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The Forgotten Mistake that Killed Japan’s Software Industry

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The Forgotten Mistake that Killed Japan’s Software Industry

Japanese softwarehas problems. By international standards, it’s just embarrassingly bad.

We all know this, but what’s interesting is that there are perfectly rational, if somewhat frustrating, reasons that things turned out this way. Today I’m going to lay it all that out for you in a way that will help you understand how we got here, and show you why I am optimistic about the future.

And no, this is not going to be just another rant about all the things I dislike about Japanese software.

I am not going to waste your time or mine cataloging and complaining about the many, many bad practices, user-hostile design decisions, mind-boggling complex workflows, and poor development process that afflict Japanese software.

If you want details and debate about exactly how Japanese software falls short, or if you are just in the mood for some good old-fashioned venting about being forced to use it, check out Reddit or maybe Hacker News. This topic comes up pretty often there.

No, for the sake of this podcast I’m going to assume that we are all in agreement that on average, Japanese software. is just … awful.

That way we can spend our time talking about something far more interesting. We are going to walk though the economic events and the political forces that made today’s poor quality of Japanese software almost inevitable,

And by the end, I think it will give you a completely new way of looking at the Japanese software industry.   

You see, the story of Japanese software is not really about software. No, this is the story of Japanese innovation itself. The story of the ongoing struggle between disruption and control. It’s a story that involves war, secret cartels, scrappy rebels, betrayal, rebirth, and perhaps redemption.

How This Mess Started

So let’s start at the beginning. The beginning is further back than you might expect.

To really understand how we got here, we need to go back, not just to the end of WWII, but to the years after the Meiji restoration, the late 1800s, back when the Japanese economy was dominated by the zaibatsu.

Now, “zaibatsu” is usually translated as “large corporate group” or “family controlled corporate group.” While that is accurate, it grossly understates the massive economic and political power these groups welded around the turn of the 20th century.   

Japan’s zaibatsu were not corporate conglomerates as we think of them today.

You see, although the Meiji government adopted a market-based economy and implemented a lot of capitalist reforms, it was the zaibatsu, with the full support of the government, that kept the economy running.

And the zaibatsu system was almost feudal in nature.

The national government could, and did, pass legislation regarding contract law, labor reforms, and property rights, but in practice these were more like suggestions. In reality, as long as the zaibatsu kept the factories running, the rail lines expanding, and the shipyards operating at capacity, the men in Tokyo didn’t trouble themselves too much with the details.

In practice, the zaibatsu families had almost complete dominion over the resources, land, and people under their control. They were the law.

At the turn of the previous century, there were four major zaibatsu (Sumitomo, Mitsui, Mitsubishi, and Yasuda). And each zaibatsu had its own bank, its own mining and chemical companies, its own heavy manufacturing company, etc. But it wasn’t just industry, each of these zaibatsu  groups had strong political and military alignments. For example, Mitsui had strong influence over the army, while Mitsubishi had a great deal of sway over the imperial navy.

At the start of WWII, the four zaibatsu families controlled over 50% of Japan’s economy. This fact, when combined with their political influence, quite understandably, made Japan’s military government very uncomfortable, and during the war, the military wrested away a bit of the zaibatsu’s power and nationalized some of their assets.

After Japan’s defeat, the American occupation forces considered the zaibatsu a serious economic and political risk to Japan becoming a liberal, democratic fully developed nation. They targeted 16 firms for complete dissolution and another 24 for major reorganizations.

Rising from Ashes

Now, that was supposed to be the end of the zaibatsu. I say “supposed to” because those of you who know Japanese history understand that it never really happened.

Of course, many things changed. Important political and social reforms were implemented, the legal system was greatly strengthened, a lot of zaibatsu assets were nationalized, and the zaibatsu themselves ceased to be.

At least, officially.

You see, the zaibatsu were quickly allowed to restructure in greatly weakened , but very familiar, forms, as keiretsu.  This was permitted for two main reasons.

First, as the cold war heated up in the 40s and 50s, America’s idealistic vision for a democratic and progressive Japan took a back seat to the more practical and pressing need to develop Japan into a bulwark against Communism. And that meant prioritizing economic growth over social reforms. With these new goals in mind, both the American occupation forces and the Japanese government, quite correctly, concluded that having something like the zaibatsu groups would lead to faster, more predictable growth than tearing everything down and rebuilding from scratch.

The second important, and kind of surprising, reason was that almost no one in Japan really wanted to see the zaibatsu broken up. Not the politicians, certainly not the leaders of the zaibatsu, not the public at large, and to the endless frustration and confusion of western labor organizers, not even the rank-and-file zaibatsu workers and employees. In fact, at one point 15,000 Matsushita union members signed a petition demanding that the Matsushita zaibatsu not be broken up.

So in the end, important changes were made. Labor rights and contract law were strengthened significantly, and even more zaibatsu assets were confiscated. The traditional family holding companies were dissolved, but they were replaced by cross-company shareholdings  and interlocking corporate boards that achieved much the same result, but in a much more transparent and manageable way.

And so, most of Japan’s zaibatsu were allowed to morph into the smaller, less threatening, and much more manageable keiretsu.

Japan as a Global Innovator

In the same way that the zaibatsu defined the economic miracle that was Japan’s Meiji-era expansion, the keiretsu would come to define the economic miracle that was Japan’s post war expansion.

Today there are six major and a couple dozen minor keiretsu groups, and during Japan’s economic expansion, as much as possible, they kept their business within the keiretsu family.

Projects were financed by the keiretsu bank, the materials and know-how were imported by the keiretsu trading company, and the final products would be assembled in the appropriate keiretsu brand’s factory. And supporting all of these flagship brands were, and still are, tens of thousands of very small, exclusive manufacturers that make up the keiretsu supply chain — and the bulk of the Japanese economy.

And with the exception of a tiny handful of true startup companies like Honda and Sony, all of Japan’s brands that were famous before the year 2000 or so, are keiretsu brands.

And for those of you who think big companies can’t innovate, let me remind you that from the 50s to the 70s, these keiretsu groups began innovating, disrupting, and dominating almost every industry on the planet; from cars, to cameras, to machine parts, to steel, to semiconductors, to watches, to home electronics, Japan’s keiretsu simply rewrote the rules.

But how did keiretsu do in the world of software development?  Well, pretty darn well, actually.

It’s important to remember, though, that the software industry in the 60s and 70s was very different than it is today. The software development process itself was actually rather similar. Fred Brooks wrote The Mythical Man Month about his experience during this era, and it remains as one of the best books on software engineering and project management today.

But the way software was bought and sold was completely different. In the 60s and 70s, software was written for specific and very expensive hardware, and the software requirements were negotiated as part of the overall purchase contract. Software was not viewed so much as a product, but more like a service, similar to integration, training, and ongoing support and maintenance. It was usually sold on a time-and-materials basis, and sometimes it was just thrown in for free to sweeten the deal. The real money was in the hardware.

Software in this time (both in Japan and globally) was written to meet the spec. It did not matter if it was creative, innovative, easy to use, or elegant, it just had to meet the spec. In fact, trying to build exceptional software in this era was considered a waste of resources. After all, the product had already been sold and the contracts had already been signed. The goal back then, just like many system integration projects today, was to build software that was just good enough to get the client to sign off on it as complete.

Software that met the customer’s spec was, by definition, good software.

Japan’s keiretsu did well in the age of big-iron. Although Fujitsu, NEC, and Hitachi never seriously challenged IBM and Univac’s global dominance in the 60s and 70s, they did pretty well in mini-computers and large office systems.

They were innovators.

Japan Turns its Back on a New Industry

However, when the PC revolution arrived in the late 1980s, Japanese industry as a whole was hopelessly unprepared, and not for the reasons you might think.

The reason Japanese software development stopped advancing in the 1980s had nothing to do with a lack of talented software developers. It was a result of Japan’s new economic structure as a whole, and the keiretsu in particular.

As a market, personal computers were something fundamentally new. Sure, the core technology and the hardware were direct continuations from the previous era, but this new market was completely different.

The PC market quickly coalesced around a small number of standardized operating systems and hardware architectures. Keiretsu did pretty well in the hardware side of this market, making some really impressive machines, particularly laptops.

But a market for non-spec or “shrink-wrap” software was something new to everyone. It required delighting the customer, and knowing what they wanted before they did. It was the kind of challenge that the keiretsu of the 60s and 70s would have thrown themselves into whole-heartedly, innovated aggressively, and then dominated.

But things in Japan had become very different in the 1980s.

Here was a chance to define and lead a new global industry. A chance for keiretsu to build a software industry from the ground up.

But, wait a minute. Why should they?

Sure, back in the 60s when Japan’s economy was small, survival required looking outwards, competing globally, making long-term investments, and innovating to make the best products in the world.

But this was the 80s! Japan was the second-largest economy on the planet and in the middle of the largest economic boom the world had ever seen. This was the era of Japan as Number 1, with economists predicting Japan’s GNP would be larger than America’s within a decade.

With such a lucrative, and pretty well protected, market right at their fingertips it made much more sense for the keiretsu to focus on the easy money rather than to take risky and expensive bets on an uncertain and emerging global market.

Each keiretsu group had their own technology firm who started selling PCs and software, some to consumers, but the big money was in corporate sales.  And since the keiretsu liked to keep the business in the family, these technology companies grew and profited by selling to their captive customers within their keiretsu group. And just like before, they made real money integration, and customization.

An unfortunate result of this is that the big Systems Integration companies or “SIs” emerged as powerful players, and Japan’s software firms never had to compete globally, or with each other.

Japan simply missed the opportunity to develop a globally relevant PC software industry.

The Beginning of the End of Innovation

Japan’s software industry in the 80s and 90s remained much like it was in the mainframe area. The software had to be just good enough for the client to sign off on it, and since they were largely captive clients unable to look outside their keiretsu group for support, that was a very low bar indeed.

But hey, as long as the economy was booming, no one minded spending lavishly to keep all the work in the keiretsu family, and all those little software defects could always be fixed in “phase two” of the project.

Software development was an exercise in box checking. You implemented a feature once the customer had asked for it and the contracts had been signed.

This not only caused Japan to miss out on the global software industry, but it marked the beginning of the collapse of innovation across Japanese industry.  Over the next 30 years, software would become a key driver of both innovation and efficiency. But by outsourcing their IT strategy to a single integrator, they had tied themselves to an anchor that would ensure almost every industry fell further and further behind the technology curve with each passing year.

Japan still has not recovered from this. Even today most enterprise systems are decades behind their global competitors. But, as we’ll see a bit later, things are happening now that could enable a quantum leap forward in Japan.

Life as a Developer in Japan’s Dot-com Bubble

So, what was it like to be a software developer in Japan in the 80s and 90s?

It was pretty bad. Software development was considered rather low-skill work. It didn’t pay well and was viewed as a kind of clerical work. The job was simply to write software that was close enough to whatever sales had promised the client while they were out drinking last week.

New hires with degrees in literature, business, or law, or whatever were rotated through software development for a few years to give them a sense of how different parts of the company worked. There was no real career path in software development. I mean, maybe you could move up into project management or over into sales, but if you were still actually writing code when you were 30, people kind of wondered what went wrong.

Of course there were some great, even visionary, software developers in Japan at that time. I knew some of them. People who wanted to make computers do new things. People who saw how technology could disrupt other industries, and developers who simply had a passion for making software that delighted users.

There were plenty of developers like that in the 80s and 90s. They were miserable.

Interestingly, hardware engineers were viewed very differently. Both then and now, hardware engineers are highly respected in Japan. Engineers are some of the most admired people at companies likeToyota, Mitsubishi, and Sony.

So, perhaps unsurprisingly, hardware innovation continued at a furious pace during the 80s and 90s. Products like the walkman and the Nintendo consoles achieved global success and the domestic market was filled with electronic diaries, dictionaries, and planners that were way ahead of what was available in the West.

And of course, eventually i-mode. Japanese consumers were sending email and browsing the web years before the Blackberry was released, and almost a decade before the iPhone.

Falling Down

But the rest of the word was moving in a different direction. The rest of the world was moving away from dedicated hardware and towards innovative software running on standard hardware platforms. As Marc Andreessen would later point out “Software was eating the world.”

As the dot-com bubble started to inflate, Japan began to realize they needed talented software developers, but without a software industry that actually valued software developers, companies had no idea where to find them. The best talent was usually unrecognized and trapped at the lower levels of the org chart. There was not much of a future pipeline. Since software engineering was not a respected or profitable career, few students opted to pursue it.

Some did of course, but these were the people that just loved programming. It was like becoming a musician or a manga artist. It was great that you are following your dreams. You might make it, but the odds were not in your favor.

When the foreign software companies started crashing into Japan in the 90s, the domestic industry could barely put up a fight.

The dot-com boom of the late 90s was the first wave of venture-funded, disruptive innovation in Japan, but it was not yet time for Japan’s software developers to step into the spotlight.

The successful founders of that era were mostly well-connected or incredibly scrappy businessmen. The general opinion of software developers had hardly changed at all. They just weren’t the kind of people you would trust to run a company.

I started my first Japanese startup during the dot-com boom, and at that time, I think the fact that I was a technical founder was even more unusual than the fact that I was a foreign founder.

Of course in one sense, the dot-com boom was an amazing time to start a software startup in Japan. You could call up almost any talented developer you knew, let them know hat they would be working on something important, that they would have meaningful input into product development, they’d be on a team that cared about code quality, and that their skills would be respected … and yeah, they’d want to come on board.

The Lost Decades Were Never Really Lost

The late 90s and the nights is often referred to as Japan’s “Lost Decades.” It was not a good time for the keiretsu companies. Not only did their power continue to weaken, but increased scrutiny of their cross-shareholdings and financials, and the merger of several banks across keiretsu lines meant that business as usual was over.  And pushing the knife in deeper, all of the implied economic and social guarantees that the keiretsu system was based on began to unravel.

In previous decades, Japan had focused on exporting domestically made goods, but now, not only was the domestic market attracting a greater focus, but Japanese industry began moving production out of Japan into cheaper overseas markets.

This was considered a betrayal by thousands of mom-and-pop manufactures who had spent their lives (or sometimes generations) as a highly integrated and specialized part of a single keiretsu’s supply chain, and who now found themselves suddenly cut off.

Japan’s famous lifetime employment system effectively ended during this period as well. It made sense for corporate groups to promise lifetime employment and predictable promotions when profits kept rising and labor was scarce, but now faced with mounting losses, corporate Japan began walking back all these implied promises.

This was a shock for Japan. It was a breach of the social contract that holds everything together. If hard work and loyalty would not be rewarded, then why dedicate your life to the company? To the distress of pundits and politicians, many young Japanese started saying they had no interest at all in joining the corporate world.

But the truth is, especially now that we can look back on it, these decades were not really lost decades at all. Growth slowed, and the changes were incredibly painful, but they were absolutely necessary to set the foundations for the coming wave of startup innovation and for Japan’s software developers to finally get the respect they so deeply deserve.

The Triumph of the Japanese Software Developer

I mark 2010 as the year Japan’s software developers finally started stepping into the spotlight, although things started moving a bit before that.

There were two triggers that led to this development. First, the emergence of cloud computing and second, the introduction of the smartphone. Although these were both technological developments, it was not the technology itself that led to the change.

Cloud computing drastically reduced the capital and time required to start a startup. In the dot-com era a decade before, starting an internet startup required purchasing racks of servers and paying system administrators to keep them running, but suddenly fully configured, maintained, and secure servers could be had for a few cents per minute — pay as you go.

Suddenly Japan’s software developers didn’t need to explain their idea to a VC and convince them that it would sell. They could just build things and get people to start using them and start paying for them. And that’s just what they did.

The other important development was the introduction of the iPhone in 2007 and Android a year later. Not just because of the technology, but because of how it changed the software business model.

Japan’s i-mode was years ahead of the West when it first came out, but getting your app on i-mode was largely a matter of lengthy negotiations with the telcos for one of the few highly-coveted slots on the menu. The smartphone ecosystems were different. Anyone who could develop an app of reasonable quality could deploy and sell it. There were no business connections, exclusive negotiations, or revenue commitments required.

2010 marked the beginning of the end of the software startup gatekeepers. As more and more talented developers realized how easy it was to start a startup, more and more started choosing startups over the traditionally low-status career path at large companies.

This, combined with a large dose of Silicon Valley glamour, has complexly transformed Japan’s image of the software developer. Software developers are valued and respected today. Unlike the dot-com days, both startups and enterprises compete aggressively to recruit and retain talented programs, even though there are a lot more of them today. Thankfully, people also talk a lot more about code quality.

Of course, this attitude shift was much broader than just developers. With the safety net of lifetime implement and guaranteed promotions removed, people have had to become less risk averse and more innovative. Those workers who had rejected corporate life, became freelancers and formed the core of Japan’s flexible startup workforce, and some of those tiny supply-chain companies began to rethink their business models.

This brings us to the start of the Disrupting Japan podcast about eight and a half years ago. We’ve talked to the innovators and followed the development of the startup ecosystem together during that time.

So, Where Do We Go From Here?

As we talk here together at the start of 2023, what does the future look like for Japanese software?

Japan has had a lot of catching up to do over the past fifteen years. After basically sitting out the global PC and dot-com revolutions, Japanese software developers have been making up for lost time and in the startup space. Japan is developing a competitive software market in some areas, but on average, there is still a long way to go.

Japan’s once dominant Systems Integrators will continue to see their power decline. Their customer lock-in is fading fast, and B2B SaaS software startups are letting Japanese enterprises leapfrog to modern IT systems for less than costs to maintain their SI-run legacy systems.

The SIs won’t disappear, of course. There will always be a need for good systems integrators, and the more forward thinking ones are already trying to reinvent themselves. However, the days when the SIs dictated their clients’ IT strategy are coming to a close. That is a very good thing for Japanese software, Japanese startups, and Japanese competitiveness as a whole.

The Kishida administration has made startups a national priority, and the importance of quality software and software startups in Japan has never been higher.

Even the old keiretsu firms have come around. They are increasingly looking to software startups to supplement internal R&D though both M&A and through long-term partnerships. In fact, last year Keidanren, Japan’s largest business federation, an organization that was one of the main architects and drivers of Japan’s post-war economic expansion, called on its member companies to greatly increase their startup investment and partnerships.

I am optimistic. As always, things will develop differently in Japan. In the same way the zaibatsu defined Japan’s Meja-era economic miracle, and the keiretsu came to define Japan’s post-war economic miracle, from some new combination of startups, enterprise, and academia will emerge something that will define the next economic miracle.

Today is a very good time to be developing software in Japan.

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TEKNOLOGI

Shopify och Google Cloud AI-integration ökar e-handelsmöjligheterna

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Cloud Computing News

Shopify and Google Cloud have unveiled an integration that enables retailers using Commerce Components – Shopify’s enterprise retail solution – to leverage Google-quality search capabilities and AI innovations. 

Enterprise brands on Shopify can today access Google Cloud’s Discovery Al solutions directly through Commerce Components, Shopify’s modern, composable stack for enterprise retail. This integration, which can now be used by Shopify merchants globally and is available in most languages, increases access to Google’s advanced search and browsing technologies so that retailers can create more fluid and fruitful shopping experiences for their customers. 

Shopify and Google Cloud’s new integration equips enterprise brands with artificial intelligence (AI)-driven product discovery capabilities that address real-world business challenges, including: 

  • Google Cloud Retail Search, which providesadvanced query understanding that can produce better results from even broad queries, including non-product and semantic searches, to effectively match product attributes with website content for fast, relevant product discovery. 
  • An AI-powered browse feature that uses machine learning to select the optimal ordering of products on a retailer’s ecommerce site once shoppers choose a category, like “women’s jackets” or “kitchenware.” Over time, the AI learns the preferred product ordering for each page on an ecommerce site using historical data, optimizing how and what products are shown for accuracy, relevance, and likelihood of making a sale. 
  • An AI-driven personalization capability that customizes the results customers get when they search and browse retailers’ websites. The AI underpinning the personalization capability uses a customer’s behavior on an ecommerce site, such as their clicks, cart, purchases, and other information, to determine shopper taste and preferences. 
  • A Google Cloud Recommendations AI solution thathelps retailers deliver personalized recommendations at scale. Recent upgrades to Recommendations AI can make a retailer’s ecommerce properties even more personalized, dynamic and helpful for individual customers.
  • Advanced security and privacy practices that help ensure retailer data is isolated with strong access controls and is only used to deliver relevant search results on their own properties.

Harley Finkelstein, president of Shopify, said: “We’re thrilled to continue our long-standing partnership with Google Cloud.

“We’re bringing together the best in commerce with the best in search to solve a complex and costly problem for enterprise retailers – world-class search and discovery for the online store.”  

Thomas Kurian, CEO of Google Cloud, said: “Shopify integrating Google Cloud’s Discovery AI technology into its enterprise retail solution puts the power of AI directly into the hands of merchants and brands to solve everyday problems.

“Now, retailers will be able to enhance their digital properties with better product discovery experiences, creating more fulfilling shopping experiences for their customers.”

Rainbow Shops builds a better customer experience with Google Cloud search technology

Rainbow Shops, a Shopify merchant and popular retail apparel chain with more than 1,000 stores, recently integrated Google Cloud’s Discovery AI for Retail technology directly into its own digital domains. After experiencing limitations with other search and product discovery solutions, Rainbow Shops approached Shopify about the possibility of using Google Cloud’s search and browse capabilities. 

When compared to other specialty search services, Rainbow Shops’ internal testing found that Google Cloud’s solution could deliver helpful results to an assortment of test queries 100% of the time. In addition to accuracy, Rainbow Shops saw an immediate reduction in the amount of time and effort its teams previously spent on manually refining search results, creating redirects, and pulling up to 50 other levers to get useful results.

Rainbow Shops is now using Google Cloud’s Retail Search technology, and importantly, it took less than a week for Google Cloud’s AI tools to be successfully integrated into Rainbow Shops’ online store and mobile app—all right before last year’s peak shopping moment for the retailer, Cyber Week. 

David Cost, VP of e-commerce and marketing, Rainbow Shops, said: “Now our search bar can handle almost anything our shoppers throw at it, surfacing helpful product results for nuanced queries like ‘lbd’ (little black dress) and extremely general searches like ‘Mardi Gras.’ We’ve also significantly advanced our ability to produce relevant results when a shopper has a typo in their query, which is commonly seen among our many customers now shopping on mobile devices.

“Rainbow Shops is using Google Cloud’s AI tools to create an undeniably better shopping experience for our customers. In just three months we’ve already seen search volume increase 48% and our bounce rate on visits has decreased three-fold.”

Consistency lacking in retailer search experiences, resulting in search abandonment

Despite the continued rise in online shopping, many shoppers report hurdles in the product discovery experience on retailers’ ecommerce properties. New research from a Google Cloud-commissioned Harris Poll survey found that search abandonment—when a shopper searches for a product on a retailer’s website or mobile app, but doesn’t find what they are looking for—costs retailers more than $2 trillion annually globally, and more than $234 billion in the U.S. alone.

Shoppers themselves say they depend on the search function or search box when shopping; it’s the most common way U.S. consumers search for products on retail websites (69%), followed closely by general website browsing (63%). The problem is that retailers’ search experiences lack consistency, as only one in 10 U.S. shoppers say they get exact results for their queries (12%) or good alternatives (11%) every time they use the search function on a retailer’s site. In fact, more than three in four U.S. consumers (76%) say that in the past month they have used the search function or search box on a retail website and it did not provide the item they were looking for. 

Vill du lära dig mer om cybersäkerhet och molnet från branschledare? Kolla upp Cybersäkerhet & Cloud Expo äger rum i Amsterdam, Kalifornien och LondonUtforska andra kommande teknologievenemang och webbseminarier för företag som drivs av TechForge här.

Taggar: AI, E-commerce, Shopify

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TEKNOLOGI

Hur data och människor driver innovation

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Hur data och människor driver innovation

The role of CIO is fast becoming the ‘chameleon’ of the C-Suite, necessitating the capacity to constantly evolve and take on additional responsibilities – moving beyond driving efficiency, to driving innovation and growth – shaping and creating digital transformation.

This includes leading modernization strategy, moving legacy technology and frameworks to the cloud, and spearheading data migrations. And it extends to onboarding, managing and retaining talent that may not be physically proximate with the rise of hybrid working, alongside responding to changing employee, consumer and ecosystem partner behaviours and expectations. In part one of this two-part special, we explore the vectors of change, and key issues and opportunities such as addressing the data paradox, moving from data management to data centricity and value, and democratizing the capacity to create and build. In part two, we move on to unpack human centred leadership, the power of the ecosystem, and skills-based organisation with final thoughts to reflect and integrate key themes and insights together.

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The world is rapidly changing with key trends impacting the path, progress and potential of digital transformation. These include a major shift to digital first and both customer and employee engagement personalisation. For consumers, this means heightened expectations around the level of differentiated, relevant and tailored experiences they will receive and across all touch points within that journey, whether onboarded within-stream on social media, or via a web form referral, or via a call-centre and beyond – all touchpoints must not only connect to your customer but equally connect to one another too. This is the essential foundation of an opti-channel approach which seeks to be friction-free and continually learning from previous interactions.  Perhaps then, it is no wonder that 81% of organizations in a recent study cite CX as a leading competitive differentiator. And for employees this also matters greatly too, with focus areas notably growing in relation to skills development, for example the personalisation of learning journeys.

Additional trends include the centricity of gaining and retaining digital trust, the demands of hyper-competition, the rise in consciousness around ESG and accelerating talent gaps coupled with high employee agency. This is also reflected in work trends around burnout, middle management squeeze, ‘quiet quitting’, the ‘great resignation’ and proximity to churn. And it extends to the transition to ‘As A Service’, the application of digital platforms for agile business, a shift in platform users, notably citizen developers and scientists and the advance of ‘composable thinking, composable business architecture and composable technology’ as the ‘three pillars of composable digital business’ (Gartner®) which is unpacked further in the definition below:

‘A composable digital business applies the core principles of composability (modularity, autonomy, orchestration and discovery) to the foundations of its business architecture (the business model, enterprise operations and strategy) in order to master the risk of change and reach untapped business value’ Gartner®*

Beyond this, ecosystem partnerships are also a key innovation strategy. This is discussed in the excellent blog by Greg Sarafin, EY Global Alliance and Ecosystem Leader and includes a 5-part suggested strategy to support CIO’s in addressing key challenges in order to build the ‘digital foundation’ that underpins ecosystem success. And of course, there are other vectors of change and uncertainty, especially geopolitical (WEF 2023), which have impacted upon already accelerating challenges such as cybersecurity with threats escalating in scope, sophistication and scale. The list of influences just goes on!

So how does today’s CIO meet these growing, interrelated and complex needs? This piece explores data centricity, human-centred leadership and skills-based organization as the key catalysts to bring to every decision, innovation and experience for shared value impact. It is supported by insights from EY’s bi-annual Tech Horizon research, part of the CIO Imperativethought leadership series, alongside other salient studies, including my own original research.

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Addressing the Data Paradox

Data that is secure, trusted and available – to the right role or system, and at the right time – has rapidly emerged to be the strategic currency of the digital age, alongside trust. But today’s data landscape reveals a paradox when it comes to achieving that value.  Considering the 4’s V’s of Data: Volume, Velocity, Variability and Volatility, these have all clearly accelerated, most notably volatility and volume with the scale of cross sector disruption and evolved behaviours in the last two years. This has exacerbated a ‘DataParadox’ intention/action gap in three core areas, as revealed by the Dell research which I was directly involved in:

1 – Businesses believe they are data-driven but they don’t prioritize the use of data across the organization.

2 – Businesses need more data, but they have more data than they can handle right now.

3 – Many businesses believe in ‘As A Service’ benefits, but only a few have made the transition to such a model.

Overall, data overload and the inability to extract meaningful insights from data emerges as the third highest barrier to digital transformation in the Dell study. This also aligns with findings from EY’s bi-annual Tech Horizon research, which reveals that 53% of senior executives identify data and analytics to be their leading investment priority for the next 2 years – reflecting the heightened significance, this represents a 50% increase since 2020.

So it becomes clear that whilst timely data-driven decisions are at a premium there are still barriers to address, including data being too distributed or siloed or wrangling disparate sources via a central ETL pipeline, right through to tool, cloud and vendor sprawl, disruption in migrations, and taking too long to either move data or analyse it (WANdisco 2022). Additional examples include broken data pipelines after operational database changes, lack of integration and holistic visibility, growing talent gaps challenges (IDC Research*) which describes ‘a worrying shortage of talent that could throttle innovation and even lead to some businesses failing altogether…’. Additionally, as discussed during a recent keynote session Q&A, the team demands of building and maintaining a cloud data warehouse or equivalent, alongside concerns around security, measurement and levels of cloud waste (Flexera 2022, Eaves 2022). 

This is reflected in EY’s study findings, where the second greatest challenge reported was that of building complex security and privacy requirements, cited by some 27% of respondents -an area that is only likely to grow given geographical differences across governance and compliance which can add to the complexity of management. And given the rising prominence of ESG and increasing demand for better cohesion across measurement, reporting, transparency and accountability of disclosures, needs in this specific area are poised to rise further still. I believe that ESG is the now the next frontier in privacy and data governance which will necessitate moving beyond pure regulatory compliance to holistically identifying areas throughout the data cycle that create risks.

Putting this all together, there is a fundamental need for interoperable, robust data capabilities across all areas of organisations from SME to Enterprise alike, across all verticals.

From_Data_Management_to_Data_Centricity__And_Value.jpeg

From Data Management to Data Centricity – And Value!

The time is now to move beyond disparate technology stacks, restricted facts and siloed decision-making capabilities, necessitating a migration in approach from data management to data centricity – this evolution describes the application of data as a shared asset to enable active intelligence and insights for customers, stakeholders and ecosystem partners, and to help continuously improve decisions, processes, products, and services. But with EY’s Tech Horizon research finding only 16% of organizations reporting that they are data-centric today, (although increasing), there is clearly still work to be done.

Underpinned by the vision, clarity and communication of a data centricity framework, this should include areas such as business goals and data strategy, data-science and architecture, data governance, reporting and visualisation. And this can be greatly supported by the use of a data fabric and data mesh architecture integrated across the enterprise. Indeed, data fabric plays a pivotal role in helping organizations achieve resiliency and sustainable growth, underpinned by right-size governance and data consistency, accuracy and accessibility via a single common platform. And the advances extend to self-service analytics too!

This approach affords a single data view, moving beyond the fragmented perspective that can result from data previously housed in disparate data lakes and warehouses. Or in other words, a fabric approach decouples consumption from diverse data repositories and works across siloes to pull in data that can be scaled and analysed. It is particularly relevant for more traditional (non digital-native) IT companies, looking to leapfrog the limitations of legacy IT.

Putting this into context and reflecting the range of application, this is something institutions like the military are already actively committing to. A recent announcement by the UK Army on ‘Demystifying data’ highlighted just how the UK is pushing ahead with data mesh solutions that add a layer to a data fabric to provide mission-critical products for commanders. Secure access to timely, relevant, high quality data always has been, and always will be the differentiator for success, whether for business decision making, or battle readiness!

And going further still, with the creation of a semantic layer to the data fabric, organisations can apply AI at scale alongside analysis tools to gain active intelligence around rapidly evolving trends and providing the agility to transform go-to-market strategies in days, not weeks – driving efficiency and innovation at the same time. By enabling organisations to run AI on the enterprise edge, this negates the need to build multiple algorithms to link AI into core processes. Further, AI systems, combined with ML, are able to transform data so that it will learn, cleanse itself, and pull in additional data as customers and market conditions change.

Embodying the ethos of ‘build for agility’ and ‘data as a product’, employing a data mesh as a flexible and scalable data platform version of microservices, enables leveraging of a self-serve and domain-oriented design which matches the language and structure of your code to its aligned business domain, with each handling its own data pipelines. This is an example of a data architecture to support an overall implementation of a data fabric, which puts ownership back to the domains, whilst retaining centralised governance. In this way, data expertise will expand from the IT department into business groups, internal operations, and customer relationships too, with security and control embedded by design, and whilst also helping to establish a shared vision around high quality, integrated data for all, no matter where that data resides – elements that all support the evolving role requirements of the CIO.

Democratizing the Capacity to Create and Build

Given the expanded user base of data, its democratization becomes an imperative for data strategists – making it more user-friendly, intuitive and accessible through an array of devices and/or through citizen developers. An excellent example of this in practice is the launch of SAP Build, a new unified low-code solution built on the SAP Business Technology Platform (SAP BTP) and which democratises the capacity to create and co-create, allowing everyone to build and augment enterprise applications, automate processes, and design business sites with intuitive visual drag-and-drop simplicity.

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And you can learn more about the benefits across empowering citizen developers, community and education, addressing developer bottleneck constraints and accelerating that all important time to value in this new 4 part video series här – I loved putting this together! And most recently still, you can explore the launch of SAP DataSphere which represents the next generation of its cloud data warehouse service with new data cataloguing, simplified data replication and enhanced data modelling capabilities to enable easy access to business-ready data across the entire data landscape. Accompanying this launch, a new data education series can be freely accessed här

Supporting all of this, agility and adaptiveness are key, making technology elasticity an important consideration, and necessitating configuration that utilises a tailored combination of core and custom features and modules, with ‘just enough’ customization to meet needs. This is especially important in applications such as Supply Chain, as explored by EY här. The right change management method is critical too, with approaches like Continuous Improvement, Continuous Deployment (CI/CD) enabling introduction of smaller, more regular changes that afford agility and make fault isolations easier to detect – so reducing risk too. 

All feedback and follow-on questions most welcome.

Research Notes and Additional Info

Gartner, Becoming Composable: A Gartner Trend Insight Report, Yefim Natis, Janelle Hill, Partha Iyengar, Gene Alvarez, Jennifer Loveland and Chris Howard, 12 January 2023

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved

IDC Research, How to be a Digital Leader in 2022, Develop Your Digital Quotient To Be Successful on Your Cloud JourneyEurope and North America Info-Briefs, Francesca Ciarletta, Carla Arend, Archana Venkatraman and Frank Della Rossa.

IDC RESEARCH is a registered trademark and service mark of International Data Group Inc and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved

About the Author

Prof. Sally Eaves is a highly experienced chief technology officer, professor in advanced technologies, and a Global Strategic Advisor on digital transformation specializing in the application of emergent technologies, notably AI, 5G, cloud, security, and IoT disciplines, for business and IT transformation, alongside social impact at scale, especially from sustainability and DEI perspectives. An international keynote speaker and author, Sally was an inaugural recipient of the Frontier Technology and Social Impact award, presented at the United Nations, and has been described as the “torchbearer for ethical tech”, founding Aspirational Futures to enhance inclusion, diversity, and belonging in the technology space and beyond. Sally is also the chair for the Global Cyber Trust at GFCYBER.

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TEKNOLOGI

Encryption demand soars as 60% of business data kept on the cloud

Publicerad

Cloud Computing News

Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.


The demand for cloud encryption is estimated to increase at a CAGR of 30.9% from 2022-2032. The market valuation is projected to increase by US$ 2.4 Bn by 2022 & US$ 34.8 Bn by 2032.

This is according to Future Markets Insight (FMI), which says organisations are investing in the modernisation of data storage strategy with the adoption of cloud technologies for digital transformation. This is expected to drive growth in the cloud encryption market.

The growing need to store data in public and private cloud-based storage is spurring demand in the market.  Also, the pandemic forced organisations to adopt remote work, which increased the use of digital technologies and online data sharing. This has resulted in an exponential rise in cyber breaches like ransomware, malware attacks, and phishing.

As a result, enterprises are adopting cloud encryption to safeguard their sensitive data from data breaches and cyberattacks. Cloud encryption encodes the data by converting the plain text data into cipher text, which is unreadable by malicious users, thereby preventing data breaches. It provides enterprises with automated security, reduced complexity, and risk reduction by offering built-in security controls and continuous protection. 

Increasing data volumes have driven the adoption of big data analytics across companies, which is capable of processing and analyzing results of big data and providing descriptive, predictive, and prescriptive results. However, one of the biggest issues is how to gain perfect security for big data.

Cloud computing and cloud data stores have aided the growth of big data. Businesses can obtain superior insights from their enormous amount of structured and unstructured data by adopting Big Data analytics in the cloud. Companies handle large amounts of data and leverage the cloud to perform analytics and keep it confidential. 

With an increase in data saved in the cloud storage server, hackers try to access confidential data using organisational cloud servers with the help of different decoding techniques. Hence, the use of advanced cloud encryption software by organisations has increased for achieving semantic security. 

“As cybersecurity and data security are equally important, enterprises should focus on high capital investment in cloud security by adopting cloud encryption. Encryption is recognised as a top tool required to meet new privacy requirements and should be widely adopted”, said an FMI analyst.  

Key Takeaways: 

  • By component, the solution segment is anticipated to expand at a 32% CAGR through 2032.
  • By service model, the infrastructure as a service (IaaS) segment is estimated to grow by 17.8X during the forecast period.
  • Based on enterprise size, the SME segment is estimated to grow by 16.8X during the assessment period.
  • In terms of industry, sales in the IT & telecom segment are anticipated to increase at a CAGR of 36.5% between 2022 & 2032.
  • The U.S. is projected to hold 71.5% of the North American cloud encryption market share by 2032.
  • Indonesia will emerge as a lucrative pocket, with sales growing at a 43.2% CAGR through 2032.

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Taggar: cybersecurity, encryption

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