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Japan: The Land of Rising Automation

 

And back to our emerging coverage of Asia/Pacific… where people tend to focus on China, India and Australia. However, the Japanese IT services market is larger than these three markets combined – and is growing. So, let’s have our Asia/Pacific research lead, Andrew Milroy, discuss some of the important – and unique – aspects of this lucrative market. 

Japan’s ageing and shrinking population creates real skills shortages and very high labor costs

Japan is currently the only major developed country that is experiencing a population decline. Unlike other developed economies, it is not offsetting population decline with immigration. In addition, Japan has the largest proportion of elderly citizens of any country in the world. In 2014, 33% of the population was over the age of 60 and this percentage is increasing.

Given its shrinking productive population, combined with its wealth, the cost of labor is high. Consequently, its companies are often the first to adopt new technologies, including artificial intelligence and robotics. Companies use these technologies to increase productivity in a market with severe skills shortages.

Japanese firms increasingly struggle to acquire necessary skills to optimize their technology investments which, in turn, raises the cost of these skills. This is leading to increases in spending with third party service providers that help to fill these skills gaps.

Keiretsu stifle innovation and decision-making

Japan has a unique business culture based around keiretsu. Keiretsu are a set of companies with interdependent business activities and ownership arrangements. Toyota is the largest keiretsu. It dominates its keiretsu and has several tiers of subcontractors, most of which only serve Toyota. The activities of contractors and subcontractors tend to be shaped by the dominant company within their ecosystems. This can inhibit innovation from smaller companies in a keiretsu and make it inflexible. Deals tend to be done at the top of the keiretsu. Japanese business remains hierarchical and labor mobility is low compared to other rich countries. Hence, there are typically fewer stakeholders involved in decision making.

The convergence of Information Technology and Operational Technology is driving major transformation

One of the key things to understand about the Japanese market is that operational technology is converging with information technology at an extremely fast rate. It has to, if Japanese industry is going to remain competitive. Its leading manufacturing and automotive firms are using cloud, machine learning, mobile, and Internet of Things (IoT) technologies to transform their operations.

Until recently, industrial firms used proprietary technology for very specific processes. They were often dependent on suppliers within their keiretsu, for components, management, and maintenance of these proprietary machines. Today, Japanese firms are integrating their machinery with information technology, often supplied by firms from outside their own keiretsu. For example, Hitachi and Mitsubishi are integrating third party mobile, cloud and AI technology into their industrial machinery as a way of lowering planned and unplanned outages, enhancing customer experience and lowering the total cost of ownership.

Similarly, Toyota, and other leading Japanese automotive firms, have been embedding IT into their vehicles, enabling more automation. Third party cloud, mobile, IoT and AI technology are all being integrated into Japanese motor vehicles.

The Japanese business environment poses huge challenges and opportunities for ambitious IT Services buyers and providers

What does this mean for the IT services environment? Industrial firms are looking for IT services firms that understand how information technology is converging with their operational technology. These firms must understand how their customers’ businesses operate, at a more granular level than ever before. The integration of the IoT, cloud, machine learning and mobility with operational technology is transforming industrial businesses and enabling firms in Japan to differentiate themselves. Large Japanese IT services firms, NEC, Fujitsu and particularly Hitachi are well placed in their domestic market. In addition to being leading IT services suppliers, they are also operational technology firms. This gives them a huge advantage in the Japanese market and makes it difficult, although not impossible, for foreign firms to compete with them locally. These firms continue to dominate the Japanese IT services market together with the NTT Group. To be successful, foreign IT services firms must be able to demonstrate an understanding of the convergence of operational technology and information technology in specific industries.

The financial services, retail, healthcare and government markets offer enormous opportunities. Japan’s financial services and retail sectors are mature, sophisticated and highly automated. There remains a lot of older, legacy technology, so there is an opportunity for IT services companies, both Japanese and foreign to create systems integration, maintenance and management opportunities in these sectors. Financial services firms and retail firms tend to look globally for ‘best of breed’ technology implementations. Foreign firms such as IBM and Accenture, are well placed to bring expertise created from projects outside Japan, to Japanese clients. This is more challenging in industrial sectors where Japanese firms consider themselves to be ahead of the curve. Nevertheless, in recent years, Japanese firms have shown more interest in what has been happening in Germany and its ‘Industrie 4.0’ initiatives.

The highly regulated Japanese healthcare sector offers some interesting opportunities. The world’s oldest population has focused on innovative new technologies to offer cost-effective care to the elderly. Huge investments in elder care robots have been made by the Japanese government and Japan leads the way with this technology, some of which is being used in Japan. The use of sensors and other devices that can allow remote care is also very advanced in Japan. Again, IT services firms are needed to implement and manage this technology.

The Bottom Line: Japan’s skills crisis is driving automation at a breakneck pace

If IT services firms are serious about growing in Asia, they need to develop a strategy for Japan. This is the biggest market. It is hard to say that you have an Asian presence if you are not visible in Japan.

Japan’s demographic characteristics, combined with its rigid keiretsu-based business culture are forcing companies to automate processes rapidly. Indeed, Japanese firms are blending information technology, often supplied from outside the relevant keiretsu, with operational technology, to drive out costs, engender innovation, and address skills shortages.

(Cross-posted @ Horses for Sources)

Why even the Beeb needs sourcing standards

When you’re one of the last vestiges of commercial-free television trying to compete in a media world gone mad on digital and traditional advertising, you need to be pretty savvy when it comes to managing the coffers when you’re still reliant on public TV license frees each year to maintain your program quality.  So who better to talk with than the Beeb’s Jim Hemmington, who sits on the corporation’s external expenditure on goods and services, which includes several key outsourcing relationships. We also invited Chris Halward of the Global Sourcing Association (which engages with HfS as its preferred research partner), who leads the GSA’s global standards accreditation program to the conversation…

Phil Fersht, Chief Analyst and CEO, HfS Research: Good morning gentelmen. Let’s get started with the introductions, shall we?

Jim Hemmington, Director of Procurement, BBC: Yes, of course, Phil. I’m Jim Hemmington, Director of Procurement at the BBC. I am responsible for external spending on goods and services. That’s about 1.4 billion pounds a year. It’s about 19% of the BBC ‘s licensing. I look after general procurement as well as outsourcing activity. And just for a bit of context, of the 1.4 billion pounds spent, about half of it is in regular goods and services with about 11,000 suppliers. The other half, or just under 700 million, is with 12 suppliers that are providing a range of outsource services for the BBC. That’s been a big area for outsourcing over the last ten years.

Phil: Thank you, Jim, for joining us. We also have Chris Halward, who’s at the newly rebranded Global Sourcing Association (formerly the National Outsourcing Association). Welcome, Chris…

Chris Halward, Global Standards Director, Global Sourcing Association: Thanks, Phil. I’m the Global Standards Director at the Global Sourcing Association. I’ve been with the GSA for about eight years, focusing particularly on training and development initiatives. This includes the development of various standards and the qualifications that we

Phil: So, let’s get started with the conversation, and I think maybe Chris, we can start with you. People often talk about outsourcing as something you learn on the job. So, why have standards in global sourcing today? What is the real benefit clients receive from them, in your experience?

Chris: I suppose the first thing to say is that outsourcing can be a complicated activity. There’s more than one party involved, which means there are a lot of different views going around as to how something can best be achieved. With that complexity comes challenges, because it’s often done on an international stage where you’ve got jurisdictions involved and so on. What you need is something which helps people work through that complexity in a structured, organized, and efficient way.

One more thought is that regulators around the world have been particularly interested in outsourcing for all sorts of reasons, not all of them good. They’re very keen to see standards being applied, being adopted as a way of developing people’s confidence in the system. I’m sure Jim has some further views on all of that.

Jim: I think that’s right, Chris. I am looking at it purely from a buying perspective, for the moment. I’ve been working on outsource deals since the mid- to late-80s. And still, at the BBC, we have an occasional problem with an outsource arrangement. What you find is that it’s still the sort of problems you had years ago. Relationships break down because expectations are different, or there are surprises on either side. That might have a commercial or quality impact, with misunderstanding about things like risk transfer and transparency.

Standards align expectations, take out surprises. Having standards allows you to have more transparent and meaningful conversations, and ensures that you’re both acting professionally and in a way that suits each party’s interest. So, if you can get that alignment, you should neutralize, really, all disputes, and you should see much more success in those relationships going forward.

 

Jim Hemmington, BBC Chris Halward, GSA

Phil: Okay, so Jim, when you look at your experience at the BBC, with the Global Sourcing Standard, what would you say has been achieved to date? What have been your successes? If you could start today again, would you do anything differently?

Jim: We do have a very mature outsourcing function. We started outsourcing back in ’96, and some of our agreements are now third generation. We’ve learned lots of lessons on the way. But back in 2015, we wanted to get an external view of whether we are good at this activity and where we can learn to be better. That coincided with the emergence of what was then known as the lifecycle, which turned into the standard.

What we found was that when we applied the standard and became accredited to it, we found there were gaps in what we thought were best practices. When we filled those gaps, we started to see some significant benefits coming through. I think one of the big areas where we found the most benefit was the lifecycle approach. Things like business planning going through procurement, the hand-off in procurement into transition, and transition into business as usual. We found we were a little bit clunky in some of those hand-offs. We’ve smoothed quite a few of those now. Our finance procurement that went live in November was the first time we kind of approached a major outsource with a plan and addressed gaps the GSA Standard pointed us towards. We started to see some financial benefits, and I’m confident that as we go to replenish our outsource portfolio, the savings are going to be significant. I reckon between four to seven percent of our spending on outsourcing. Because we’re just getting better at it, and we’ll engage more effectively with the market.

Phil: With a lot of the changes happening in the market, particularly innovations emerging, such as robotic process automation and the impact of digital.  How does the standard support disruptions as they evolve? How does it cater to some of these emerging technologies and disruptive business models?

Jim: Okay. Again, from my perspective, I think what the standard does is give you a stable and steady state platform from which you can then explore disruptive technologies. Particularly in areas of transformation, it enables you to take more risk because you can assess things like the impact of disruptive technologies.

Chris: Just to amplify that, Phil, I think one of the things the GSA Standard does is to have a very clear focus on what we describe as Strategic Leadership. It’s about ensuring that the underpinning strategy is as rigorous as it is robust. So, what I have seen in the past is that outsourcing arrangements succeed or fail quite often based on how clear, how effective, and how well-thought-through the underpinning strategy was.

All too often, people tell me about arrangements that don’t work. They’re bemoaning the fact that they didn’t really think these things through. They didn’t look at the options. They didn’t look at whether a particular way of doing things is going to be right. What the Standard does is it really encourages people to focus on that aspect of their sourcing strategy. And to ensure that they continue to concentrate on that aspect throughout the lifecycle.

The other point that links into this is that the lifecycle approach enshrined in the Standard ensures a joined-up approach. That is what Jim was alluding to. You need to address the tendency of going into silos. You’re trying to link everything together so it all flows through and can remain aligned to the appropriate needs of the business. As we know, and HfS Research has talked about it a lot, when things are changing, you need to be really nimble. You need to be flexible, and that’s something that maybe too many organizations over the years have not been able to do. The Standard really encourages them to do exactly that: to be nimble.

Jim: Yes, I agree. Certainly in the BBC, we’ve been reluctant sometimes to adopt emerging and disruptive technologies because of the risks and uncertainty involved. Whereas, I think if you’ve got a standard and you are using that to track the journey and help you understand better how you can manage, you do start to adopt disruptive strategies more readily, and it gives you a competitive advantage.

Chris: I think that as well, Jim. You would probably agree that when you’ve established the Standard within the organization, people in the organization understand how outsourcing works and how it impacts the business. Then it’s much easier to explain to them. They don’t need to understand every single detail of the Standard, but they get a sense of, “What are the important things that we really need to focus on?”

Phil: So, gents, we’ve just completed our annual seminal study on operations outsourcing with the KPMG globally, covering 450 major enterprises. What we got from the study was clear intention to keep expanding the outsource model. There was a notable pullback (see blog) in intentions to invest in offshore resources and instead invest more aggressively in automation initiatives. It sounds a little bit counter-intuitive. How do you increase your outsourcing if you’re not going to increase offshoring? Is this something you believe is a long-term shift? Or do you think this is more about outsourcing leaders needing to be seen as moving beyond labor arbitrage as a prime resource of value? What’s your take on what’s going on here?

Jim: That’s an interesting one, Phil. I don’t think it’s a short-term thing. I think it’s more of a progressive thing. Because you’re right; I think the fact that we’ve offshored is being primarily driven by labor arbitrage. Because that created huge cost savings for us. But now we’re starting to explore automation, and other things are coming down the line.

A couple of years ago, we were having discussions around contract terms, because there were huge capital investments to be made, and the BBC didn’t have cash for capital investments. But so many services now are available, such as the cloud and other sorts of sharing mechanisms. The change continues to be progressive, and I think organizations will now look at all elements of outsourcing. It’s not just labor arbitrage. It’s how technology can be used to improve their outsourcing activity. That, we haven’t seen in the past.

Chris: Let me just come back with a couple of comments as well, guys. Because what I really believe is that globalization provides opportunity. If I’m a business leader of a large, global organization. I have a pool of skills, a pool of labor to draw from across the world. I think in the past, labor arbitrage has clearly been an important driver and has encouraged people to address the challenges of managing offshore arrangements. I also believe there are many reasons why you source from overseas, not just labour arbitrage. Having said that, we have things going on around automation which have given people pause for thought that there may well be other ways of doing things that will deliver the same or more value.

I think we do need to see the apparent paradox as a short-term reaction to the perceived opportunity and risk; that’s become particularly clear over the last couple of years. But I think we also have that long-term, globalization scenario. There will always be a strong case for organizations to collaborate across the whole globe. Wherever opportunities arise, using capabilities from across the globe will add value to their business.

Phil: Okay – so you can both have a stab at our final question! If we convene in three years’ time, do you think we’ll still be talking about outsourcing in the same way? How dramatically will all the changes we’re seeing in the political dynamics and the emergence of new solutions affect the conversation?

Jim: I think we’ll be having very different conversations. I think it goes back to this progressive point, Phil. Just a couple of years ago, we saw outsourcing was all about agreements, with the likes of Capital One and IBM and and all the big guys. Outsourcing now comes from all over the place. It’s coming from different organizations, coming up with different ideas. It’s coming from, as you say, the use of technology and automation.

The link world that we deal with now, where geographical location is not a boundary anymore, means there will be lots of things that we’ll be buying in the future, and my end user, it might be the audience. Or it might be someone in the BBC who has no idea where that service comes from and won’t really care if it’s adding value. I think the term outsourcing will become more and more of an issues sort of term. It’s more of sourcing really and about how organizations are buying the right activity to support their business. I think more organizations are trying to get into sourcing space. The more they can be agile the more innovative they can be.

They’re the sort of conversations that we’re going to have in the future. So, I think the big monolithic contracts and the kind of well-known names at the moment, kind of lead to that. There will be many, many more organizations providing these services. There will be a huge variety of service propositions that organizations can choose to go with, depending on what they want to achieve. So I think it will be a very different industry in the future.

Chris: I’d go along with that, Jim. I think there are going to lots more, probably smaller organizations that will be new sources in the ecosystem. There will be different services required, from client organisations that result from changes in their markets. The BBC is a great example of this given the massive changes that the BBC has had to address in recent times.

I think we’re going through that period where people are suggesting that maybe everybody will sit around and do nothing because robots will do everything. But the reality, I suspect, is that we just come up with more ideas, that we can’t think of at this moment, that take up people’s energies. What we will end up with are sourcing managers who are much more central to an organisation’s success. We’ll need to find different solutions and often, we will need to be finding suppliers of those solutions that are more agile, more flexible. It means that we’ve probably got to have shorter contracts, more flexible contracts.

I think it means that we’ve got to have better relationships between buyer and supplier. Because there’s got to be much more reliance on driving towards outcomes both organizations clearly understand and want to deliver together. That’s the critical thing, and I’m not sure that’s been the case in the past. I think the notion of having an outsourcing standard becomes even more important, because change is much more apparent and complex.

Jim: Yes, I agree. Tracking back to what makes the GSA Standard unique, I think for me, what was refreshing about it is that there are lots of patches and procedures that the BBC adopts to buy goods and services, and lots of organizations that we deal with have their own set parts, too. What the GSA standard does is provide them a very flexible framework on which you can hang your current processes and procedures and align them to very different processes and procedures your suppliers might be adopting.

That’s where you’ve got this sort of ease on the alignment, without having to go through the rigmarole of fundamentally changing the way you do things. What the standard does is provide a central core of activity that just aligns different things to achieve the same outcomes.

Chris: It’s fantastic to hear that. Because we’ve worked so hard over the last few years trying to ensure we have a robust and rigorous standard that covers all the critical areas that are good-quality buyers or providers. Because it’s appropriate for both sides.

Phil: I think it’s great that you could share that with us. I thank you both for your time, Chris and Jim, and I look forward to sharing this interview with our leaders. Have a great weekend.

(Cross-posted @ Horses for Sources)

Bush League Tactic #1: Hustle Harder

If you’ve spent any time at all looking for help starting or growing your small business, you will have come across the “Hustle Harder” crowd.  They’re going to tell you they or some other prominent success story got ahead by giving up absolutely everything, becoming a total workaholic, and grinding out 100+ hour work weeks.

Invariably these guys are Young Turks who seem like they’ve way too much caffeine, or more likely, too many energy drinks.

Too Much Hustle Comes From Fear, Ignorance, and Misplaced Enthusiasm

I’ve been there.  In my first startup I vividly remember working from 8am to 2am 7 days a week to try to force our first product out the door.  I was 23 years old and I had no earthly idea how to improve my changes other than by working as hard as I was physically able.

It was all coming from Fear, Ignorance, and Misplaced Enthusiasm.  I was a wild-eyed youngster with a big bag full of venture capital and an unrealistic deadline to meet.  Gosh we spent a lot of energy blunting our spears on things that didn’t matter and just generally not getting much done any sooner than an older wiser version of myself would be able to do years later, but without all the Sturm and Drang.

tired rubbing eyes

Too Much Hustle Leads to Burnout, Exhaustion, and Mistakes

Look, I get it–hustle is exciting, it creates energy you can feed off, and it’s actually pretty easy to drive yourself harder.  For a while.  Then it gets old.  You get burned out.

Dang, real burnout can be so debilitating, and you don’t even realize it.  But it’s a vicious cycle because you get addicted to the hustle.  Suddenly, you’re having these kinds of unhealthy thoughts:

  • You feel like just working harder can fix any problem in your life.
  • You feel stressed whenever you’re not working because you should be hustling harder.
  • You start neglecting other things besides work that are important in your life.  Things like your family, your health, or getting a decent night’s sleep.
  • You have no time for your friends, so your social life withers and you drift apart.
  • You’re juggling so many balls so fast that you start dropping a few.  Some of the balls dropped turn out to be quite important.  You’re making more mistakes than you used to.
  • You’re so much less efficient than you used to be.  Tasks that should’ve been simple suddenly drag on.  Are you being productive hustling or just milking the time to move the clock?

Now it doesn’t take a rocket scientist to see that those things are not going to improve your productivity or help you to be more successful.

Hustlers Start Over Again and Again

Remember that old story of Sisyphus from Greek Mythology, rolling that gigantic rock uphill over and over again.  That’s what it’s like to be a Hustler.  There’s no leverage, no automation, no ability to benefit much.  You just go back in and push harder.  You can achieve a lot of things through Hustling, but you never get ahead in the long term, only on the immediate task of the day.  And then you have to Hustle again tomorrow, and the next day, and the next.

I don’t know about you, but I want to get ahead in some leveragable way.  It’s okay to hustle for a little bit, but I don’t want to spend my life building a net worth that’s based solely on how many cubic hours I can put to the task.  It’d be nice if being smart, or investing in some learning or other asset would make a lasting difference in my future growth trajectory.

But so long as your main tool for improving your game is to up your hustle, it isn’t going to happen.

Hustling Harder Is a Bush League Tactic

I’m just going to say it: Hustling Harder is a Bush League Tactic.  A Pro will not count on More Hustle to win the day.  At best, a Pro will Hustle Harder on a very short-term basis to get something Really Important done so it can have an impact sooner or to avoid a massive negative impact.  If cranking up the Hustle becomes a way of life, you’re using it wrong.

To create consistent growth, you need a System, not continuous turn the volume up to 11 Hustle Harder tactics.

It Doesn’t Matter How Smart You Are, If The Other Guy Knows The Answer And You Have To Learn It, He Wins. A System Gives You the Answers So You Can Win Too.

A long time ago, I realized that it doesn’t matter how smart you are, if the other guy knows the answer and you have to learn it, he wins.  It’s the same with having a System.  If you pit Hustle against a proven System, the System is going to win every time.  You don’t have the time while Hustling to figure out all the nuances and advantages that are built into a polished System.

Having a System optimized for whatever task you need to accomplish is awesome, but hard to come by.  Only the most important tasks that a large number of people have to take on have such Systems available.

A pilot has a System for every possible emergency, and he has trained, possibly on a simulator, for each one.  That’s because the price of failure for pilots is very high.  Same for your doctor, especially if they’re performing major surgery to correct a life-threatening situation.

Where Small Business is concerned, there are many areas where you can find Systems to help with your biggest problems.  I put together a system for customer growth of my main business CNCCookbook that drove the site from zero to 4.5 million visitors a year as I write this.

You’ll be able to use the same System that I used for CNCCookbook and other companies before that if you choose to join my Customer Critical Mass course.

But what do you do if your task has no System tailored specifically for it?

Good News: There are Systems designed to make your work on any task more productive.  When you don’t have a special System to use (or often even if you do), use one of these Productivity Systems.

I use one I’ve developed over the years constantly.  It’s got a few moving parts, but it is the Foundational System of my day.  And I will give it to you absolutely free for joining my mailing list for Customer Critical Mass.  You see, I am putting it all together in an online course that will shortly be available called Work Smarter and Get Things Done.  It has served me extraordinarily well over the years.  In fact, it is the oldest system I use, as I literally developed it to help get out of the Hustle Trap my very first startup landed me.

If you’d like to have this Productivity System for yourself, just get on my mailing list for Customer Critical Mass and as soon as it is available, I’ll hook you up with it.

[ Yes, Get Me on the Customer Critical Mass Newsletter List ]

 

(Cross-posted @ Bob Warfield)

Podcast – Connected cars, goods, energy, healthcare and future IoT trends

I have been a longtime fan of Ken Briodagh’s IoT Time podcast, so when he reached out to ask me to come on his show, I suggested we jointly host a show.

He very graciously agreed, and we had a great conversation discussing connected goods, connected transportation, connected agriculture, food production, energy, trends in the Internet of Things, and had great fun doing so!

Ken has recently written a book on IoT Trends which is available in paper form on Amazon, and as a free download at http://www.iotevolutionworld.com/iot-ebook.aspx

You can find ken online on Twitter @KenBriodagh and @IoTEvolution ;

http://www.iotevolutionworld.com ;

IoT Time Podcast: Season 1 http://tmcnet.com/59297.1
Season 2 http://tmcnet.com/59298.1 ;;

IoT Evolution Expo: http://bit.do/IoTEvolutionExpo ;;

IoT Time book: http://www.iotevolutionworld.com/iot-ebook.aspx

 

(Cross-posted @ The IoT Heroes Show with Tom Raftery)

McKinsey: AI, jobs, and workforce automation

 

For business people, AI presents a variety of challenges. On a technology level, artificial intelligence and machine learning is complicated to develop and demands rich data sets to produce meaningful results. From a business perspective, many business leaders have difficulty figuring out where to apply AI and even how to start the machine intelligence journey.

Making matters worse, the constant drumbeat of AI hype from every technology vendor has created a continual barrage of noise confuses the market about the real possibilities of AI.

To cut through this noise, I have invited many world-leading practitioners to share their expertise as part of the CXOTALK series of conversations with innovators.

For episode 219 of CXOTALK, I spoke with Michael Chui, a Principal at the McKinsey Global Institute (MGI), and David Bray, an Eisenhower Fellow who is also CIO at the Federal Communications Commission.

The McKinsey Global Institute has released a variety of research reports on topics related to Ai, automation, and jobs. For example, see this article on the fundamentals of workplace automation.

As you can see in the graphic below, Chui and his team examined a variety of industries looking at the impact of automation, including AI, on the workforce.

CXOTALK McKinsey - automation and AI

Image from McKinsey Global Institute

Another fascinating graphic showing automation potential and wages for US jobs:

 

CXOTALK McKinsey - automation, AI, and wages

Image from McKinsey Global Institute

The conversation between Michael Chui and David Bray covered key points about the relationship of business and the workforce to automation and AI – including investment, planning, and even ethical considerations.

You can watch our entire conversation in the video embedded above. An edited partial transcript is available below and you can read the complete transcript at the CXOTALK site.

How should organizations think about investing in AI?

Michael Chiu: More organizations have started to understand the potential of data analytics. Executives are starting to understand that data and analytics are either becoming a basis of competition or a basis for offering the services and products that your customers, citizens, and stakeholders need.

While there are often real technology challenges, we often find the real barrier is the people stuff. How do you get from an interesting experiment to business-relevant insight? We could increase the conversion rate by X percentage if we used this next product to buy an algorithm and this data; we could reduce the maintenance costs, or increase the uptime of this whole good. We could, in fact, bring more people into this public service because we can find them better.

Getting from that insight to capture value at scale is where organizations are either stuck or falling. How do you bag that interesting insight, that thing that you capture, whether in it’s in the form of a machine learning algorithm, or other types of analytics, into the practices and processes of an organization, so it changes the way things operate at scale? To use a military metaphor: How do you steer that aircraft carrier? It’s as true for freight ships as it is for military ships. They are hard things to turn.

It’s the organizational challenge of understanding the mindsets, having the right talent in place, and then changing the practices at scale. That’s where we see a big difference between organizations who have just reached awareness and maybe done something interesting and ones who have radically changed their performance in a positive way through data, analytics, and AI.

What are the adoption problems around AI and machine learning?

David Bray: The real secret to success is changing what people do in an organization, that you can’t just roll out technology and say, “We’ve gone digital, but we didn’t change any of our business processes,” and expect to have any great outcomes. I have seen experiments that are isolated from the rest of public service; and they say, “Well look, we’re doing these experiments over here!” but they’re never translating to changing how you do the business of public service at scale.

Doing that requires not just technology, but understanding the narrative of how the current processes work, why they’re being done that way in an organization, and then what is the to-be state, and how are you going to be that leader that shepherds the change from the as-is to the to-be state? For public service, we probably lack conversations right now about how to deliver results differently and dramatically better to the public.

Artificial intelligence, in some respects, is just a continuation of predictive analytics, a continuation of big data, it is nothing new because technology always changes the art of the possible; this is just a new art of the possible.

I do think there’s an interesting thing in which it could offer a reflection of our biases through artificial intelligence. If we’re not careful, we’ll roll out artificial intelligence, populating it with data from humans, [and] we know humans have biases, and we’ll find out that the artificial intelligence itself, the machine learning itself, is biased. I think that’s a little bit more unique than just a predictive analytics bias or big data.

Which business areas most suited to AI?

Michael Chiu: When we surveyed about 600 different industry experts, every single one of those problems we identified, at least one expert suggested it was one of the top three problems that machine learning could help improve. And so, what that says is potential is just absolutely huge. There’s almost no problem where AI and machine learning potentially couldn’t change and improve performance.

A few things that come to mind: One is a lot of the most interesting and recent research has been in this field called “deep learning,” and that’s particularly suited for certain types of problems with pattern recognition, often images, etc. And so those problems that are like image recognition, pattern recognition, etc. are some of those that are quite amenable and interesting.

So again, regarding very specific types of problems, predictive maintenance is huge. The ability to keep something from breaking; rather than waiting until it breaks and then fixing it, the ability to predict when something’s going to break. Not only because it reduces the cost. More important, is the thing doesn’t go down. If you bring down a part of an assembly line, you bring down the entire factory or often the entire line.

To a certain extent, that is an example of pattern matching. Sensors are the signals that reflect that something’s going to break, informing you to do predictive maintenance. We find that across a huge number of specific industries that have these capital assets, whether it’s a generator, a building, an HDC system, or a vehicle, where if you’re able to predict ahead of time before something’s going to break, you should conduct some maintenance. That is one of the areas in which machine learning can be quite powerful.

Health care is another case of predictive maintenance but on the human capital asset. Then you can start to think, “Well gosh! I have the internet of things.” I have sensors on a patient’s body. Can I tell before they’re going to have a cardiac incident? Can I tell before someone’s going to have a diabetic incident? That they should take some actions which could be less expensive, and less invasive, than having it turn into an emergent case where they must go through a very expensive, painful, and urgent care type of situation?

Again, can you use machine learning make predictions? Those are some of the problems things that can potentially be solved better by using AI and machine learning.

David Bray: There are opportunities for artificial intelligence and machine learning to help the public. I think a lot is going to happen first in cities.

We’ve heard about smart cities. You can easily see better preventive maintenance on roads or power generation and then monitoring to avoid brownouts. I think the real practical, initial, early adoption of AI and machine learning is going to happen first at the city level. Then we’ve got to figure out how to best use it at the federal level.

CXOTALK brings together the most innovative leaders in the world for in-depth conversations about leadership and innovation. See the complete list of episodes.

(Cross-posted @ ZDNet | Beyond IT Failure)