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Courtesy of Twitter's Andrae Kirkland below is a transcript of his speaking session on 'Process Mining as a Digital Transformation Accelerator' to Build a Thriving Enterprise that took place at the Process Mining Live Virtual Conference.
Process Mining as a Digital Transformation Accelerator
He is Android Kirkland.
Android Kirkland is an award winner engineer at the intersection of Tech and Link business design who has led transformation initiatives for world renowned organizations. Andrea, I'm going to ask you to make sure that you turn on your camera so that our audience can see you coming in with us.
It's great to have you with us, Andrea. As I was saying, he has led transformation initiatives.
For a world renowned the organizations such as NASA, Nike and Amazon busch, InBev, His current role as senior program manager at Twitter, Andrew leads solution development aimed at elevating platform health, using technologies such as artificial intelligence, machine learning, and robotics process automation.
And he's here today to talk to us about digital transformation and an accelerator for digital transformation, running through robotics, process automation, and process mining as well Android. It's a real pleasure to have you with us. Thanks for taking the time to share your expertise of our global audience today.
Just say thank you for the opportunity. Good morning to everyone, or good afternoon, good evening where you are in the world. But it's a pleasure to be here. She's a, it's always great to see you, and really excited to share the content that we have with the prepared for the group today.
So, today, if you don't mind, I'll go ahead and present, Start showing.
OK, so, I'll try so everyone can see the presentation deck here.
What I'd like for you all today is really the discussion around process mining, and how it can be used as a digital transformation accelerator. Right?
How we can get those transformation initiatives identified, evaluated, really processed and deployed as soon as possible. I do have some different, will say, methods that have been historically used, and kind of how that compares to process mining or how processes many compliments those different methods.
So, without further ado, let's go ahead and hop into the content for, the journey standpoint, really, gonna go into an overview of process mining. I think this is one of the points where day one presenters have an advantage over day. two and day three, where for you, all who have been engaged with the different with different presentations. You all, Have had this discussion, multiple times, now, in terms of what is process money?
But for those who may be joining us for the first time, or who are still working on getting that, understanding will touch on that for you, Then we'll talk about setting the Foundation, excuse me. Process mining, again, deals with process, right. Not to do, it's very intuitive there. But, really wanna understand, what are the current ways of working. How can we use that insights gained from process minded to uncover those gaps and pay points, understand variances within processes horo our team members, are carrying out different processes. So, what's that foundation? Alright?
Then, we'll talk about that transformation roadmap, right? We do have that process mining those activities as accelerator, to get those insights, to get those, that data as soon as possible, to then build intelligent strategic plans and intelligent allocation of our investment resources, right?
So that's what I have planned for you today.
Now, before we get into the meat and potatoes of the discussion, I really like to introduce this concept of intelligent automation versus automating intelligently. Right, when we look at process mining, as it relates to digital transformation, I'm not sure if you all attended the previous discussion, but robotic process automation was brought up, right? We go through these different activities of process mining to identify ways we can automate processes to make the process more efficient, more effective, experience higher quality, all the things, right?
So, intelligent automation really uses its focus on using technology to automate those processes and those are people workflows, but that's not the same as Automating intelligently. Right, when we talk about automating intelligibly, it's, what information, What data are we using to define the process, to understand what we need to automate? How should we automate? What process changes should we make to optimize the process before automating, Right? And that's where process mining. And, as it relates to process discovery, really shines, because it allows us to see those different variances in the process, OK?
So I like to say, that's the difference, that makes a difference. That can really make or break the success of a transformation initiative.
So, as you all go out into your organizations and talk about digital transformation, just understand or remember that intelligent automation versus automating intelligent discussion.
So, getting into it, Process mining, you know, this is really the, the, the, the way we can define, objectively what we should prioritize, and what should, should be de prioritize, alright, We're talking about data, driven insights, analytical methods, to really uncover, and understand what our current ways of working are, all right, what are the business operations that are carried out through a series series of processes or workflows. Alright, and then how are we performing against those workflows, and those processes Are our team members carrying out a standardized process. Do we have beards is within how they go from Step A to Step B? All the way to Step C, Alright?
Those are the types of insights that will help uncover pain points, gaps, issues, quality errors, et cetera, within our processes. And, that's really the heart of process mining, and then value, right?
Taken, click down to that, alright?
If, again, if you've been on the different presentation, to this point, you're familiar with these three questions of: what is the process? What should be happening, and what is actually happening, right? So, when we talk about process, mining, and are, as it relates to our business, critical workflows, you know, what's the end to end business operation? What are the different inputs and outputs of that operation? And how our team members going about delivering those inputs and outputs. Right? That's, you know, what sets the expectation of what should be happening. What are the intended outputs, and what is the expected quality or output quality, right?
Once we look at that, and ask those questions, then we can now set the foundation. Or, once we layer on process mining, compare that to what is actually happening. Right? What's the process? What should be happening? What is actually happening? based off of insights that we gain from process planning activities, OK?
When we talk about those three questions, it turns out taking expectation versus, but the, the output is no.
For all of our operations folks on the call, you're familiar with the process districts, process centric design, right? Driving that process alignment, kind of understanding our current ways of working, especially as ways to cross functional silos, You know, what is the end to end process? How do these team members work together? What is the expected, again, output and quality that is needed to prevent downstream issues and downstream variances, right?
That leads us to the gaps and pain points.
How can we uncover issues and improvement opportunities given the current operational landscape? one of the extreme value adds a process mining, is that we can rapidly identify those variances, right?
Because, obviously, variance affects quality, affects experiences, whether it's customer service, or product performance, these variances tied to gaps and pain points. You know, we go through the exercise of separating out root causes versus symptoms. How do these variable, these variances, within our process? Are they a symptom of a process variants, or are they the root cause of downstream impacts, Right?
So these are all the questions that we can get from process mining, and setting that, that foundation of understanding what should be happening versus what is actually happening.
And then that Segways right into, as you all are probably already familiar, the Process Optimization piece. Once we have those gaps and pain points identified, once we know where the opportunities lie, now, we can start developing, building out that transformation roadmap, in terms of getting to that transformed, future state, optimized design, right? All in the name, the delivering value to the business, to our customers, to our stakeholders.
So, again, you're probably all familiar with process limit gaps, pain points, and process optimization, and then feeding that into some historical ways. We've carried out though, that different, that workflow, right? What are different ways we've kind of driven that process alignment understood the gaps and pain points in the cupboard And what the impact of those caps the pain points are, right?
So, as a Lean six Sigma Black Belt, you know, myself, I have use five why, Kaizen events, chatting obsessions, functional interviews, All all the different tools that are in the toolbox of a six Sigma professional Improvement, Infest professional. And I can tell you firsthand that they are time time intensive and resource expensive, right.
If you all have gone through any of these activities, you know how how deep a Kaizen can get into discussion, right? I'd just like once a couple of weeks ago, week long and I will tell you, the hardest part of any Kaizen event is really getting that current state, right? Getting what the feedback is. An understanding of the current state, from the different stakeholders and team members who are carrying out the process. Who or who are stakeholders in the process. Getting that mutual understanding of what's happening today.
By far and large, that's the hardest part of the event, right?
Process planning allows us to do is capture that current state objectively, right? When we talk about five Whys and ... Index. And anytime people are introduced into, say, our process analysis, there's always that subjectivity or that bias or that heartburn in terms of wildlife. So and so this was working or if we add new technology or system, et cetera, all right, you're always going to get that feedback and those those people oriented process evaluation methods. However, process mining helps us or complements these different methods because it provides an objective way of gathering that data objective insights because it's, the proof is in the pudding, right. It allows us to see the different variances, then we can go and ask a ball using the five, why. Why do we have these, this number of variances in the process, right, in the answer. But by now, that, several times, until you get to that root cause, right.
Or, you can use it as an accelerator to your Kaizen event in terms of it from our process meaning outputs. We understood the process to be this right, what's actually happening versus our expectation.
So you've completely the NSA foregone, but you shrunk that current state discussion down significantly because you are starting with a benchmark of what's actually happening, as opposed to different viewpoints of the current state, right?
Chatting sessions, functional interviews, again, you all probably know how, how time intensive, those are, as it relates to gather insights, right?
If I'm shadowing on a one-on-one basis, or want to know a handful of folks, and it's, it's going to take some time, to gather the insights that we need to understand the process, Understand the pain points, understand, what are the opportunities that exist for transformation.
I will say, for a project that led to my previous employer, When I was Director of Business Transformation, Appian as a Bush, alright, we were able to gather tens of thousands of transactions. just through process fighting over a couple of weeks, right?
We're talking about tens and thousands of trans logistics transactional transactions using scattering sessions or functional interviews that were taken months to go that much insight, right.
So, again, speaking to the strength of process planning, and how it can accelerate and complement some of these different, historical or traditional methods, that's where it really that the value of process mining offers, and how it can help accelerate your digital transformation efforts, OK?
Great segue to enable transformation! Right.
You know, any transformation initiative is going to tie to that org vision. What's that top down? Or overarching plan for the organization? A lot of times, it's dealing with operation operational excellence, at cost reduction. Or enabling customer experiences and driving value in that regard. So what's that or vision, right? What's the objective? Again, keyword objective data, that represents what is actually taking place in our business or in our organization that ties to what that overarching or patient is. Right.
We just went over different ways that historically we've captured this information, wasn't necessary objective, Highly subjective. But we work with what we had, right? We were able to, to kinda sit out. The variance is the noise versus the signals and get into the true gaps and pain points that we can identify, without a tool, such as process mining today.
Built into a strategic plan, right?
Those strategic plans, it's that planning and allocation of resources. Or that enabling digital transformation, right?
However, with process smiling, because we do have that objective data, what about what's actually happening in our workplace? Now, it's much more intelligent. So, if you recall from first the, one of the first slides I shared with you that automating intelligently versus intelligent automation, this is an automated intelligently. Because now we have that objective data to really backup what we need to, to invent where we need to invest with opportunities like, and how we can best transform those processes. Right? Or a call from one of the sessions yesterday.
one of the questions popped up was, you know, how do you get that buy in from different stakeholders to pursue these different transmission initiatives? Well, if you have that objective data in terms of, Hey, this is how we're operating, this is the expectation, right? It's costing us $10 million, or a million dollars, or whatever that, that justification that business justification is, that's gonna get some attention. That's gonna get some eyes. Looking into how we need to roll these different initiatives into our strategic plan, Because we're much more intelligent on where opportunities are based on objective data we get from process mining.
Wanted to share a case study with you all, for my time here, Twitter. And my scope, as soon as I mention, I'm focused on platform health and platform manipulation and how to make the platform as safe as possible To challenge, as you all know.
It's, it's it's It's been very hot, hot topic, and public discourse. But what are the operational processes that help us get to a better point, or platform manipulation from people, from preventing people, from taking advantage that, the platform to abuse? Or what have you spread information that may not be of high quality on the platform? So, real quick, immediate use, Twitter services. in a manner attempts to artificially amplify or suppress information. That's at a high level, what the Scope of Spam and API operations are, OK?
As I clicked on it to that, what we typically see are fake accounts, whether it's still a profile photos, copied bios, or artificial engagement. You're selling and purchasing followers to increase your will say the notoriety or kind of your credibility in that regard. That's another thing that you see from a spam standpoint. And then malicious content. Again, misleading or deceptive links. Phishing campaigns, things that are used to take advantage of our users, and really threaten their their internet and social well-being. Right?
So these are things that I deal with on a day-to-day basis and that I'm looking to tackle. Right? So in this space, it's how can I use process mining? How can I use these next level tools to then elevate, platform help and protect our users and their safety and their social well-being. Right?
As a quick example, cryptocurrency spam.
You know, this is something that if you're familiar with cryptocurrency, it's taken off hot topic and public conversation now. So, so, there is a propensity for bad actors or adversarial users to try to take advantage of other users, right?
So, three metrics that we really focused on The screen prevalence, false positive rates, and case review, right? Now, you're saying, well, how does process mining kind of tie into spam and online operations? While what we can see is, how are our agents who are reviewing this type of content, actually, on this type of content? What are they doing to check, right? Or, is one user going from another tool? Or using one tool going to another secondary tool? Or are these is a user agent, really focused, and sitting in one specific tool, Right? Because that's what process is, it's, the logs from the different platforms that we use internally to carry out the different processes. So, you know, we can see, kinda clicks, and the events that are taking place in terms of researching to come to a decision on whether or not how to actions against the specific account or specific case as it relates to these three metrics, OK.
So, again, that's a quick example. It looks like I'm moving pretty quickly here, in terms of the time, but what we can do is hop into some questions, and I'll pass it over to you for some Q and A.
Outstanding. Andrei and I will I will ask the audience to continue to submit your questions as we carry on the conversation here with Andrew. Andrew, I'm going to ask you to stop showing yet. There he goes, Stop sharing your screen so I can bring my camera back.
And that's, That's terrific. one of the questions and common themes that came up. First of all, thank you for the presentation. Grading Sites there was a comment made earlier when you're talking about the kind of Kaizen in the context of process mining, and the very valuable, because, although it's, it's fundamental to a large extent, when we start talking about process mining and digital transformation, sometimes, it's easy to divorce ourselves from the reality of the business. And, which means that you often need to get people in the room to have this discussion still about how we're going to do certain processes. How are we going to design things?
And, and we'll talk about Kaizen, You made a comment that, that, although Kaizen is, this meant to be, you know, rapid continuous improvement, and people think of it as small effort. In reality, there's quite a bit of effort to do a good Kaizen. Absolutely. That people appreciated the comment you made there is a comment based on experience.
Yeah. No. And that's the challenge that I'm dealing with right now. I'm preparing for a Kaizen event next week. And, you know, there's a lot of pre work that goes into these events, obviously, the week of, or the days of a lot of time, and energy and effort from several different functional stakeholders. Right, and then the output.
So, you got at least three weeks dedicated to one event, whereas process mining, again, speak from experience in three weeks, I can capture tens of thousands of transactional insights to then go into a, you know, I completely bypass the current successes because the current success with his hands. Right? It's in the reports, it's in the logs, we have that insight. So, I'm glad that resonated with whoever was an audience, because it's, it's definitely a True point.
Yeah, You know what? We're no end to follow up on that as you know, you know. You have a background in Lean six Sigma, Lean six Sigma, Black Belt, and the and the, and that gives you, in my opinion, more of a fuller picture of for the improvement by using intelligent automation and automating intelligently as you made the distinction very well as well as was noted.
Um, and, uh, and as you do that, in, as you automate intelligently, you're always looking for not only the data that process mining can give you.
But, also, it's very important to understand the context of that data. If I'm going to quote, you know, Walter shoe hard from the 19 thirties, you know, one of his great quotes is, that data is, it, data is meaningless, A part of its context.
Meaning that, we can also look at the process, mining feedback and see the loops and all of that.
And, they could be meaningless. It depends on the context, right. And, I think having this human touch points with the digital, with the, in this case, the process mining reveal of the flow making those connections is, is quite important. And I think you make you made that case in your presentation as well.
Yeah, absolutely. And you hit the nail on the head in terms of data without context, Now is, it's me. And they say, it's just numbers on a spreadsheet, right? So that's why I made that distinction of yes. We have these historical tools, such as Spotify interviews, chatting sessions, et cetera, that, while process mining can complement these things, it's not necessary replacement for these things. Because the context that we get out of those discussions, that really helps tell the story. Input, again, context behind what's really going on? What's the date when the data is showing us? So absolutely, it's not a replacement, but more of a compliment? For Sure.
Absolutely. And especially if you expect people to have a change in behavior associated with that process, They, they, you know, it's important that we get there their immersion and buying into what's going on there. Let me shift into something else here that came up as I look through the questions that continue to come. And please continue to submit those questions. I'm going to get to as many of them as many of them as possible during our time here.
Andrei, you have a unique background because you had experiences where you're doing very tangible products and services with previous organizations.
And now you're in an organization that was born digital and and there is a difference between an organization that, Well, that's another going at digital transformation that was born digital, versus one that was not born digital. I'm curious about your reflections on both types, and it may be, you know, the advantages and disadvantages. Maybe a little bit on both sides, you know, both about being born digital and transforming, and not being born digital and attempted to transform, What are some of the things that you have learned along the way?
Yeah, that's a great question. And it's, it's very relevant to discussion of having a matter of fact.
We had a conversation with a former colleague of mine, and we were, what I mentioned was operationally discipline. When we look at companies who are producing, tangible products are tangible deliverables to a customer or stakeholder, you know, it's, it's, they have that operation, those those process flows, Things that have been in place for an evolved over years, and years and years. Whereas a company that has, is relatively new, relatively young, 14, 15 years, especially in a digital space, that operational discipline, those processes, aren't, well, well defined, aren't, well, documented, You know, there's a lot of tribal knowledge, which is always good, right? We'd love tribal knowledge, as great as it is.
You know, we want to get those documented, so that the difference is going from one specific place that has, or industry or area that has documented processes, robust processes, quality metrics, et cetera, where you can kind of use that as a launchpad to define what those transformations are. Kinda, what we're going to do to transform, using, process, mining, to gather those insights, because maybe that low hanging fruit wise. You know, it's not as, as as, available, as much available was historically. So, how can these Advanced tools, such as process, finding help uncover those deeper insights, Right? So, that's, that's all on the one side. On the other side, the flip side of that, is where those processes aren't as modified and aren't documented. You know, your process mining layer process running. On top of that, you're going to see variances all over the place. And that's why you see, just in terms of person to person, process the process, And especially, we'll look into end, Right? So, that's really some big difference.
The key difference that I see in terms of that having the operational and discipline and the challenges that it provides in terms of, you know, just tons of variance versus, you know, things that are well established, working well, and now, how can we transform those. So.
Very, very, very, very, very interesting. Thanks for sharing that. Now, you are in the, in the platform now.
And the display form has, you know, very sophisticated algorithms that are running all the time. And then there are some user interventions as well.
I'm curious about, how do you overlay, or is there any level off overlay between, you know, what you're doing as A, as, not as a news, Well, perhaps as an user, potentially, but I'm thinking more as an administrator for the platform, or, and along with the algorithms that are taking place, you know, And maybe assuming some applications of artificial intelligence, and then there is process mining here.
Is there any any sort of interaction of process mining with this? Other areas of AI and, and the real?
Administrator, management of the system, or process mining, is a bit a little bit on the side, still, at this point, and it's kind of a separate activity.
Yeah, that's another great question.
Know, one thing that I see as a gap is that feedback loop, right, What's happening operationally, versus what do we need to do in order to make our algorithms for intelligent, you know, when we look at process, mining and the variances in insights, it exposes, You know, it begs the question as to why?
Why do we have so many variances? Why do we have a high rate of 90% rate false positive in terms of what is actually flag versus not flagged as spam? You know? If I see 95, 90% false positive rate, I'm asking, well, why even have the algorithm in the first place, right?
And so, that's what the, the insights and questions that because we have these these process level insights, we can ask us more intelligent questions and more targeted questions versus going in different interviews, Kaizen, event for next week and next week. You know, those are much more broad based questions versus with process mining layer on top of that, again, much targeted much more to the point. And then we can now feed those back to the product teams and engineering teams, who are developing these models to make them more efficient. So Bear cobbler complimentary and not siloed in that regard.
Thanks your question.
Yeah, absolutely. So there it seems that there's still some, some room there to start merging those two. Those applications, that's, yes. That's, that's what I took from it, which, which makes sense. I think that, you know, it's, uh, it's still a bit of an emergent technology and you have some things in place already from, from the perspective of your algorithms.
That, um, you have to pick your battles to make sure that's the right battle to fight, you know, and the right technology for that, for that, for, for what you need.
And, in that respect, one of the questions that came up, it was, why would Twitter use process mining at all?
Because you may not need it, It's maybe you have lot of automated processes already, and maybe there isn't a whole lot of value from process mining, is there?
Yeah, so that's one of the assumptions that I came in to into Twitter with as, well, you know, you look at the global scale or the organization, you look at the reputation, advanced models, what, you don't really think about the processes behind them, right? Now, think about how manual these reviews are happening, you know, what the backlog of hundreds of thousands of cases and a one-on-one review process, right, and using the different tools to review, these different cases. Now, again, that's when I bought it from the case study, is, what are the different, how are the team members using these different tools? What are they clicking? What are the researching to make that decision?
From there, what's the, will say the action rate and disposition rate? Because once we get that insight, then that ties back to robotic process automation because we're actually and we're doing these different activities and we can see that standardized process that elicits the best result. Then, is that something we can automate? it? Yes. Perfect. If not, then how can we transform or building more intelligent models? Getting back to that feedback loop, I was mentioning to complement what we see on a 1 to 1 review basis. So, that's the, that's that's the high level, without getting into the details, about how process, when it can definitely fit within the work that I do specifically Within Twitter.
It's a great reminder that even organizations that or are bought or born digital, they are not completely digital, right? It hits like you're still dealing with processes with human beings and paperwork.
And the digital, this digital organizations, this is a great comment you just made there. And because I think that for a lot of organizations that are not born digital, they, they, they have this assumption that, you know, you're all digital in all aspects of your work and that that's, that's not necessarily true.
Yeah, you know, Processes are processes whenever. You know, there's an output. You know, there's an input and in between the two, it's a process. Right. Those processes. While some may be automated using AI, ML, we do have those human touch points in, Especially as it relates to quality, auditing, developing those feedback loops, et cetera. So, you know, it's definitely something that hasn't manual component to it. Much more manual then, you know, you might anticipate.
Yeah, and by the way, this is a good segue for another theme that has emerged in the questions, which is about how do you effectively collaborate.
If I, if I could recall, I think you are in saint Louis, Missouri, I mean the organization is dispersed geographically and and so, you have people working for all different places at Twitter and they're collaborating.
You're gonna be doing a Kaizen and some people are like, how do you do a Kaizen, you know, when you're not there in the room of the people and so, talk a little bit about just, about on your digital transformation journey, how, how, well, how do you keep the collaboration healthy, active, productive? And then maybe a little bit about, you know, any techniques or tools are being used that we can learn from, on, on collaborating in this digital world.
Yeah, certainly. So, it was actually a question that I asked myself when I prepared for the first cars on Twitter.
And, and because we're in this digital space and remote space, it's OK.
I know I wouldn't want to sit in front of a computer for eight hours, and across functional kind of discussion, because you, just, even in person, those are intensive, right. And when you talk about virtually, it's even, it's exponentially more intensive, because you're dealing with the challenges that come with working, remote, and virtually. So, from that standpoint, what can we do to shrink the time down on a on a daily basis? Instead of a full day, maybe we do happening. So let's, let's start there. Let's try that, right.
What are the different platforms? Because I don't have a whiteboard.
What are the different tools, such as Lucid Chart, elicit Spark, where we can collaborate on a process map together to really drive out the cross functional understanding.
What's another point?
And, again, really, this communication, I talked about the pre work and the post work of the Kaizen event. It's a lot of buy in these conversations for this particular event. Started back in early June. Alright, man, here where you aren't, August. So there's a lot of stakeholder communication by in understanding the problems, so that when we get to the conversation, it's much more targeted. It's much more straight to the point. So we're not, because we're dealing with a shorter time period, we can kind of remove some of the fluff that, what would have happened in person, right. So that's, what some of the tips, and tricks, and methods, that adjustments, we've used as relates to going digitally versus in person. The tag tree, in terms of different time zones.
You know, that's something that, somebody's gonna when somebody's gonna lose, just because there's no perfect time when you're dealing with somewhat Basin and San Francisco, New York, China, India, so there's all these separate times as we have to balance. And unfortunately, it's just, you know, you can pick the best to work for the larger group.
Absolutely, and I assume that you're using the same technologists for collaborations that everybody else is using, Right? Zoom and goto Webinar and MS Teams, or whatever it is. Is there anything different in terms of that approach, or you're using, what everybody else is using internally here at where we use Google Meets.
But that's, you know, ticket Pig, Zoom, Microsoft Teams, et cetera. It's going to be the same, you know, options are same features, just in terms of collaborating visually. You know, making sure you're on mute, if you do have a question. Use the raise hand function and really paying as a facilitator, you know, paying attention to that cube, right? It's easy in person to allow folks to dominate a conversation, but in, in, in a digital space where people can kind of hide off camera, it's, it's much more easier to, for people to kinda shy away from speaking to really drawing out that information. Because, I haven't heard from you. What's your point of, what's your take on this important process, or what's a pain point that you have specifically, Right? Really, drive that engagement, Which is, which is going to be huge, as it relates to getting as much insight, as much detail as possible.
You know, it's awesome to hear that from you. And in an organization that's, again, Jane Doe, and successful in what they do, in the, in the way that they collaborate. Because, what you're talking about, as I see the comments as you were speaking, people are posting certain comments and the and about collaborations and what I hear talking about is about the importance of fundamentals of collaborations. And it's, and it's awesome.
Because you have the background that, that, how much the fundamentals matter. And when it comes to collaborations to fund them, when you, when you go digital, it seems like those fundamentals matter even more. I always tell people, you have to know the fundamentals of collaborations matter even more. Now, there, you're going digital, the fundamentals of even presentation and I've talked to people about energy when you're presenting as well.
When you're presenting in person there is there's an advantage of being there in person. There is a certain level and body language that takes place. So, when you're presenting digitally, you almost have to overdo it a little bit to get the same result and I think with collaboration, you also have to overdo it.
But you have to overdo the right fundamentals and the things that you're talking about are just good fundamentals for collaborations and I'm gonna summarize. And I wanna get a confirmation.
From you hear that, that is it You know, it's basically the fundamentals and you have to emphasize them even further as we as we collaborate digitally.
Absolutely. And the fun of fundamentals is a word I'd use consistently over the past several months ago. I joined Twitter back in, November of last year, user first, several months, to understand what's going on. Spam and API, that's digital space. I come from a supply chain, transformation, background operations background. So, you know, new space learning, ramping up. What are the opportunities, Et cetera. Right? From that, you see the, the, the opportunities for just getting to the fundamentals, right, not only fundamentals from a communication standpoint and reporting standpoint, but presenting, but also more process. Right, and next, take it back to process binding of the process piece. But the fundamentals of process excellence, operational excellence. You know, that's something that, again, I am use fundamentals word several times over the past month, and you really struck a chord with me there. But you know, it's actually nail head fundamentalist communication.
Vitamin is a process, that's what really drives digital transformation, where they're working through digital, working through digital means, or transforming digital processes.
Yeah! Well, sad, well said. This is a good reminder for all of us on the fundamentals matter.
Now, on that, and then, maybe, a very specific tactical question here, and William Fuller is bit, is asking this.
You mentioned the lack of a white board have additional alternative that you recommend for a whiteboard.
Now, it's interesting before it, before I started getting all these comments, all commercials, that there was all this whiteboard applications, People, I know. But, it's like, there's not a very good integration of a whiteboard application that I've seen that, let me put it this way to make a Kaizen activity or you know, seamless, it's, it's still a little bit clunky and that, so, we know that there are whiteboard applications there.
What I'm getting to here, and I'm sure what we then fully is getting to hear that there's something that's integrated, not be a little better way that's more seamless, because right now, it feels a little clunky, most of these whiteboard applications.
Yeah, that one that I gravitate towards exclusive Spark and Lucid chart, just based on how we can have, what we call the Infinite Canvas. And so, I can just kinda go and scroll, and write and draw, etcetera, in real time. But I completely agree. It is clunky.
You know, there's nothing that I've seen can replace being in the room, having the whiteboard, you know, being able to quickly move over to walk over to the back, or the parking lot from our notes, quickly jump back over to the process, and they get into the root causes, of X, is something that, again, as we move to the digital collaboration piece, it's an unfortunate casualty in terms of working digitally and collaborating digitally.
Which is unfortunate, because, you know, again, when we talk about Kaizen event, talking about the intensity of a time and resources, you know, those moments matter, getting two to where you wanna go quickly matters. So loose a Spark, Lucid chart, those are two that I would suggest checking out, because they're complimentary ones, process mapping tool. one is kind of design thinking, whiteboard tool.
Very good. Well, one other question, shifting gears to the strategic and maybe a little bit of tactical here as well.
That, on your digital transformation journey, I mean, forget about the whole company, just the area that you're looking at. You know, you're looking for our platform, safety, and health, and you'll look at your area.
How, how do you optimize, Not optimize? I'll do prioritize what you're going to work on And that there's so many opportunities, so many different things you can go after. And I'm following up on the question here from someone else who mentioned. There's a number of people mention this, you know, how do you understand the difference between kind of this global optimization and local optimization, then can have been adopt an enterprise view versus a department or business unit focus? I mean, there's so much to take into account how do you go about prioritizing the strategic, and perhaps the tactical That creates a lot of value.
Give us some thinking on, on the on, how do you go from the trivial, many to the critical feel on the things that you're going to work on?
Yeah, so getting back to one of the slides, it's, what is the kind of top-down priority, right? What does the organizational strategy and priorities right start?
There are, first and foremost, because whatever work be sure we're doing should tie to those initiatives, and those calls right?
From there, you know, it's, it's asking the questions based off of what this process mining or other methods, in terms of what, What are we tracking? Where, what our metrics are performing against those metrics? What are the processes that drive those metrics? Are we measuring what we should be measuring? What are we measuring that we should be measuring? And are we working on? But, again, working on the right metrics, right?
That those conversations have really been what I used to drive the strategic plan that I've developed for my specific department over the next short-term or immediate term, over the next four months, to close out 2021.
The one-year plan for 2022, and then building the roadmap, or a three year plan, jumping up to 20 24. So, those are the types of, again, you know, what is it that the business is prioritizing, right? How does our work relate to driving, or enabling, or building on those priorities?
What are our metrics?
How are we performing gets those metrics? Or these are the metrics that we should be monitoring. What are we missing that we should be performing against?
And then how do we use that to, again, build that that roadmap, From that standpoint, again, you know, what are the insights needed to answer those questions?
Process mining, guys on five, why, and views, shattered, et cetera. All the different metrics. Right?
Excellent. Andrea, what a pleasure to have you with us.
We cover everything from process mining to Y boards and everything in between this object to the tactical. And that's what makes it so enjoyable to have cross industry leaders we've experienced in multiple organizations, and, and now sharing this journey of digital transformation at Twitter with our global audience. Thank you so much, for taking the time to share your expertise, On behalf of our global audience, I can say that we're very grateful for your insights and your time today.
Perfect. Well, I appreciate the opportunity. I always enjoy these conversations, like that, as a development opportunity myself, I found great value. And the other presentations, even familiar with process mining, not familiar with operational excellence, you know, there's always information that you can learn from other experiences. So, again, you hit the nail ahead in terms of diversity, and at that cross functional aspect of the global experience. So, I really do appreciate the opportunity.
Thank you, Andrea, very much, thank you. It was a real pleasure to have you with us. Ladies and gentlemen, that was Andrew. Andrew Kirk land with us. He is a senior program manager at Twitter, under a platform health operations. Wonderful to have him here with us. Now, we are going to be taking a break, and we're gonna be moving to our next session at the top of the hour. And then when we, and we're going to be welcoming a artificial intelligence leader directly from the City of or of Toronto in Canada, and that is belong. Belong is going to be with us. Bill is a, it works as a leader at Dell. And he has a global perspective of Dell, applications, and strategies related to artificial intelligence and data analytics. It's always a treat. He brings tremendous market research to share with us.
He brings tremendous insights and practical experiences.
Bill knows the difference between hype. In reality, for digital technologist, get ready to be impressed by someone who has real depth in each one of these areas of technology that we're gonna be covering next. So if you enjoyed technology, and if you enjoy markets and the evolution of technological markets, you do not want to miss belongs presentation. And he's gonna be talking about data science driven, digital transformation. So, for all the data scientists out there, this is your next slot. I'll see you back at the top of the hour. Thank you.
Sr. Program Manager - Platform Health Operations,
Andrae Kirkland is an ASQ Certified Lean Six Sigma Black Belt who has led transformative initiatives for NASA, Nike, and Anheuser-Busch InBev. In his current role as a Sr. Program Manager at Twitter, Andrae pairs his continuous improvement expertise with next-level technologies to develop innovative solutions to combat some of the most pressing challenges that exist today - content integrity and data protection.
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