SSON Fireside Chat: Building Continuous Improvement into Digital Tools

In this session from the Continuous Improvement Digital Summit 2022, Bojan Bujak, Director of Process Management at Canadian Bearings and Tony Levy, Director of Product Marketing at Skan, discuss how the “telemetry of work” is the next step in process mining and intelligence tools to ensure process improvement doesn’t just stop at the initial mapping.

Transcript:

Hello and welcome to our third session of the day, the content of the Continuous Improvement (CI) Summit. We're going to be hosting a fireside chat on building continuous improvement in digital tools. This is a fantastic session, I think to continue the conversation on CI. We started today with a top 20 insight into how to get value out of Continuous Improvement. We have lots of questions about making it embedded into organizational culture. And then we continued with that fireside chat into making a culture of Continuous Improvement where a lot of the questions were around how to ensure that they were building and being monitored and measured and valued. And drive value out of those CI programs. I think that today this conversation with digital tools is really going to help us continue that conversation of measuring value.

What we're going to do is I'm going to mention that we do have CPE eligibility for those of you who are in the US with CPE credits to attend this year, you can get 0.6 KPIs by watching this session, watching the full 28 minutes, watching the webinar live, voting in the polls as well as voting and clicking the two of the attendance checks to obtain a certificate. At the end, you click on the yellow CPE widget located in the bottom right hand side of the console. I want to add as well that for those of you who are joining us for the first time today, you can connect with our speakers by clicking their LinkedIn buttons and continuing the conversation there. You can download some of the resources available. We have a number of live events or we also have some downloadable digital white papers that people can view in order to continue their understanding.

What I want to mention as well is that we're going to begin our first poll. So that way I can hear from our speakers while people vote. So our first speaker of the day is Bojan Buzek. He's the director of business process management at Canadian Bearings. Our second speaker is Tony Levy, the director of product marketing at Skan.

Bojan, would you like to share a little bit about your background and your work with digital tools and see?

Sure I'll go with the creative intro. I'm a corporate doctor with two specialization. One is performance radiologist and another one is improvement surgeon. And what I really do is roles in transformation process improvement project, program management and/or change management. Most of my experience comes from supply chain between UPS and FedEx. I also worked in financial industry, utilities, military and manufacturing. I'll pass over to you, Tony.

Thank you, Bojan and Jordan. Welcome, everybody. I've been in the software industry for over 20 years, helping organizations apply data analytics to transform the way they work from supply chain management to corporate performance management. Think of operations and finance. I've seen data analytics unlock business value at the intersection of people, process and technology. I joined Skan last month to help organizations take this to the next level. In this emerging category of process intelligence. Think of that as a non-disruptive approach to creating a reliable, secure, high fidelity digital foundation for automation, transformation and continuous improvement. It's a pleasure to be here. Back to you, Jordan.

Thank you. So we're going to move on to the poll results of the first question. But before we do that, I want to just remind people that they can either vote in the poll by clicking the biggest challenge that they're facing right now, or they can comment in the Q&A box about a challenge if they really don't see one of these there. What I would love to know as well, though, if they were to bet on which challenge, where would they think it is versus what? We'll have a look at the results in a second while we wait for people to cast their vote.

Tony, where do you think that people are going to have the biggest challenge?

Yeah, you know, based on my experience, I think it's really all of the above. That's what I would expect. Each one of these dimensions is critical. You mentioned creating a sustainable culture. I think all three of them are really critical for sustaining a culture of continuous improvement. So that's where I would put my best. I think that's a bad influence. I'd hate to influence the response, by the way.

Oh, that's true. Actually, I didn't think of that. Well, let's have a quick look now and see what the results say and then I'd love to get your thoughts. Winner winner. So, yes, I would say it is interesting that if there was a leader, I would say workforce and process, but barely. You're right, all of the above and I think people, process, and technology is definitely one of those balances. It's those levers that are very difficult to get right and to control. So I would love to know your thoughts Bojan, on what you see there.

So I was expecting all of the above. I'm kind of curious of the folks that said none of the above. I cannot see they put any comments in there, but I was expecting workforce or the people's side to be probably higher than process because people are more unpredictable than process. So I'm kind of surprised that they're both at 13.3%.

Absolutely, I would love to know as well how you're using digital tools in your environment in order to support CI.

Tony, do you want to go first or do you want me to?

Why don't you go first Bojan.

I will go back to a time when I was at a utility company. And as you know, a big component of the continuous improvement is the feedback loop. A few decades ago, we used to have the metal boxes strategically placed throughout the facilities and people could put their comments in there and then would hope that somebody is going to go through them and figure out what they meant and do something about it. It's better to modernize that. They use the spigot platform for the crowdsourcing initiative, which can be used for their feedback. And I actually did use it as a feedback loop in other organizations.

The basic idea is everything is now digital. You have the interface, modern interface, you have the ability to submit anything from suggestions to concerns to improvement ideas, anything and anything depending how you structure these challenges or sessions. And then the beauty of these digital tools is the visibility that you get throughout the process. So you can see where your ideas are. People can vote on them, they can give them star comments.

Some better tools would have the graphical interfaces that will show you what are the most popular ideas. Then as you progress through the challenge, you set the thresholds and how do you go to the next level and then you reduce obviously number of those suggestions or ideas, and then eventually you get the winners with appropriate rewards or recognition system put in place. And then the beauty starts from there really because then you can track those ideas, you can assign budgets, you can see what the current status in some more progressive companies. They will actually try to assign the person who submitted the idea to be part of the execution team and bring it to reality. So by either way of succumbent or some other creative ways, so I wanted to bring that usage of the crowdsourcing and innovation systems into the continuous improvement tunnel and use it in such a way.

Tony, I'd like to get your thoughts as well.

Sure I think Bojan raises a great example, collecting feedback from process operators, from owners on improvement recommendations. You know, crowdsourcing has been successfully used in a range of practices. I've seen, for instance, in forecasting medium term trends, such as a likelihood of a recession. Some companies are using it for demand forecasting. We do need to be careful, though, to avoid what some people call social bias. They call it the bias of conformity, and that's the desire of people to conform to group behaviors. That can be addressed and mitigated through various anonymity techniques. But it does underscore the importance of using real-time granular process data to complement crowdsourcing. So coming from Skan or a software provider, we would recommend using crowdsourcing to complement more detailed process understanding. So if you're already using digital tools to monitor key processes in a reliable, granular way, then combining crowdsourcing data with process data can create additional insights on where to prioritize next. I think it's a really novel idea, but we do have to make sure that we're mitigating any potential biases.

So we talked a little bit about how crowdsourcing can be complemented by digital tools. And I'm curious, Tony, from your perspective, how continuous improvement on a broader scale as a methodology and those process tools make such a good match in your eyes?

In our experience, you know, continuous improvements really requires what I've been referring to as a reliable, detailed understanding of existing processes. To establish this, frankly, practitioners need to stop wasting time with manual observations. Right? This approach can take a long time. It consumes valuable resources both from the process excellence or automation team as well as the operators themselves. This can be very disruptive to the work being done. It's expensive and time consuming.

And now, with the pandemic largely behind us, many teams are back to traveling to various sites with their stopwatches and notepads, interviewing operators on site to document existing processes from then which to identify and prioritize improvement initiatives going forward.

Furthermore, on this topic of bias, we really have to try to mitigate biases that are rampant in manual observation methods. There are probably at least three forms of biases - cognitive, social and motivational. Cognitive biases about a failure to process information logically. An example might be anchoring bias, which is the tendency to make judgments with a reference to a benchmark. So, for instance, if an operator knows what the standard process is, then we'll describe their work based on that benchmark and ignore all the activities they perform that are outside of that standard.

Use of recall bias overestimates the impact of events that are easy to recall. So an operator that does admit to activities outside of the standards. So it's called the happy path may only describe those activities that are easy to recall, but ignore all those other standard activities.

And the transformation team is susceptible to bias as well. Confirmation bias. The tendency to seek evidence which confirms beliefs and ignores evidence that doesn't. So someone who already believes that there exists a set of non-standard activities then will actively hunt for data to justify that or support that, and it will ignore other data and then may stop once they've found evidence of that non-standard activity.

So we talked about conformity bias, the tendency for people to want to conform to the rest of the operators. So maybe the operators will simply focus on the standard process and not rock the boat. Motivational biases about the reward system. Operators are rewarded for following the standard process, and then in interviews they will focus on the standard process and leave out the non-standard activity.

So digital tools can add a lot of value in establishing a reliable, granular view of existing processes, reduce time, effort and bias. And then, you know, once that foundation has been established, then traditional process mining tools might be used, but they largely are unable to create the kind of fidelity that we need. Right? They integrate into back in log files and record committed states of work, but are not able to capture all the activities.

For example, activities involving software that don't create logs such as office productivity tools. So process intelligence is really, on the other hand, is able to capture all of the human digital interactions. Think of them as digital footprints, and then connect these activities into an end-to-end process. So this provides both the high fidelity and the end-to-end process mapping that we need. I think in the abstract we call it the telemetry of work. I think that's a great way of thinking about it. Some people call it the digital signature work. Some people simply call this the digital twin of work.

For example, one organization that we work with that are provider of curated data. They use process intelligence to uncover non-standard activities related to onboarding new suppliers of data. So initially what happens is a spreadsheet is sent to a supplier who then fills out the spreadsheet and a macro converts that into a PDF. Sometimes that fails because they're not using maybe a Windows pc, they're using a Mac. They then return the PDF that's a keystroke back into a spreadsheet and then has to be adjusted one more time to fit into their Europe format.

This is performed for every supplier. They have over 5,000 suppliers they onboard every year. This entire sequence of activities is undocumented and it would not be caught in manual discovery methods or in traditional process mining, but is discovered with process intelligence and they were able to save over 100,000.

Think of all the hundreds of similar non-standard activities across thousands of operators that you can address with a clear picture of your current process. Then once that's established then an analytic layer on top of this information is used to measure and monitor work activities. As well as process metrics such as turnaround time, process time, and then finally to monitor technology usage. What percent of time is being used on core applications versus non-core applications?

Process intelligence can then provide 'what if' analysis capabilities and the ability to kind of project or forecast key metrics based on that reliable digital twin. For instance, what would happen if we could improve the productivity of our weakest worker for this process to match the productivity of our most productive workers? We could do a what if, for example? Then finally, from a continuous improvement perspective, you really need analytics to measure both the operational performance, project the future outcomes of different scenarios, to prioritize those improvement opportunities along key dimensions. Maybe around dimensions of complexity as well as expected savings.

So we believe that you must establish a strong digital foundation then you have to take advantage of analytic capabilities to project the outcomes and then identify improvement opportunities that are an optimal balance of complexity and savings.

That was very, very thorough Tony. Thank you for kind of guiding us through the ways in which humans demonstrate biases, in the ways in which process tools can kind of circumnavigate that. I loved your thoughts on that idea of the digital twins and the telemetry of work. I definitely think that's so fascinating. Bojan, I'd love to hear if that reflects your experience as well.

Yes, it does. What Tony described was a kind of advanced to these systems that I used to work with. I haven't seen Skan in action yet. I hope to do that soon. But, yes, the regular systems can only see so much. That's why we still use the observation methods manual ones. But this sounds like a pretty cool invention in the process mining field. I can't wait to see the full functionality of.

Absolutely, and Bojan I'd also love to know as well, what has been your biggest challenge in getting process tools to be used in a continuous improvement context?

So for this particular crowdsourcing example I gave you earlier, it's really how do you harness all the support system to get to the end result? Some people tend to think it's super easy just to set up the challenge and it's going to run itself, which is very far from the truth. You need to have the administrator in place. You need to have the subject matter experts in place to review those results. As Tony was saying, this whole bias and the popularity bias, some people could write any sort of idea. And if they know half the company, they're going to get a ton of likes. And somebody who's a silent genius sitting somewhere in the corner might have an excellent idea that's not going to get too much popularity traction because the system is set up by comments and votes. And you need this expert to actually really read through it and understand what the person meant, potentially go and reach out to them and get the clarifications. But that could be the real gem that's going to set the company on a new path for the future to be the competition. So it is the active management of this whole process that can be really tricky and if not attended to, can really grind the whole challenge to a halt.

Absolutely and Tony, does this reflect your experience as well?

Yeah, I think that the only thing I would add is that companies, organizations that are using traditional process mining tools, you know, one of the biggest challenges is simply all the integrations required to access those backend logs. That takes time, is disruptive, does not provide the level of granularity that's needed. And so there's an emerging set of capabilities which we call process intelligence, which really addresses these challenges. It's non disruptive, does not require backend log integration and yet also provides deep granularity across the entire end-to-end process. So those are some of the experiences that we've had.

I also want to know as well, we mentioned we kind of run that poll at the beginning of the session and you were correct in saying that it's always going to be that finite balance of people, process and technologies. I would love to know from your perspective, how these tools fit into CI in practice in order to better balance these kind of levers?

Absolutely, Yeah. We believe strongly it's a strong point of view that bringing together, orchestrating people, process, technology and coordinating those levers are foundational to continuous improvement. Once you establish a reliable high fidelity digital foundation, then the analytics on top of that can help you monitor worker productivity. So you can compare top performers with bottom performance and look in detail that what are the set of activities that distinguish these two and probably that will identify opportunities for training? You know, maybe the bottom performers have only been on the team for a couple of months. They haven't been ramped up properly enough. And they need additional training on a sequence of process steps that they take that the top performers don't take. Or maybe it's something as simple as giving them access control to some aspect of the software or maybe automating a particular step.

And then from a process perspective, you know, looking at end-to-end processes and comparing process variance, right? These are a group of processes. This is a variant that has significantly different cycle time than this other process and therefore being able to identify areas for standardization and automation.

Then finally, technology usage. Analyzing core application usage versus core application usage to identify automation opportunities to reduce the amount of time spent on non-core applications. Furthermore, process intelligence can generate automate ability insights. What do we do next in terms of automation? So there are algorithms that are used to score processes and some processes for complexity, looking at measures of cognitive complexity or manual effort or workflow simplicity. The less complex and the more manual a task, the more suitable it might be for automation.

Then on the benefit side, helping estimate based on quantifying value levers such as labor rates. So the combination of complexity and benefits can be used to automatically identify and prioritize potential automation targets. This can provide a fast start. Think of it as a baseline to help the process and transformation teams analyze and target CI projects more effectively.

I definitely think as these, RPA for example, is such a key automation tool that's being used in order to automate those administrative core functions or non-core functions that aren't as skilled. I definitely see how that comes into play and becomes such a key focus of continuous improvement as well, because it enables that continued high Level focus on the improvement of processes and the refinement of processes.

I'm going to quickly talk about put the next poll up and then ask Bojan a question. This is our second pole of the day. For those of you who are interested in being eligible for KPIs, they must vote in this poll. But for those of you who are interested in understanding what their peers are doing, this is also a valuable opportunity to vote in the polls. It's multi answer which means that you can pick more than one. As always, you're more than welcome to comment in the Q&A box as well to share your thoughts. But Bojan, I would love to know one of our couple of our commenters here have mentioned that identifying leadership opportunities is one of the key workforce challenges that they've noted. That's one of the key challenges that they've had.

I would love to know how you've encouraged employees with particular reference to senior leadership to take advantage of process tools in order to make CI kind of embedded into company culture and to really to take advantage of that workforce lever we've been kind of mentioning.

I think it all starts with the culture of continuous improvement and how do you set up that culture that people feel encouraged and valued for taking the risk that there's no repercussions or reprimands if there's no stupid question. So how do you encourage everybody to participate, to put in ideas? How do you take those ideas? So going back to the whole visibility, if you run tools like Excel and then it almost becomes like a black hole without good communication afterwards. That's why the crowdsourcing tools with the pipeline visibility or the lifecycle visibility can bring a whole new difference to this challenge.

OK I submitted my suggestion. What happens next? You can see how it's going through the different threshold gates and then if it's going through production or if it has been killed due to whichever reason. And the reason should be known to you so that you can find in your suggestion, ability and improvement abilities. So I found those to be invaluable. Like the whole communication and culture is always up front with any sort of continuous improvement initiatives in terms of leadership. It's a kind of different challenge that if you want the successful, as they call it, challenge in the crowdsourcing, you need to have a strong sponsor as high as possible in the organization who's active and visible and promoting the challenge and encouraging participation of his direct reports and then it cascades down throughout the other levels. So those are my two.

Thank you. Tony do you have anything to supplement before we look at the results of this poll?

Well, the only other thing I would add, I think those are great points that Bojan raised, is, you know, the reality is that business leaders and transformation leaders are today already under tremendous pressure to meet top down targets, for example, for cost savings. And yet they struggle to hire people. So digital tools is a way to unblock this logjam, right? To unlock the capacity of process and transformation teams, to focus on higher value activities, such as creating new insights on how to improve existing work, versus traveling around with stopwatches and notepads conducting manual observations. So let's not forget that we're all under pressure to meet top down targets, and so we need digital tools to unlock the capacity of our teams.

I think that's a fantastic summarizing statement. Let's have a look at the results as well. So I think that it's very interesting to note that 55% of our attendees are using digital solutions to implement the improvements to drive process improvement. So if I was to make a guess, I would say that's about RPA and and automating those areas that they've identified to need process improvements. But I think it's also very interesting to note that they're potentially using tools like process mining, task mining, process discovery to identify improvement opportunities. This is my superficial interpretation, but I would love to get the expert's opinion. Tony what are you reading into this survey result?

Yeah, I think that is good news. 70% are using digital tools, 30% are not right. So 30% are still trapped in manual processes that trap our capacity. The capacity of the transformation teams and the capacity of, frankly, of the operators. And so I think you're right. I would assume the 55% is about RPA. So that's important. And we believe that process intelligence capabilities feed RPA reliably and effectively and necessarily.

Absolutely Bojan, I'd love to get your thoughts as well on the results.

I would concur with Tony that it's interesting that such a high percentage are not using digital tools in today's day and age. I think the guest is right with implementing the improvements, potentially identifying them too. I was expecting that to be a little bit higher. I was a little bit surprised with the measuring the impact of improvement is only 30%. I was expecting that to be.

I totally agree. I mean, in our closing takeaways Bojan, for looking at the results, what is your advice to our attendees based off of where they're currently focused their digital tools? What would be your advice?

Well, I guess the focus would be on the 30% of folks, or 27% of folks who are not using it to explore the landscape and see what's out there and really explore. They don't know what they don't know. And I leave it with that.

Yes, I agree. Tony, any closing thoughts?

Yeah I mean, to the 30% that are not using digital tools, I would say simply stop manual observations. But then to the 70% that are, I would say make sure that you're building a reliable, highly granular digital twin of your existing processes. Don't settle for high level process, let's call it maps, from traditional process mining tools. You need much higher levels of granularity to cope with all the variability in business today.

And then finally, as you look at future improvement opportunities, make sure that you're orchestrating people, process, and technology using your digital solutions because that's critical for sustaining continuous improvement.

Thank you so much, both of you. I think that these are really valuable insights. I think that the attendees who shared their thoughts and polls and Q&A have absolutely enriched the conversation. Thank you so much for your time. As I mentioned at the beginning of this session, there are digital resources available to supplement the learning that we had today. And if you're interested in connecting with Bojan or Tony, their LinkedIn's are available on the top right hand side of the screen. If you're interested in joining us for our next session, it's going to be looking at how you can take your CI strategy to the next level with industry benchmarking from the top 20 most admired SSOs in the world.

So do join us for that. You can do so by clicking the green next session button widget that is jumping up and down at the bottom of your screen right now, most likely. But otherwise. Thank you again, Tony Bojan.

You're more than welcome back.

This has been a fantastically engaging session. Thank you. Have a great day.