daily testing graph, from back to when we first started working with, with yourself and the teams and the green line is the step change in declared capacity while, the brown line is the daily output.

Harper: This really pulls together, everything we've been talking about - there's variability between days, and you can see that variability is getting even bigger now.

There was a general trend upward that we needed to manage against, so we did have a bit of a runway where we could, improve over time, but it was a pretty rapid ramp. As we all know, the needs in the UK were growing very quickly, and we didn't really know how far it was going to go.

We didn't know what the future was going to bring and so building this stuff as quickly as we could was critical and so we went through various steps. The big transition that we're seeing now is now that we're sort of stabilizing and we, both, the lab as well as, I think, you know, the general population is getting used to, living with the virus - which we're going to have to do for a while.

We're moving to a different phase, where it's not all about growing, efficiency, finding the bottlenecks, we've got things where we feel like they are pretty efficient, maybe not 100% of the way there - but most of the way. We are feeling pretty good about it, we can handle these day-to-day variations.

Now, we're moving into a more sustainability stage. So, we're working on helping the team, again, exercise those scientific skills, but in a business and manufacturing context. So, they have the tools to use things like root cause analysis and really, stabilizing the lab, so that it's a sustainable journey now that we don't have to grow quite so quickly.

Jerome: It's also maybe worth pointing out that, what's important here is not so much the daily output, but the capacity that can be released on the daily output, should there be a requirement to have a short surge increase in testing.

So that's why, that green line there, is really key, because what the UK government will be looking at is, what capacity do we have should we need to use it?

Gary: As Harper alluded to a couple of seconds ago. When I moved to a different phase of support, which was root cause analysis, some capabilities around management control reporting system, which is a really good approach for the Lighthouse lab. It's absolutely the right thing at this time.

But it's also given people the Lighthouse new skills, new experiences, which, at some point, they may take it to another place, another organization, which is a really fulfilling thing to do, and lots of smiley faces on the screen now and I don't know what the joke was.

It's not just a physical delivery, it’s a virtual delivery, as the majority of us have been doing and so the ability to be agile, and flexible on how we get across the tools, techniques, and, and support of people has been really key.

Harper: I can't, can't sing praises enough for the team, both in terms of their productivity and effort, but also, the fun that we've had doing it and the good spirits, it's been hard. I won't, and can't sugar-coat it too much but the, the odd thing about our project here is success for us is shutting down the lab. Meaning the virus has gone the country has sustained itself through the pandemic.

But I feel very strongly that. that doesn't mean we should allow our people to go through that roller coaster. Everybody here has gained skills experience and I firmly believe are better off for it and I think that's the trade-off. They've given a lot of sweat and tears for this project.

Now, myself, as a business leader on my own, this means that Scotland is a great place to hire people over the next few years. I've got some of the best, well trained people in the building here. I assure you we're doing our best to sustain for the long term of the Scottish economy. But I will take advantage of that, also. Because we're a growing concern, as well.

Jerome: Just to add to that. I've never experienced such a culture where there is no resistance to change. We almost have the inverse of that, where everyone wanted to change things and improve things, which then gives you another problem. We've seen that that's come through loud and clear. Also, as Gary pointed out there's a picture on the left, one of the staff has a parrot on their shoulder. It's just worth pointing out a small detail like that, because you wouldn't see this in the non-virtual world, we see pets and we see the, the insights into the lives of others in a different way. It's been really fun working with it, with such a diverse and talented team of individuals.

Jerome: Yeah, Harper please chip in as well, but we just tried to conclude this with maybe some of the key learnings.

The first one, I took this from the Lean Enterprise Institute, which did a review of successful Lean projects through the pandemic. One of the key things was make it your problem. Own it. Don't wait for Harper, the chief exec, or whoever, to give you permission.

Find out what is your next move. Understand why that's important and make it your problem and do something about it. The more people that do that, then we gather momentum, and we build up, and eventually then we join up all the dots.

That's that was one of the key learnings to start off with.

Gary: Yeah, Engaging people. Don't ever underestimate the time you need to invest it to get to know people. It's very easy to go in and just look at the practical problem that needs to be solved. But for us, absolutely one of the key learnings was just getting to know the team.

It’s one of those cliches of the organisation, the best assets are people but 100%, get to know, people, get to know what things are like at home and the conversation is a little easier when you come to some of the difficult things in that need to be challenged. By engaging people, you understand the purpose.

Jerome: The shared purpose, I remember sitting down with Harper one night and Gary and a few others and Harper asked us the question, why do you guys want to help us? 

The reply was along the lines - because we know, this is so important, and we want to help make a difference.

When you start working in this environment and it becomes, you hear about covert testing on the news, and what's happening in society, and you actually see it for real and you see the people that are doing such a tremendous job. That purpose, it just becomes so infectious. It certainly gets you out of bed in the morning, or in the middle of the night, or whenever you need to get out of bed for this one.

Harper: It's a pretty dramatic example, right. But hopefully, we're not going to be all motivated throughout our entire careers by a life-threatening pandemic.

I've seen similar levels of engagement and ambition in teams, and it has really galvanised team efforts. Things like, gaining on a competitor and making a competition in the market place be your engagement and galvanising point or somebody gaining on you, for instance. 

We've also had experiences where, we're generally sort of leading edge, innovative technologies. But we're on the corner, on the cusp, of a new innovation, is another thing to harness. So, I would say, think through how you can find opportunities.

There's nothing more important for pulling us all together, because I think what you've heard from Jerome and Gary and hopefully myself as well, is that having access to these tools and facilitators, that understand how to use the tools, is necessary, but not sufficient.

It won't get you there unless the people are ready to do the work, ready to implement those tools. Ready to engage with the facilitators, ready to find solutions. That's a real key to making this whole thing work.

Jerome: Then the last two really, which we covered, the Plan, Do, Check, Act thinking, which was the bias for action. Also, don't get tied up in plans, but the process of planning back to the, you know, the plan, do check out, is really everything in there.

We want to get a few questions in, and we started a bit late, but the leave you with the contact details for Harper gallery myself. I'd like to signpost you to our National Manufacturing Conference Making Scotland's future, 15th to 16th of June, and the contact details there. So, I'm going to open up for some questions here now.

Jerome: So, some comments in here - Some great work, you deserve your day in the sun guys. I wonder what was your most challenging bottleneck and what bottleneck did you end up having to live with?

Maybe go to Harper yourself, first on that one.

Harper: So, there are a couple of strong differences from us, and maybe more common manufacturing approaches. One is, we're not really trying to build anything, we're trying to destroy it.

Our raw materials aren't really inventory in the same sense. Rather, we're trying to get rid of our incoming materials - patient samples.

So, really kind of inverting the thought process of inventory control, and thinking about the bottlenecks in that sense where, even though we may not have been optimising for efficiency, we needed to optimise for turnaround time and getting results back. That was the challenge, in my mind - really working through that more than any one of the individual steps.

One thing we've had to live with is, we get whatever the public sends us. The incoming material is not perfectly standardised.

So, we've had to build in some sort of inefficiencies, to support more dynamic behaviour. For instance, during a lockdown, the types of samples that come are very different than when people can go to the pub in the summer. So, we have to build some of those things in, because it's not like we're ordering from, from a vendor.

Jerome: Thanks for that Harper. How did you get to the Capacity model and how did you model capacity to understand the art of the possible? In terms of increasing capacity, maybe come to Gary on that one first, and then Harper?

Gary: Modelling capacity was a fairly simple task. It was just one word, which was more. So, the first instance I was just trying to help to get as many through as possible, am when it came to putting that into a linear plan.

As we engage with Harper and some of his's key people to sit down and, and decide what the gates would be, that we try and get through. So, Harper, I leave for you to finish the answer off.

Harper: Yeah, that's right, this gets back to, we're not a normal business that has to worry about, you know, supply and demand curves. We just had demand coming through the roof, so we could keep going.

The other thing we could do is a lot of our downstream the say more technical biochemical steps. These included using instrumentation and reactions that had a very defined cycle time and capacity, and so those were easy to model out.

Once we set those, then we could back into the demand for the upstream part of the process, and make sure we can match the throughput, or slightly exceeded the throughput, so we kept the edge and fed.

Jerome: That's great, guys. There's another question, as well on the business kit theme about capacity is a normally scaling specific speed in regulated industries like a laboratory is used very much as a safety check.

But in a crisis, when time isn't commonly available, and what has been learned to avoid waste from the normal process of processes of the system and how will it be kept to transfer to another setup? So that we keep that we keep that learning.

Do you want to say a few words on that one, Harper?

Harper: Yeah, it's a tough one. There's a couple of different ideas I'll reflect on just, it's a pretty broad question. Certainly, the regulated aspects is, maybe on first glance a limiter for us to scale quickly.

But I would argue, it's how we were able to do that safely effectively is that we had to have everything very tightly controlled through our quality system. First and foremost, before, anything about capacity quality came first. Because it doesn't matter how many results we get out if we can't count on the results being right. That's, that's worse than not being able to produce.

So, that was a fundamental piece, but what it meant then, is, I could be confident that the growth we were seeing was controlled high quality growth, and I think those actually go hand in hand. I think we're more effective because of it.

It meant that there was a little more inspiration behind standardisation of the work. Rather than just tried to convince people that we would end up more efficient. What everyone was really driven by is quality results to their fellow citizens out there. That was an easy ask for the team.

Jerome: Harper and I certainly noticed, when we started working on the standard work and let's say, the process verification of the standard work, that really got into the qualitative aspects. So, very much ethos was, we need to get this right, which is not about cutting corners.

We actually didn't really focus on, let's say, the value adding time to speed that up. We focused on older sort of non-value-added activities either to use that lean context, that we're either side of the value adding.

So, the standard operating procedures in the standard work thinking really built on the existing procedures, the lab had, but to get to another layer of detail. In terms of what was the what was required to the process, and the individuals in the process.

I think can, Jonny, I'll take a say for me, I know we were overrun now. We started a bit late, and I think we should probably conclude there.