Courtesy of Enhance International Group's Jim De Vries, below is a transcript of his speaking session on 'Building a Resilient Digital Ecosystem' to Build a Thriving Enterprise that took place at IT Infrastructure & Cloud Strategies Live.
Building a Resilient Digital Ecosystem
Jim has served as a resilient enterprise executive leader, an advisor for companies, from startups to Fortune 50. Jim, please turn your camera on so the audience can see you and join us onstage. Derek, go there is Jim, Jim, where you're coming from today.
I'm coming from the great town of Bethlehem, Pennsylvania, and the great state of Pennsylvania in the United States. Outstanding, Jim. Hello there from San Antonio, Texas. We have nearly 2000 participants from all over the world. Jim, very excited to be here with you. Quick, quick note to our global participants regarding Jim, he oversees the global identification prioritization execution of high value business improvements in innovations for companies, business partners, and customers in multiple markets.
He has held operational excellence, sales, and supply chain and sales and leadership positions in leading global companies, in the chemicals, industry, with air products and chemicals in the energy industry, with General Electric Energy insecurity with Tyco, ADT, and the supply chain with C H Robinson.
He's asked throughout his career, he has develop and refine resilient enterprise ecosystems to accelerate innovation, leadership, development, strategy, execution, and value creation and global scale.
Jim believes that people make the difference and that is in harnessing people's talent that companies can become resilient.
So, Jim, thank you so much for taking the time to sharing your expertise of our global industry to the global audience today. Very much looking forward to your presentation.
Your job is a, it's great to be here.
I'm very honored to be here at this conference where we will talk about digital transformation, getting ready for change, Every transformation is a change. So we'll talk about discovering your digitalization journey.
Fostering a culture that accelerates technology adoption and then third we're gonna look at digital readiness and governance and infrastructure again.
The challenge we have is digital transformation does require change and without change there's no pain.
And and without pain we won't be able to build this resilient digital ecosystem that we've all wanted to build. So let's get started with discovering a digitalization journey.
Well, it's defined many, many, many different ways.
So, what is it? We talked about artificial intelligence.
We talked about machine learning, deep learning, oh, a host of acronyms, internet of Things, digital twins, blockchain, and smart contracts. And of course, we have Industry four. So planet was supply chain for employees.
It's getting hatty out there. So what are the top digital transformation areas that folks are focusing on?
Now, this comes from our friends at at at one second.
Comes from our friends here, that, uh.
Sorry, slide problems.
And what they found was that, from a customer experience and engagement perspective, that's where most of our strategies are.
They're coming from there. They're coming from, reducing operational inefficiencies.
And, they come from, from IT upgrades, So, those are the top three areas where we're having a lot of focus today.
Then, we're talking about, increasing speed, to market and existing products and services, then increase innovation, digital ethnography, trying to drive change in that way, from digital transformation perspective. Then we want to introduce some new business models.
And, and we see companies going out of what they're doing today.
And because it built this huge, digital ecosystem within their company, and they said, can we harness it and sell something different, then, of course, we have new products and services. So, digital transformation means something different to everybody, and that's the challenge. There's a lot out there.
There's everything from artificial intelligence, to robotics process automation, process monitoring, mining that we've talked about hyper automation, data driven Twins, so how do we make sense of all of these different things? Israeli law.
So, when we look at what's been going on.
A lot has.
Well, this is a little bit, remained. The same is for the transactional area is where we've seen a lot of digitization, bottom and bisector.
So the professional services, the media, finance, and insurance, wholesale, wholesale trade, these are the areas where there's been quite a bit of work in the asset's usage and labor digital transformation.
The oil and gas industry has picked it up the utilities where there's high risk, high reward, the chemicals and pharmaceuticals up in Detroit participating quite a lot.
Now what's changed is with covert in 19 healthcare was was lagging but of course we're Coburn 19 healthcare and even education.
Because October 19 those 2 sectors have bumped up in the last year of course and now we're seeing a snowball effect of all the different digitization efforts.
So, as we look at digitization, we break it down into three major pillars. The first pillar is data infrastructure. Where's the data? How is it coming through? What does it look like?
Do we believe our data?
And what we see is moving from bottom to top, we have disparate data to really building that data ecosystem that we're all trying to build.
So, we moved from data mining, up through process mining, and up to an enterprise network.
The second pillar is visibility, and we're, we've had SQL reports and BI reporting capabilities, Really, for the last 20 to 40 years.
What's the new technology is around digital twins, and driving that into real-time data, predictive and prescriptive.
Statistics and analytics to drive that value chain collaboration network. So you have an enable informed decision making.
The third pillar is focused on artificial intelligence, where you start from a target, or artificial intelligence, like an expert system, at one particular area in your company. All the way through an AI ecosystem.
And in, in the beginning, we had high code programming, that we're moving to low code, and no code programming, so anybody can program in the language.
And we're looking at natural programming language. We're looking at deep learning, computer vision, and, of course, that auto machine learning.
So the purpose of this is to say, without data, we can't move from left to right. Everything relies on data. Without visibility, we can't move from left to right.
So we need to move. We need to mature in all these areas. And what we'll learn is, enterprise information. Management is a slowly thing out here that is often overlooked, that we need to be looked at.
Because, without good, clean data, the Struts are trustworthy were not able to make informed decisions and drive the digital ecosystem.
So, with that, we're going to talk about culture a little bit.
So, at the boardroom, we're all sitting around the room, and we're saying, We need to digitize. We won't be able to keep up with the competition, or legal saying, We don't have the governance to build this digital.
How are we going to make sure that we protect ourselves?
Our salespeople are saying we are getting less and less time in front of our customers, and, and Finance is saying we have, you know, 100 bots built into the system and we'll be using bots in 20 20, 20, 21, and we'll be driving.
Automation throughout our core processes. And that's where we're, most digitization starts, is finance driven.
So everybody has a different viewpoint on digitalization and just what it looks like. But at the end of the day, it comes down to the employee and what they're looking for.
So, this comes back to say, What does our company stands for?
Do we have a core list of beliefs, passion, urgency? What do we stand for? And how does digitalization fit into our overall company goals?
So, we all know that culture eats strategy for breakfast. That's pretty well-known phrase, and, and customers will never level company until the employees love at first. So, when we're doing digital transformation, we have to keep going.
Keep in mind, the day in the life of the employee, are we making it better for them?
Are we empowering them to make better and more informed decisions from the CEO, to the general manager level, all the way down to the front lines?
So we want to be able to characterize the heart of the company and understand our cultural cultural understanding, so that we can make informed decisions.
So when we're inserting digitization and digital transformation, it makes sense to our stakeholders.
The stakeholders aren't bought in.
No matter how cool the technology is, it's not going to work.
We know that, for many, many years, for the last 30 years, every change is tough when we all encounter change.
If we're going to go through denial, anxiety, fear, anger, stress, it doesn't matter who you are, but the goal is to come out stronger than when you began.
So, how do we drive that digital transformation, and link it to the heart of the company, or what it stands for, then, drive that, where we need to drive it through a lot of communication, and through different change processes, which we'll cover in a few minutes.
So, we all know that nobody likes change, when it's something that's done to us.
But, change is that what we think of or embrace On our own, is different.
So, we have to create an environment such that change is part of our company, and we respect our employees perspective of what the new world is going to look like with digital transformation, that is not a threat.
And where do we start? Well, we should start with, we go back to quarter and we look at our value chains throughout the company.
We have our infrastructure at the top here on the left.
And then we have our pillars of our company, Inbound logistics, outbound, operations, marketing, sales, services. So we have our, we have our segmentation of our business.
And the goal is, is to have a clear understanding of all of our value chains. So if you're looking for, where are you?
Where do you focus on in digital transformation?
You really have to have your end to end enterprise map. Now, there are four walls, all the waste from your supplier to your customer.
So if you're a heavy industry company, and you look at what makes you tick in all those different departments, you may say production, manufacturing is where you focus on.
So in that case, that might be where you want to focus from a digital transformation perspective.
Where are, where?
What is your, what does your network look like and which department it takes, dictates your overall heart heartbeat. That's driving the culture of your organization.
So that could be, again, R&D, sales manufacturing.
If you're in a high-tech, pharma kind of industry, it may be new product development, so are we focusing on driving digitization in those areas that are vital to who we are?
Our brand, that's where we should certainly be looking at.
The safe bet is to work in areas where the customer doesn't see.
We may want to practice there.
But the real value to your company, to increase the value of your company, there's going to be where the customer and your clients, in the stockholders believe that you that makes you you.
So if you're making cell phones, it's in your R&D or working a new cell phone every 18 months, or 12 months or six months, whatever it is.
But you need to figure that out.
Then, marry your digitalization strategy to that.
And there's many different change models. Of course, I came from GE.
I like to change model from tissue, which is, no, of course, you lead by the top.
At the top, you managed to change. You create a shared need for the organization, shaped our vision, you mobilize, then you sustain that change and control results. So you come out stronger than where you started.
Of course, today there's Proceed Add Car, which is another fantastic change model that's very, very popular today.
I'm not advocating one or another, I'm just saying and suggesting that you make sure you are marrying this with your digital transformation journey, whatever. that change languages. You're, you're driving that throughout your organization.
So, when you tell people what they need to do, but let them figure it out, how, how it is going to be done? Or how to do their jobs, you get a much better client. Bottom line from these coaches.
The people who are doing the work need to be involved in the solution even if you know what the solution is.
They have to be part and parcel of that.
And there's different types of cultures.
There's no right or wrong. Understand what your culture is, or your team first culture, or your elite culture.
Are you a horizontal culture, or a free spirit culture? Are you more of a traditional corporate culture?
These are the guideposts the guidelines, in which that will drive your company and how you're going to manage that change.
So this brings us to the last section: Digital Readiness, Governance, and Infrastructure.
And in this, I like to look at things from a people, process, data, technology perspective, were discussed about getting everybody pulling in the right direction, in the same direction.
Getting that people and culture align. Understanding our processes, Mapping our processes. Understanding our end to end processes, which discuss that.
Then it comes to data. Do we believe our data is data treated as a as an asset?
Then we get to technology.
If we launch technology without understanding people and process and data, the likelihood of that technology sticky is very, very well.
So we have to be very careful that we try to orchestrate in this manner. People, process, data technology. Of course, you can launch technology and data activities without worrying about the people or process, but the likelihood that it's going to stick is very, very, very low.
So, let's talk about digitization. What is digital transformation digitization?
What are they saying?
So, when we talk about Big Data, which is one of those terms, it's out there. It's digitization. We're trying to get ones and zeros. We've talked about digital transformation, where we have a war room, and we can see the world and everything. That's more of a digital transformation.
We're seeing end to end supply change.
When you talk about ERP, and upgrading them, so that we can see more and more that we, than we could, before that's digitalization on these platforms.
So, again, we need to understand where these different technologies and activities fit in.
our overall digital transformation journey.
And again, it comes down to ones and zeros.
We need to find our data sources.
So we, at the beginning, we've talked about social media, the e-commerce being the primary area of digital transformation, and that's because all that data is readily available.
We're mining from known sources.
As we move forward, we need to create new sources of data, new ones and zeros.
And that's bringing in not only machine learning of our AARP's, but bringing in Internet of Things and new data sources.
Then, bringing in images, video, that we've had, access to what we've never used, and looking at, how do people act in the workplace.
A very hot area today, in digital transformation is video capture, an ethnography for safety, for customers. Understanding customers, values.
In ordering patterns, in pattern recognition, all, these are the new, the things that are coming out that are being used in different environments than what had been before.
So, all three of these techniques, mining the data, harvesting that data, and driving, web scraping, uh, data and video is what's really happening today, and as that data is continuously changing, you hit this high rate of change and, and we're really trying to understand if we can make more informed decisions between what we predicted and what we actually perform.
We close that gap, build the systems, so that there's better understanding for each and every person in the company of what they need to do and why they need to do.
That's going to be the breakthrough.
So, we need to build a system of continuous data mining. So, data needs to be an asset. So, when you look at your data systems today, and you make business decisions, how do you make decisions?
Is it more on experience or using some data, some descriptive statistics, or you're using inferential statistics or predictive statistics?
So, again, this is a graph of analytics maturity on the X axis. On the Y axis is competitive advantage. What we're looking at here is, how are we using data?
This first area as standard artist reports, basically, since the 19 eighties, we've been using standardized reports that were run batched once a day.
If you standardize our support but not put them on a business intelligence platform, you're still in descriptive analytics.
You're running a company in arrears. And when you ask the cut the executives, how are you making decisions? You're making decisions on data that's in the past.
What we really want to do is move to a horizontally integrated platform of now predictive analytics, and the only way to get to that is that Digital Twin that we talked about, so that we can move to what will happen and what would be the best that could happen.
So, again, we're going to go back into Enterprise Information Management.
The the risk management area is top area. Do we trust our data, we have cyber attacks all the time. Do we have value in the data that we're collecting?
Those data, again, is from ..., ..., are mostly are the minimum amount of data collected to get the job done. It's not to give the complexion the nuances of the data to make necessarily real-time decisions.
So those, those ERP systems either have to be updated, or maybe you put software on a service platform on top of it to supplement that data.
So that's where you're seeing quite a number of SaaS providers provide that capability, in Order: A process mining robotics, process automation, intelligent, process, automation, and now hyper automation, those of the hot topics, that's making that value of that data real.
So we're moving from ad hoc reporting, all the way through statistical methods, or casting, so that we can get to predictive modeling.
And the only way we can achieve that, is with real-time data, and you start with a data mart, and then you build this real-time, data driven digital twin.
So Davenport had it right in the two thousands.
This is the cornerstone of everything when it comes to data digitalization. If you don't have this, you're not gonna be successful if you don't have that infrastructure in your company.
It's painful, it's foundational, but it's required, you will not see exemplars that the 7% of the exemplars out there that are working well, with using data all have this infrastructure well, built in to the organization.
So, of course, Huzzah Premier, IBM is certainly one of those premier companies where they've taken data from social media and turn it in text analytics, and then made it visible and then they're moving again from descriptive, predictive, uh, in cognitive. They're making decisions.
So, that journey is, how long does that journey take? That journey can take 8, 12 years to move from descriptive.
All the way to cognitive, it's a, depending on how big your company is, how complex your organization is.
Another company that's been very good at Justice Flextronics, one of the largest electronics companies in the world, They've been doing this for at least 20 years.
Another company, a Cisco, are all been using data as an asset to use it in supply chain risk and resiliency to make more informed decisions across our enterprise.
So, how do you get started? Well, we started with Lean six Sigma.
We talked about digitization, and in gaining that day-to-day visibility. And then we get into intelligent process automation, and RPA, and advanced analytics in the digital Digital Twins.
Or you could just outsource, and give up, and have somebody else do it for you, But the thing that's missing in this, from our friends at McKinsey is, again, the data.
The data provides the transactional clarity of all this, all of these decisions. So we need data cleansing, data mining, process finding. Again, if you talk to any AI scientists, you ask them, what do you spend the majority of your time on? It's this bubble right here. Data cleansing data mining, and why is that is, because there's no enterprise information management.
So, if there's something I want you to get out of this talk, is IM.
Let's get that right across the organization. Figure out how to fit it in your digital transformation journey.
And of course, there's governance. We cannot forget about governance.
That is a key staple for any digital eco building any resilient digital ecosystem. I've outlined just at a very high level.
You need, of course, your executive sponsor, and you need to build your advisory council to get it started, and then a Task Force. And then, you need to start assigning digital data stewards throughout your organization Who owns the data on which this decision is going to be made? Then, who are the end users? How are they going to be using this data?
That's the key.
To building a resilient digital ecosystem is building this. This will mature over time. It will become part of your organization.
So, let's look at the digital deployments journey and a summary here. So, again, we need to have business alignment.
What's your business? What's the brand of your company with the culture, a company?
How do you, how does this fit into your overall culture?
Number two, you need people.
You need the people alignment to what you're doing.
Does the culture does your culture fit the digitization? Are people threatened by digitalization?
Or they feel like this is going to help them in their jobs and they feel where they're going to gain value in this.
Then you need the IT alignment, you need the processes, the information, the technology, the cloud structures that there's frameworks that we just learned about.
We need those in the background.
So, with that, I wanted to just go through one last, major slide, and that is the rigid, very resilient, digital ecosystem, demand driven maturity model, And as we move from whether you're service centric, cost centric, on the X axis, are your inside, out, or outside in, which is more of an empowering mindset.
So, if we move from left to right, know that we're just doing things as fast as we can, and it's a semi world, a subject matter expert world.
Startups often fall into this because they haven't build the infrastructure, then you get to stage two.
Then, at this stage, you start building under your Pillars of Power, under each business unit, and under each area.
So, in this case, one size fits all, but you're not scalable.
So what it was, I just mentioned in this last webinar, about being able to leverage things across the enterprise, that's hard to leverage because everybody has their little fiefdom to manage their shadow IT, to get the work done.
So, if you're in stage two, you're, you're, you're not there yet.
You need to move to stage three where you start saying what's the trade offs between supply demand product and what is this whole idea of what an integrated supply chain in getting these value chains across our enterprise.
So that we can start looking at what are all the scalable, different things that we can be doing, and recognizing that value does equal profit.
So our costs are optimized and scalable, recognizing this value equals profit.
So in stage 4 and 5, we're building to this scalable margin to serve model.
So this is our overall goal. So the question is, where are you? If you're early in stage one, you're going to be focused on much different things, then you're going to be on stage three.
As far as, when we look at all the different technologies that are available to you.
If you put in a technology platform or a software as a service, and you're not ready for it, then that is probably going to go to the wayside and you're not going to get the return on investment. So, understanding where you are before it, before you go, is extremely important, just like it is in any other program.
So, again, we end up on this slide of the three colors of saying: Where are you today?
If you were to score yourself a 1 to 5, each of these areas, where would you be?
Are you doing process mining? Are you doing predictive analytics? Are you doing some deep learning? Is it being done?
It focused area. Is it going within a business unit, or you're going across your enterprise?
So, as you build your resilient digital ecosystem, understand how everything fits in.
With that, that closes out the slides and open for questions at this time.
Josey, very well, Jim, very well, Excellent. So I'm going to ask you to stop sharing your screen so that I can come back in.
Sorry about my technical problems at the beginning of the presentation.
I couldn't see the screen. No, no, no problem. You had a little bit of a delay when you're first presenting something, related maybe to the bandwidth where you're broadcasting from, and that, but as you went on it, kinda caught up to speed caught up, and then everything, you know. Transmitted well. So, well, done, Great, great review. I mean, you really kind of guided us through a, through a journey that's very comprehensive. There is a lot in there. In terms of the different kinds of building a resilient enterprise, I mean, it clearly is not an easy thing to do. Otherwise, everybody would have a resilient enterprise, your finger.
There's only 7% of all the companies in the world actually have achieved this, you know, the Cisco's the, you know, some say Amazon, but some people don't say Amazon. There's a little controversy on that one. But there are some company like Zahra.
There are a company and IBM, they have really built out this Brazilian digital ecosystem. Apple is probably very close, I would imagine.
But the ones that we benchmarked, you know, in the last five years, what we find is it, it's a journey. It takes 20, no, 10 plus years to do it.
But it starts with respect of data and data as an asset. And if you don't respect data, and you don't respect people, we talk about people and what what makes up the people in the culture. You really can't get off, that you can't get forward, you can't move forward.
It very much so Jim Anda, and let's face it, we know and this audience knows very well that technology that enables our processes and our people to be to deliver greater value to customers and society. Those are the right technologies, but we also have lots of technologies that can make stupid happen at the speed of light. And the, and, And as we talk with Enterprise Architect, San Jose, talk to, to, really, the people who are honestly speaking. About how they're dealing with technologies in their organizations.
So they, most of them feel overwhelmed and they feel like everybody's trying to put in their little piece of technology and from into the organization. And the and I choose sometimes leads it, but doesn't have the, the leadership capabilities to do the job enterprise wide, because there are sometimes just connected to the actual business outcomes, The business side doesn't know what they don't know.
So the question off How: to get how to press the reset button and do this well, what would be your advice? What would be your suggestion for organizations will feel like they're overwhelmed they're under kind of like this chaotic system, where it's so many things are happening parallel and they don't think they have a good handle on what's going on. What does your suggestion? Where's the reset button how do you get them to start in the right foot?
I Think first we have to ask ourselves who we are as a company what do we stand for and what aren't we going to do as a company?
Don't take digitization out of it.
What do we stand for?
And in then, if we clearly understand what we are and where we're going as a company, then bring in digital transformation.
But if you don't know where that is, you can't get started.
So once you've done that, then it's bringing that C suite together and having a heartfelt discussion as to where is our greatest opportunity for our weakest link in the organization and where digital technology can add value and and start collecting the data in the systems. If there's no data in the systems, start building the systems to collect the data to enhance the visibility without visibility.
I don't know how you can know what to work on.
If you don't have your processes mapped end to end, if you don't have digital feedback, very simple process mining tools.
and, and, and data.
Sensitivity tools using alter acts, your company is like that, are going in. Mining tools are going to start understanding what your date, what your data looks like across your enterprise.
What, what condition is that in? If it's important condition, start building that data centric team to start off with.
Then, kek, very targeted projects, procurement, finance, the EEZ areas, we're digitization.
There's tons and tons of class case studies on, and focus yourself in those areas First, and crawl walk, run, situation.
I answer the question.
Yes. You did You did Those are great, great tips on on how to reset the system, and start on the right and the right path. I liked the comparison that you made in your presentation between just digitization and digital transformation, you know, kind of contrast of digitization and digital transformation. I think there's tremendous confusion about those topics. People think that just because you're digitizing things, you're somehow digital, digitally transforming the business.
And I think we both understand that. That's not the case. And the most of our audience understands that as well. That, first of all, I don't know if there's anything is such a thing as a digital transformation is just a transformation that digitization as part of that, because there is no digital transformation without business transformation. And there is no business transformation without culture transformation. So. So, and you and you talked about this, and, but it's very hard for organizations to see it. And I think some of it has to do with IT professionals and leaders being kind of myopic on the fact that if, if I bring technologies, you know, things will get better. And what we've seen is a disaster. You know, numbers like 80, 90% of digital transformations failing to deliver on their desired outcomes.
And, quite often, there's not even a clear vision of what you want to transform into. It's just like, we just want to use this technology. And I'm not sure how, that, what, the vision is to what we want to become as part of the use of the technology.
So, the question is, how do you, how do you, how do you slow people down in a place where they think that, Oh, we need to implement this technology? And that technology and AI and NPL there is more hype than there is Actual reality. Sometimes, In terms Of business outcomes.
But, yeah, do you have to explore those technologies? How do you manage that friction off? Is the need for speed with technology implementation, but also the need for patients and the reflection when it comes to the transformation journey, and how does this technology fit into that journey?
Yeah, and this is the most perplexing question.
There is out there because, know, I hate to say, it depends on, of course, the ecosystem, what you're working on, how big the company is, and so forth.
But you really need to start by saying what's valuable.
And in, and if they're trying to implement something, I think their classic case is RPA.
RPA was really took off over the last 2 or 3 years. And then all of a sudden you heard RPA folks saying, oh, we need to do change with RPA.
So anytime you're looking for technology to solve a problem, without looking at the people, process data ahead of it, it's gonna fail.
It's not a question of if, it's just going to be when you're going to have some short term gains and goals, but the likelihood it's going to step is very low, and it's been shown time and time and time again. That's the case.
So what I do is, I try to share those stories with the client, and say, you know, let's, let's have the RPA that, let's say, we automate and we're able to increase productivity by 2 or 3 X.
Let's take that money, and then invest it in data.
And in putting, instead of those people focused on those tasks, let's have them clean up the data.
And so, more robotic systems that EIN, Eric.
What error term, people's acronym, and In.
That's there, sir, OK, The data masters, and those type of folks have have that, answer your question, your essay.
Jim, you're having a little bit of a bandwidth problem on, on, from the location of your broadcast, So what I suggest you do, is that turn off your show, that we can still get your audio clearly. So if you could talk to your camera off so that we don't, you're not broadcasting or video because I think you are having a bandwidth bandwidth choke right now going on from where you're broadcasting from. So, go ahead and turn off your video on the, on the on the interface so that your audio can transmit clearly.
OK, attempt to do that right now. The right on the goto Webinar interface below the microphone. There's a little icon there. Just click on that icon for the camera, that will turn the camera off.
You stop showing the presentation. The the icons for the video is just below the little red box with the Y arrow. There is a microphone icon to the left hand side, and there is a little camera icon. That's, That's the one Jim. Perfect, perfect, so keep it at that.
So can you say what you just said? Because, as you're speaking, or video, in, your audio, is blurring out?
I apologize. Yeah, so I would start at the beginning again with data.
So how do we fund with the RPA other activities?
So we will get some gains from RPA, let's say, or intelligent process automation. We get some gains of productivity. Take that time and money.
Just don't take a piggy bank, but use it in and put it into securing better data and cleaner data.
So you're self funding that infrastructure. So cell phone, your infrastructure, just don't take the money on the run.
That's that's the short answer to that question. Absolutely, No, I hear what you're saying. That thought then that needs for the right foundation with people, process, and data, as you mention and that and that cleanup, you did emphasize that during our presentation. That is true, at least from my personal experience, with over 100 organizations currently, that data scientists are spending most of their time cleaning up data because there's the illusion that if I have a lot of data, it's a good thing. Well, it's a good thing if it has the right level of quality. Most of the organizations don't have the right level of quality that data becomes useless or actually can, can lead you to some really bad conclusions.
So, it seems that you're experiencing the same thing on your side, when you're talking to the data scientists, when you're implementing technology, that they have data quality issue is, is, is a big issue that organizations are dealing with right now, right.
Yes, and it's, it has to start at the top.
So, if if the leadership wants to make data informed decisions, they're going to start insisting that if you're going to bring me a decision to be made, it requires data until you have the data.
Whatever you're looking to buy or upgrade, you're not going to get it until you have sufficient data built.
So I go back to my years in the 19 nineties, that's what Welts added in 19 97.
I will not make a decision on anything unless you have data.
And rejected all improvements, all upgrades, all system changes. It says, until you have collected the data to validate that, we're not going to make any decisions. So for two years, I don't think we need hardly any big decisions because we were focused on cleaning the data.
Then the other thing is most of the data we're collecting.
again, any RPS is not decision based data.
It's finance data, the minimum we need for accounting, not for day-to-day decisions.
So now we have to build additional systems, whether they're software as a service, or we expand our ERP ease.
Or we use Internet of Things.
or we use our TLS to track the flow of our traffic, of our goods, whatever it is, then we can start bringing those in.
But if you start bringing in TLS and all that stuff in now, and you don't have a handle on your ERP, and all the ERP data is garbage, now you're mirroring all this nice, clean data with garbage data, then you're wondering why you're not making good decisions.
Well, I think the answer is quite clear.
Excellent point and process mining, the ERP data is not going to be that helpful. I mean, me show you some waste, but it's, it's not gonna be as helpful as it could be, for sure, Jim. Terrific insights, really wanna appreciate you, taking the time. I know, how busy you are, and how many things we have going on. Multiple decades of experience implementing, successful change. And leading business transformations across several industries. So thank you for sharing that expertise with us today.
Thank you so much, and I apologize for my technical problems.
I guess living out here in the boondocks doesn't pay off. Thanks so much here, is that?
Thank you. Jimmy came through clearing the and great message. Great presentation, we appreciate that. So, ladies and gentlemen, that was Jim, the freeze, the, the, the, the Managing Leader in director for Enhanced International Group, sharing his expertise across multiple industries, on leading culture, business, and digital transformations. This is, as you can see from his presentation he got spray tactical on these things, because that's where, that's where the real challenges are on real implementation. So again, this is a conference. not from theoretical people to you. This is our conference from the leaders and practitioners. To leaders and practitioners. Who wants to know the good? The bad and the ugly, when it comes to digital transformation. So, we are going to take a break now, and we're gonna come back at the top of the hour with a leader from v.m-ware.
And v.m-ware has been a fantastic growth journey, accelerating the excellence innovation, and transformation across multiple organizations, and we're seeing themselves as well. And we're going to have their leader from Enterprise Engineering, Nicole Scheffler with us, Nicole, who's gonna talk about building an enclosed an inclusive culture for this transformations for this digital transformation that we're talking about.
So, check back with you at the top of the hour and v.m-ware. Thank you.
Jim De Vries,
Founder, Managing Director,
Enhance International Group.
Jim de Vries is a skilled thought leader with more than 30 years of experience helping clients achieve their desired outcomes through his ability to facilitate teams and drive improvement. His experience encompasses financial, commercial, CRM, services, IT, call centers, security, transportation, automotive, power systems, oil and gas, nuclear energy, research and development, government, and electronics industries.
September 07-09, 2021
October 12-14, 2021
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