Session Information:

Identifying business opportunities with process mining and successfully translating it into business value

Session Transcript:

The view of process mining, intelligent automation. It's a real honor to have Karen Harris here with us. KLM, Go ahead and share your presentation, just yet. I'm gonna ask you to stop showing your presentation screen for a moment, because I want to make sure the audience sees it, and I want to make sure that we acknowledge, you know, you. Kayla is a systems engineer, has a background in science from the United States Naval Academy, Bachelor's of Science in the United States Academy. A Master's degree from Kelly Butler University.

He has spent the last 12 years implementing automated systems for defense, for healthcare, enforce supply chain industries, with a focus on optimizing data utilization. So, when we, when you bring you KLM here, we're bringing a real leader in a real practitioner of intelligent automation and callum, on behalf of our global community. I'm deeply grateful for you to come here, share your expertise about this, this journey of intelligent automation with all of us.

Well, thank you so much for the wonderful introduction. I'm happy to be here. and be happy to be in front of all of you discussing these opportunities. I think it's a critical part of all organizations universally growth, process mining, and identifying business opportunity. So I'm very happy to be here and discussing these aspects with everyone.

With that being said, I'll go ahead and kind of introduce while we're discussing today business opportunities with process mine and success lead translating into business value.

one of the key things about our organizations at every single day, We're looking for opportunities to be able to either reduce our costs, increase our savings, or increased profitability.

And all those are actually measurable a trivial valuables to data. Right. We can utilize this data. Then turn in turn, create projects, or programs, or systemic or organizational changes within our processes to increase the value which these things bring to our organization. So I want to highlight this as being a major part of organizations, just because each one of us, whether we're leaders or practitioners, need to understand these concepts and how to implement them successfully.

Here are some of the key topics that I'm going to be discussing today.

one is developing organization's processes and inclusion of measurable data. What does that mean?

I think one of the key thing about, before we start any organization, or actually implementing a software programs or processes, We have to identify what we're trying to achieve.

It starts with by developing oriented processes and inclusion of those measurable data portions.

Second forces, is the data find the data points used for process mining to develop a business case. In which data points are we going to use to say, This is what we're going to drive, or, this is where our business case is going to come from. Or do we even have a business case at all, as one of the key aspects of it.

Analyzing a potential business case through process mining, developing the business case, and I think most important, is key performance indicators through process mining. All these things are kind of the life cycle of which we, as organizational leaders, are identifying opportunities for both business growth, but also the success of a project or program dependent on process mining.

OK, first, let me start off by the developing organization price with Inclusion of measurable Data. Why is this important?

Key thing is, I think there's a great quote, Stephen Covey, author and a couple of different practitioner box throughout our organizations is If the ladder is not leaning against the right wall, every step we take just gets us to the wrong place faster.

What does that mean to us? What that means is, before we're actually setting up any type of system or processes, we have to evaluate what do we need to evaluate success?

Otherwise, after we've actually implemented those processes or systems, we don't know how to measure our success.

Or, we don't know how to measure how well we're doing.

And that's a that's a failure on us or organizational layers. So we have to be able to identify, in the future, where are we going.

And when then, once we get there, how do we evaluate this.

So let's look at the different event data for business cases user.

An end user is vitally important, right? And this could be across entire industries, and user is can be purchased online.

So the customer, it could be someone inside a facility, whether it be supply chain industries, manufacturing, industries, it could be in a software industry, right?

You're having some type of user interaction, whether touch, systemic date.

Systemic data is in after a user inputs, some type of characteristic, or modification, or change, that in turn, turns to data from which other processes can then use an autonomously derived data.

I refer to this as more of like, AI experimental station, Meaning, I'm using systemic data or multiple systemic data inputs to then evaluate what is the next step in the process, or what output from that data am I using to then create the new process and methods of deriving data architecture, as another important aspect.

Before we understand how we're building it, we have to look at what we're trying to achieve.

I love these pluses flow diagrams.

Will there be in software applications whether being facility processes?

Because you have to understand where we're going to get evaluate some of the exception cases that it may come about.

So, for example, I'm expecting process A to B to see to occur. But something could occur where it's preventing a to B step for appropriating properly. So I want to evaluate that as part of my data algorithms, as well. And I want to have some type of systemic data derived to those exception cases.

Database logging.

Database logging is key.

Key thing is, is it every single footprint we have within all of our industries, Each should have some type of data point. We can go back and evaluate.

The key thing is, is database logging.

When a, when a user is touching a screen, when a user is making a transaction, how has our application actually logging that information to the data? Is logging this information in a transactional form that we can use it, simplicity ischia this. We don't want to over over log to the point. We are unable to obtain some of the rich details inside.

They want to make it simple.

And recording reporting is key, because allows us to evaluate trends, trends, feeding. When we have certain systemic data flows, how are we trending trending towards success? We want?

if I have a specific time between a user and assisted death, systemic data output, where does that time variance, Is that time Variance important to us, is it should be evaluated and reporting on all these different aspects as allows us to extrapolate this into a user friendly form, especially when putting a business case together. Because when you're talking to investors, or people from finance, organization inside your organization, that you're saying, I want to build a business case around something. We have to be able to represent those key format in a way that's user friendly. And everyone is able to understand, read, and be able to interpret what business case for driving to is going to provide value to the organization.

Next key thing is what type of data. Now, we've got the different types of data that we're looking for. What I'm actually looking for to develop a business case, and this is something that we are looking for every single year, and we're actually defining type of projects or programs, or processes that we need to refine.

We're gonna find large gaps in events, history, or transactional data.

So, that's one aspect you could be looking for.

So, between our process flows, where are we seeing these gaps to where we can refine or is a user spending too much time pressing different buttons?

Are we seeing too much time in between when a user goes from one location to another location?

Empresses, another process?

We're looking at these key pieces because when we see gaps, what we're seeing is that we can refine those gaps, meaning we want to make them faster and quicker, especially. Time is money. It's an important aspect and looking at organizational processes.

We're also looking at the process flow discrepancies. As it kinda mentioned, when we're outline, all the different steps within our processes were charting is out nice flowcharts. We have to define where there's discrepancies are.

Now, we can kinda foreshadow or predict basically as to what we anticipate or being expected or unexpected scenarios in accounting. But sometimes there are variations. This we may not expected.

So, I want to be able to find what these process flow discrepancies are and why are they not executed as expected?

Because those are, themselves, adds, value, And then it ... tunnel, mostly driven, data results, or AI, RPA type methodologies, and the bear gets expected outcomes, and we can find that to be able to incremental differences.

one of the key factors out of some of the projects that we've worked on in the past, is when we're building these large AI platform, sometimes the algorithm takes a couple minutes to be up and running. And sometimes we're define which type of data we're wrapping and pulling at specific moments will dictate and could alter the course of which the algorithm is expected to run.

So for example, good scenarios omics, I'm pulling data sources, and when these algorithms are running for process, I'm capturing data at a specific seconds.

Another second later, that data changes and it alters the course and the outcome of which that artificial data was derived.

Now, when we're actually going back through and evaluating how well our processes for forming, we can see this incremental differences and compare that against what we're expecting.

Now, I know I had a flaw, and could be able to alter the course of which, and how this process is running based on some of those values.

How do I evaluate it, too?

Another key thing is, now, we're done as a data file, like, hey, there could be differences, There could be opportunities here. But, should I be relying on all estate? And, the answer is no. Current patterns to evaluate how long non conformance has been occurring. So, we have a particular pattern which processes are expected to flow. What I want to do is now that we have this footprint, or this data, that our X axis, this is how my process sepsis line.

This is when things are occurring, is some of the data that I'm looking for, it's just outside. What I'm expecting, meaning is it's a one-time event, or am I showing something that happens daily, hourly? You know. one of the key thing is, is that we want to throw outside some of those outliers.

Outliers will throw off our opportunities for business cases, because what we're trying to, we don't want to grab the outliers that may be following a process that is not on standard for day-to-day practices. Otherwise, when we're actually analyzing how our opportunity is reforming word value, adding, we may not get what we're expecting out of the business case.

And evaluate whether the data utilized is accurate to begin with. That's a very key aspect, as does the data appear to be pulled from an accurate source?

Some of some of the key flaws, when defining a business case, is making sure you're using accurate data. Could you imagine what happened to a business case for using inaccurate data? I can promise you, we've done this before, I'd say most organizations have.

And sometimes is organizationally is also a little bit more optimistic. We'd like to lean into our business cases more saying we're going to provide more fruitful value, and we pull data sources that aren't always accurate. So, a key thing is accurate data.

And going back to those non non conformance datas, are there any Delta variants that should be excluded? So as a typical data analysis, we're going to take our highs and we're gonna take our lows that are way outside of our normal processes and exclude those. From our business case. We want to really refine the averages from which our business case data is pulled from.

Next topic is analyzing a potential business tasered poshest mining.
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We've talked about the different data points. We've talked about, what are we looking for to value, whether or not we actually have a business case. Now, let's look at the key different areas of a business case. There's many different ways you can drive your business case, but I would say there's three ones stand out in particular, especially to large organizations. Savings, how can we translate time into money?

If you've ever worked with Lean six Sigma practices, they literally, I'm looking at steps every steps matter, and a facility, and industry, and manufacturing.

Whether maybe it is time equals money, is somewhat spending too much time taking steps, or performing a procedure, to get to an end state in our process.

Lower expenses.

Another key thing is that, when we talk about time is money.

I'm also talking about lowering basically the number of people or number of processes that are having to occur to reach that end state. So I wouldn't be able lower our expenses to accomplish the same end result.

And efficiency.

I'll look at efficiency is not as a linear path, but I'll look at as multiple parallel paths or multiple threading of an application, even to drive duplicity, increasing efficiency to basically say, I don't want to split this from an A, B, and C process. I want to take this to an A, B, apart B, to C, so I can have multiple different variations of the same process occurring at the same time to accomplish it in short period of time.

Does that accomplishes savings, or am I going after profitability?

Profitability is the other key thing that we're looking at an organization. This could be incrementally our margins. I cannot increase the cost of a different item based off some of the sales ....

How do I increase my sales?

That's, that's a profit of marketability, Right? And then all seeing every type of campaign, ad, everything else that's submitted by these large organizations, should, and can be tracked.

Is my sales work result of a product, IE, are we increasing our products, sales, through the way that we're building our product? Or is it a result of a process?

I can we get a product or feature out to our customers in a quicker manner?

And customer satisfaction, I never want to take away from this aspect, because it's huge.

Especially in today's e-commerce world, everyone is actually expecting things much quicker, faster, and to be more reliable. These larger companies are putting a lot more pressure on smaller companies, just for identifying. They have the money to be able to invest in the technology capabilities to keep up with the growing demand. And the key thing is, our customer satisfaction is changing from previous errors. Previously, we were looking at the value of service, right, quality products, and we didn't mind taking delays because we understood that there is shipping cost or system issues that could occurred or manufacturing delays. Now, that's different. There are so many different ways to communicate and expand supply chain technology to get a product to a customer quicker and more reliably.

And I also want to take a step back from the quantitative features.

Quantitative features are the things that we can use to be able to build a strong business case, because it's something that we can be able to represent to investors and stakeholders. But the qualitative is another key aspect, So look at our organization, employee satisfaction.

Organizational leaders understand the value of strong employees.

And they also understand how much time it takes to train if someone operating into their processes and up to speed with how the processes are performs.

So they want to be able to retain those employees and employee satisfaction big to me. Customer satisfaction is also another key thing. We want to make sure that we're not only we're delivering a reliable results to our end user or customer. We also want to make sure that we're getting the feedback retained in this process.

Too, Make us either change what we're doing or refine our processes to get them their products.

Developing the business case.

How do I effectively define my business case value?

Now, we've identified which project performance, whether it be savings, profitability, or going after qualitative measures.

I want to understand translating the data to time H equals money, I, how much time can my organization save?

I've discussed in the past as two.

When you are looking at processes, I want to have every single footprint in data form.

I want to be able to represent this and extrapolate this data into time, between different events in my processing.

Mentioned this to be software. This could be inside of industrial warehouses. I want to be able to articulate and define how much time for my organization say.

And I also want to say, what are the salaries of those that are affected by this time?

I, if I had employee A, who makes a certain amount of money per hour, and this person is spending this amount of time performing this process, I want to evaluate every single input that user is having regarding all the processes they are performing.

And I want to evaluate, if I was able to modify third process design by this amount, how much time would that say, using the input that I have available from my data announces. I can then translate time-stamp salary, equals the savings.

That's where I'm looking for, that's allows us to start building a business case.

Profitability, same exact definition, or different way of looking at it, is translating the data profitability. How can changing our processes, it back my expenses? I want to look at manufacturing. For example, when I look at a process, uses to, this is when my equipment arrives, This is when I actually utilize that equipment. This is how long it takes to take parts, A, B, and C, to combine them together, end up with our end product to the user or the customer sell. How much time does it take? What are the factors that are affecting that time, and is there a way to actually reduce the amount that's actually affecting it?

That includes even changing materials, right?

Some different companies may ship out it. Different materials at different times. If I can get it faster from another vendor, or manufacturer to include in my product, I can actually reduce my costs there, as well.

And how many customers do not purchase items to a potential process, and how many potential business did we lose? I look at this to go back to the systemic portion. Talk by the manufacturer, sort of, let's look at it from systemic.

When a user is going to a checkout portion of any type of online or e-commerce procedure, what portioning do they stop, where you can track that an event logs When apportioning actually add this to my car. I had this add into my heart. I get to my checkout. And then I stop or pause.

Or I'm, well, how does they end individually.

They scroll, do they look at other different items, but eventually they don't purchase the items.

That information is vitally important to sales because as I mentioned, we can track how a person is utilizing our applications and then evaluate how much potential business are we losing do this.

So cost of what we could have been able to have and the utilization is, what business do we lose, eagle's profitability.

So, I think that also helps evaluate the business case and translate the data to business value. And here's an example for this, For the quality to how many employees we lose the potential process flow, are: either hiring or training.

Or, it could be, I do customer through employee feedback on their exit interviews, leaving a party for these different reasons process, flow, reduction equals value.

And evaluating the cost, that's the final key piece, is what are the costs associated with modifying my systemic processes?

Is it software modifications that require I do?

am I, having my users click too much before they've actually reached the end process?

Can I provide an autonomous method of delivering results to a user this quicker than having my current structure of utilizing that data?

Database architecture, this is another key aspect, as I mentioned, is sometimes, we are architecting our data in a format that makes it a little bit too difficult to pull out the end results we're looking for. So, do I need to define this? database arts briny to develop more views? Do I need to be?

Even how the queries are running against a database to make it more efficient, and my train is my algorithms, or even AI technology taking too long to pull the results desire, or operating system. Am I not getting that feedback? And then it, within an operating system, could be switching to another operating system, it has a high performance rate that can be optimized my system a little bit faster.

Or, the key thing is going from a systemic portions to a physical process, hardware space, As mentioned in each industry, we had the physical aspect to. are we taking too long to allow our customers to check out our items based out too far?

Were a customer walking too far distance between one like diet and to another life?

Could we allocate those different items into a space? Allows more user for a customer to be able to identify and find those items and be able to sell those items Or workspace.

When I'm actually use, let's say I'm working at a checkout file. Could I be doing two things at once rather than waiting on one thing to complete?

All these different factors are important.

Even in physical layout, as I mentioned, there's many different ways in which a person can be able to utilize their space more efficiently and re-arranging that space could be able to help.

And, What are the costs associated with changing my manufacturing costs, equipment? Do I need to be switching to other type of materials that are a little bit easier to mold, or are they a little bit easier to manufacture?

Materials.

So, do my materials cost, change, device, watch those materials, cost, gradually go up, or go down could, arbitrary node material, smell things and could have been using equipment in. Ways that can automate things a little bit more efficiently working in supply chain industry. All a lot of the things we're going after today is all about automated in that and utilizing robotic arms, HGVs, whatever, it may be, some type much harmlessly driven out.

And finally, it's real simple equation for this return on my investment to build a business case, as the number one thing, that any type of investor Staples, going to ask and wanting to understand is what is my return on investment? It's very simple, your profits, but about the cost of their investment, and the 100%.

Or if you're looking at your overall process for a business case over multiple different years, current value minus your cost of an investment.

So very easy math to do for an easy outcome. The key lies in the actual data to be able to build the business case.

And finally, I want to summarize that with any project or for business organizations have to evaluate how successful they are. Are they successfully being able to work through the expected results?

They are intending to have KPIs or key performance indicators are vital. A key performance indicator is really utilizing the exact same data. We can use surprises mining. Is a measurable value that demonstrates how effectively companies cheating key business objectives.

Are we achieving the expected or our library expecting? If not, how is it adversely being affected?

one of the key aspects of building up a business case and developing a project or program is, is once we're modifying or implementing our project, we then have new track of data inputs.

As he, we are now changing a process. We're implementing a new process, and as a result, we need to have define new trackable, data endpoints that we can then use to extrapolate into key performance indicators, Census track, how successful are doing.

Funny thing is, there's no difference between identifying a business case and the process you go through, to evaluate how successful a new project or program has been implemented. It's still utilizing process mind to be able to take the data and implement into a usable form for us, to be able to understand how well we're doing.

Um, if we, if, for example, if we're not able to achieve our business objectives. So, we can always go back and add more data points, right?

It goes back to, Am I able to achieve what I was able to expect to achieve?

And, if not, what am I missing? What information I'm missing, and how can I be able to apply new inputs or new data? To be able to extrapolate?

Why were adversely being affected through the new process?

And then I'll, I really say this. I want to extrapolate the data to identify additional area of opportunities. You see the graph that I have up on the screen kinda shows different ways.

We can show to stakeholders how well we're doing.

Communicating that progress is very vital to business and organizational structure. And some people do it weekly. Some people do it daily, some people do it monthly or quarterly.

However, big investors want to know how well, and how much the worst success we're seeing through our new processes and procedures.

And that brings me to the conclusion of my brief.

I hope everyone enjoyed it, and I look forward to hearing some of your questions.

Kaitlin, fantastic. Reveal, and the Presentation, we really appreciate that.

I'm gonna ask you to go ahead and stop showing you the presentation screen, so that I can bring my camera back on and we are, we have questions from the audience and, uh, and also, we.

Let me just reposition by the questions from the audience, here, so I can see all of them.

But the first question I'm going to ask with you, for you, it's actually thank you first for going into the basic fundamentals of building the business case.

And, because, I had alluded to that a bit in my previous session. That sometimes, you know, technology can be a solution looking for a problem, and the.

and the, and there are some, not so good things about that.

And you'll go through the business case perspective on how you build that and looking to try to understand what the issues are.

And really, that translation to value creation, which you make very good case for, and ah establish a flow, why do you think the organizations and people struggle so much, should build, to understand what the, how value is created or destroyed, in the process?

Because my, my experience, the experience of our audits, reflects that on the questions as well, is that, people really struggle to come up with, you know, they come up well. They tell you what's not working. They may even have some evidence that it's not working, but when he asked them, So what if we put a team to work on this? What is the annual value creation that we can get out of this, and they like freeze. Why do you think that happens?

So often organizations, I think there's two different aspects of that.

Um, a lack of true analysis is one, you know, maybe they're, the data points aren't exactly what they were expecting. So I would say that a lot of people need to be inclusive, as I mentioned before. You have to know where you're wanting to write, and what modifications or issues could occur along the way to be able to ensure that your system is built in a way that you can be able to extrapolate that data any usable.

So, if the data is not readily available in a usable form, then you will struggle, You will struggle with being able to identify flaws in your processes.

I think you're going to also be able to struggle with, How do I define what profitability or savings could be attributed to these data margins? And you're also going to struggle with the other key things, being able to represent it to stakeholders.

Um, one thing is analysis. Another thing is getting people to buy into your analysis. And, to your point, I think having it, all this information in a usable format, allows it to be a little bit better to use.

And I think the number one thing that I've seen, and I've seen a lot of organizations struggle with, is actually being able to produce in a usable format to investors, finance, individuals. They really want to see everything driven down to an annual data analytic perspective.

And it's gotta be clearly articulated in a format that they can Angela easily digest. And not hat. And having it in a way that's not usable is going to make that a lot more difficult.

Very well, do you find that people struggle with having access also to the right data and information, especially the cost data organizations can be quite protective. They will not tell you what is the rate for a certain functions, for example, or is it costs a certain products? And the even finance organizations can become totally protective of that type of data.

Here is if you part of question here, curious if you have experienced some of that? and maybe a why are some of the potential workarounds those barriers?

That's a great question.

I think as organizational leaders, we have to be open And open.

Meaning, when we're actually staffing to meet the demands of new projects or refining or even bringing in consultants, we can't be closed whole other information. I think a lot of organizations to your point don't want to give some of that exclusive material away because it's going to demonstrate that there's flaws. And people don't like flocks. But I think we have to be open and honest herself that these flaws exist in every single business, an organization, and our goal as leaders, and is to be able to prevent those falls, or at least make adjustments to mitigate some of our profitability or savings loss. And in order to do so, we have to be able to be open with our information. We also have to position people in the correct locations where they have that access. I don't think everybody needs access, but I think the people that are able to build a business cases should have exclusive access to that information, and it should be baton between each organization position as people in the right locations.

Very well.

Switching to a bit more specific questions that came up related to process mining, on your experience, staples, of course, your experience, and other organizations, and industries prior to that, as well.

As you look for, as you look at opportunities that are conducive for greater value creation with process mining, is there a kind of a profile of what those processes may look like that you have, that, that there are certain characteristics of the process, that, that, that make it attractive for process mining applications in your view?

Ooh, that's a hard one.

And now, let's say it's been different per industry.

When you're looking at systemic processes, I'd say they should all kind of resemble each other a little bit. What I mean by that is you have an end user input which is then tying back into an application and an application can tie right back into a database of some sort which is utilizing fundamental data.

And I'd say with inside of that, they can all be resembled the same. And I said, you're really going after time.

You're going after time, where you're seeing people stop utilizing your application, your same process flows, but then, how are you? Utilizing your applications and time is a humongous measure, as well as time, the identifying exception cases there are, errors are things that are occurring within your application, which should also be logged in, creating some type of delay.

But when we're talking about physical processes, that's very difficult. And, or manufacturing, where they're dealing with different types of materials, and processes there? I'd say they're all very different.

And it really takes understanding to a significant level of detail what the process is at the lowest level, and how do we measure it?

And how do we measure our intrinsic data that's driven at those lowest levels? And I'd say that is very difficult to understand.

And I think that's another key aspect about each industry that deals with those physical aspects they struggle with, just because they may not have placed enough input to a systemic driven system, to allow us to be able to extrapolate that. I mean as I've been in places where they're still using Literally stopwatches to time people.

And I'm saying well why can't you put some type of? buttons or systemic portion where there's feedback from people saying that this portion of the process, rather than relying on timesheets, right So it is thinking outside the box of how do we use software technology to leverage those data inputs to perform better?

How do you approach technology applications and opportunities and the in the in an environment like Staples, do you, do you look at, because there are two fundamental ways of looking at it? Right?

You have some problems that, you may have and you may and the and the and then you may look at potential technologists that could help you solve a problem The other approach is I have a technology or like process mining and I am I'm looking for Maybe an era of the business where I can leverage that technology to create disproportional value.

How do you go about identifying and prioritizing process mining opportunities?

Great question.

And I think that also ties back into, especially at a large organization, like Staples, Wal-Mart's Amazon's, especially in your e-commerce and sentiment strategies. It's a very supply chain is a very complex unit, and it has a lot of demanding moving parts. And I think one of the things and feedback we get from opportunities is really being in the field at the lowest level, looking at those opportunities. And being open to feedback.

I think one of the key things, even makes every engineering group is being able to listen, I think, being able to listen to what other people are saying about the process, like I've been in a cafeteria with some of our drivers and just being able to listen. What's things, are they talking about that I could think about from a software technology to improve their day to day tasks now, or inside of a warehouse? What type of things am I listening to the break room, where these workers are fulfilling e-commerce customers carts?

With things they complain about. What are they talking about? Having to input too many different things to basically do a simple task. Or thinking about taking too many steps to perform different tasks, all these things are important, and, I think, listings step one.

And step two, is, then evaluating as to what solutions could we provide to be able to accomplish that problem. But, the problem really comes from the lowest level, I think. And the lowest level is really just, who's actually performing the task. That's who we should be talking to.

Very well. Are there any specific areas? Maybe if we can be a bit more specific about areas? Where are you implementing process mining. Of course, you know, understand there's some proprietary things that you can talk about.

But for those things that it's OK for you to talk about, is this, are there areas or process mining are really helping you create value right now? Be the procurement may be auditing, maybe, E-commerce. Just curious about, what are some of the areas of the company, where process mining is delivering value for you today?

Completely. So one of the key areas that we focus on is I guess when we look at what are opportunities. I go back to where is most of time spent because what we're trying to save from the Filament Strategy and that's where I work and more or less. Supply chain side nonetheless, cells in the marketing side, is, I really want to focus on how do we implement autonomous solutions to solve the saving side of things, right? How do we be more efficient inside these large warehouses, talking about a million plus square foot warehouse, with couple of hundreds of people working in these warehouses. They're all doing different processes to fulfill customer orders.

And, what I wanna look at is what steps are required to perform in each function of a facility you have receiving. I have the picking strategy, we're actually individually identifying the items required for customers orders.

We have the shipping address back, we have the transportation, and every single aspect of these processes have a measurable input for us to be able to say, These people are spending this much time doing this allocations. And when I look at that time, I'm going to take the one that we're spending the most amount of time and evaluate, are we the most efficient we can be?

And the answer is usually now. So, let's tailor that. I wanted to take process mining by identifying how long it takes in between each process, a users having to accomplish a step, which, in our case, is really the picking strategy, individually fulfilling customers orders with items.

And I want to say, if it takes this many steps to reach this location, I'm literally watching the systemic, the exchanges between the application that they're using to identify the items, the time actually grab the items and put it into the customer's order to be delivered. At a time that order is actually received another part of facility. All those time calculations have been in effect And as time calculations, as mentioned earlier, eco saving opportunities, we can make them more efficient. And always goes into ideas.

for example, do I need to, if we're getting savings, for example, when we go on sale with different items. If I go on to see all the different items, I can expect an increase of those quantities as an item being order, right? So, all in a position that, in a way that's in close proximity for a person that's picking that item for that customer to be really close to. I don't want them to walk on the other end of the warehouse. I want to close.

So, analyzing this strategy, as in the physical aspect and aligning with systemic measures to make it more efficient, that's what we're going after every day.

Very nice, Very good view of how you're approaching those opportunities in the organization.

What has being the, I mean, my goodness, you have been doing intelligent automation at the company, not use specifically, but the company has been doing intelligent automation for many, many years.

Whoa, What's exciting in the next six months to a year? Kind of like the next steps on some of this internal and external improvements and uses of technology, anything that that's in the horizon. That's kind of the next step.

Absolutely. I think whether it be manufacturing or supply chain industry, we're implementing new, autonomous message. And I say this outside of systemic, I wanna look at robots, HGVs, autonomous guided vehicles.

There are so many physical technologies out there that we're able to utilize to accomplish what we've previously relied on a slew of different employees to manually move things, IE, oh, I think about how many times it or how many workers it takes skilled workers, labor workers. They have to be able to utilize forklifts, to travel up and down. These aisles grab pallets of different product and transport them to another side of facility, like, in manufacturing, where previously steel was carried by these workers on forklifts, and other type of material handling equipment, and now we've got robots moving everything.

And autonomous guided vehicles, driving these things, are based on this.

And every single time, I'm using some type of robotic measure to move something. I'm adding a new data input to a systemic measure. And I can actually go in and utilize process mining for. So, I'd say that not only are we actually increasing the amount of data, we have to be able to use process mining, we're also creating a more simplified solution.

That's fantastic count. Caitlin, thank you so much for sharing your expertise, your practical perspectives, on intelligent automation, on for value creation, On behalf of our global community.

Again, we want to extend our deepest gratitude for you to take the time to be here with us.

Now, it's been an absolute pleasure. Thank you so much, and I really do appreciate the opportunity and great questions to everyone. Thank you very much.

Thank you.

Ladies and gentlemen, scale them Harris, Director of Controls and Automation Engineering at Staples, some exciting things are happening with intelligent automation and process mining at the company. And as S, kailin cover so well. And, and and the, the, the fundamentals of building the business case for intelligent automation, and M, process mining, very, very helpful as well.

So this wraps up day one of process mining live. We are going to set up what's coming up tomorrow. So a bit of a preview here, quickly through the agenda for tomorrow we are going to have software AG, discussing process and task mining, Hybridizing solutions, to harmonize insights. Then we're gonna move on to presentations across multiple industries, including Twitter. We have Andrew Kirkland, who has seen a Senior Program Leader at platform health operations at Twitter. Who is going to be talking to us about process mining as a digital transformation accelerator?

And tomorrow at the end of the day, tomorrow we have not one but shoe industry leaders coming from the UK. And one is Mark McGregor and we also have Sophia Passover discussing with us the process money and the title was very suggestive.

All that Glitters is not gold why broadening your approach to process mining is the key to long-term success. We're going to again have Margaret McGregor who is an industry expert in intelligent automation.

While along with Sophia Passover, who is the founder and President precedent for a stereo logic on the on not only a narrow view not just look at the process mining narrowly, but looking at it broadly in the context of intelligent automation, and all the different options that you have, and, And how do you extract the most value from this potential suite of products and services that exist.

So, very practical view of the prioritization and implementation of this technologist for value creation at scale.

Excited, again, to welcome this great cross industry leaders to our program tomorrow. I want to remind everyone that you will receive a recording of all the sessions as a registered participants a week or two after the sessions are completed and the post-production team has worked on the videos. You'll be receiving an e-mail with a link and password, to give you full access to each one of the sessions, this is only possible because we have the best sponsors from process for process mining from, around the globe with us. So I wanna say a big thank you to our sponsors salon. Is Abby software, AG and sterile logic for making it all happen, Bring in this level of content and great qualified speakers and industry leaders at no cost to all of us on a global scale. So thank you. Again, Salon.

Is Abby, software AG and sterile logic for making this all happened for us. So between now, and our, first, our first session tomorrow, you can check out our link on LinkedIn for the discussion about the conference. What speakers are saying, where participants are saying, I'm gonna put a short update on today's presentations right there under the comments section. And you can find all those, that information on LinkedIn, under my name and the posting that I have for the conference. Which is, which is the last posting that I have under my profile. So, you should be able, if you have an opportunity to drop by, say hello. Say, thank you to our sponsors. Say thank you to our guest speakers. Ask questions to them, because they also check that, that communication, And if you want to connect with them, connect with them directly.

Right there on that posting, I have the LinkedIn for everyone, all the presenters on the conference. So it's an easy way for you to connect with them. So, for now, thank you. Have a wonderful rest of your day, wherever you are in the world.

About the Author

Calem Harris,
Director of Controls and Automation Engineering,
Staples.