Don’t expect AI software companies to gobble up revenues SaaS-style, warns a16z

The potential of artificial intelligence (AI) revolutionising software is evident, from creating new data models to the improved insights gleamed from the data provided. If you’re a business intelligence (BI) vendor and you are not exploring AI or machine learning in some capacity, for instance, then there is a real danger of missing the boat.

But if you’re expecting AI software companies to eat up recurring revenues like their cloudy, SaaS-y predecessors, then think again.

Martin Casado and Matt Bornstein, of venture capital firm Andreessen Horowitz (a16z), argue that lower gross margins, scaling challenges and weaker defensive capabilities mean AI businesses are not going to resemble traditional software companies going forward. What’s more, the mix means AI companies will more closely resemble services-oriented businesses.

One key area of definition is around cloud infrastructure costs. While SaaS providers are among the many businesses who are likely to use a hyperscaler or other cloud provider, companies focusing on AI software will have much more complex – and subsequently expensive – demands, from training models, to inference, to the rich media being used.

Nascency is also a concern, a16z note. “We’ve had AI companies tell us that cloud operations can be more complex and costly than traditional approaches, particularly because there aren’t good tools to scale AI models globally,” Casado and Bornstein wrote. “As a result, some AI companies have to routinely transfer trained models across cloud regions – racking up big ingress and egress costs – to improve reliability, latency, and compliance.”

As a result, this chunk of cost could put an immediate stop to thoughts of gross margins in the 60%-80% range, with sights lowered to 30%-50%, with scaling ‘linear at best’, rather than supersized. But there are other reasons to consider.

The human factor is an important point to consider, a16z noted. Take the example of the largest social media companies hiring thousands of human moderators to help the AI-based systems. This is not to mention the continually iterative process of training models, securing new training data, and then feeding that back into the systems. The need for human intervention will decline going forwards, but Casado and Bornstein wrote that ‘it’s unlikely that humans will be cut out of the loop entirely.’

Putting together a strong defensive moat, as a16z calls it, is more difficult than it seems. SaaS companies can do so by owning the intellectual property generated by their work, such as the source code. Open source providers have, as the past year has shown, come into problems with their differentiated approach. Yet for AI companies, reference implementations are available from open source libraries, while a lot of the groundwork is conducted in academia. Ultimately, it comes down to who owns the data; in this instance, it is the customer, or in the public domain.

The future of enterprise software is a fascinating one with the emergence of various technologies. In 2018, venture capital fund Work-Bench explored how AI was being incorporated, again noting the roadblock between the academic work being undertaken and the business models being plugged into it. “Despite hopeful promise, startups racing to democratise AI are finding themselves stuck between open source and a cloud place,” the report noted.

While stressing caution, Casado and Bornstein are overall optimistic, so long as AI companies heed the warning signs. “Things like variable costs, scaling dynamics, and defensive moats are ultimately determined by markets – not individual companies,” they wrote. “The fact that we’re seeing unfamiliar patterns in the data suggests AI companies are truly something new.

“There are already a number of great companies who have built products with consistently strong performance.”

You can read the full a16z analysis here.

Editor's note: You can read more news on artificial intelligence, machine learning, deep learning and more at our industry-specific sister publication, AI News.

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Microsoft touts ‘enhanced AI’ features for Dynamics 365


Keumars Afifi-Sabet

21 Feb, 2020

Microsoft has unveiled an operations-centric module for its Dynamics 365 suite of enterprise resource planning (ERP) and customer relationship management (CRM) applications, on top of enhanced AI capabilities.

Customers are being promised smarter AI-powered business insights in 2020, with additional technology powering new features such as forecasting in Dynamics 365’s Sales and Finance Insights apps. A preview for these features is expected to be released in May.

This is included in a package of 400 new and updated features set to be rolled out over the course of this year as part of Microsoft’s 2020 release wave 1, which spans features touted to be released from April through September.

The Dynamics 365 Project Operations tool, slated for an October 2020 release, is being launched to support project-oriented teams managing data across different data silos to stitch their systems together.

The application connects cross-functional project teams, with Microsoft claiming that it offers the visibility needed to reduce the barriers to efficient working that currently exist.

“The predictive forecasting capabilities enable the proactive decision-making needed to meet sales goals,” Microsoft’s president for business applications James Phillips said, of the suite’s enhanced AI capabilities.

“Dynamics 365 does this by extracting patterns from customer relationship management (CRM) data, current and historical leads, won or lost opportunities, contacts, accounts, customer interactions such as emails and calls, and more data sources, and then projecting these patterns into the future.”

Updates to Microsoft’s customer data platform, meanwhile, aim to help organisations struggling to give their customers a personalised experience. These struggles are largely attributable to disconnected systems and data silos that can’t join together to give a holistic view of the customer journey across websites, purchases, service calls, and app usage.

The company is introducing first and third-party data connections to enrich customer profiles, that can be updated in real-time. These will be laced with insights from third-party data sources, including demographics and personal interest, in order to generate a rich picture of organisations’ customers.

Microsoft is also expanding the availability of customer insights to government cloud computing environments in order to improve the ‘citizen experience’, meaning public sector customers can better interact with employees and citizens.

UK among countries most likely to encounter cloud attacks


Sabina Weston

21 Feb, 2020

The UK is among the most cloud insecure countries in Europe, according to a new survey conducted by Specops Software.

Nonetheless, it is still among the European countries least likely to encounter ransomware attacks and cryptocurrency mining, at 3.82%, making it the 16th most cyber-secure country in Europe – out of the 32 which took part in the study.

Specops’ survey measured European citizens’ cyber security by analysing the percentage of cloud provider attacks on Azure and the monthly percentage of machines that encountered cryptocurrency mining, malware and ransomware attacks to determine who is the most cyber-insecure.

The study found that machines in the Netherlands were most likely to encounter cyber-crimes via the cloud, with 16.28% of Azure accounts in the Netherlands having faced attacks.

Despite being one of the countries least likely to encounter ransomware attacks and cryptocurrency mining, it was still named the most cyber insecure country (17.64%) in Europe, alongside Bulgaria, Belarus, and Ukraine. Specops also revealed that one in ten (10.17%) machines in Belarus encounter malware every month.

On the other side of the spectrum, Ireland, which is famously home to one of  Facebook’s major HQs, was the least likely to experience cyber-crimes – at 1.08%.

Other cyber-secure countries include Norway, Denmark, Switzerland, and Iceland.

Microsoft has also recently conducted separate research into cyber threats in Ireland, revealing that 70% of large Irish firms have experienced problems with phishing, hacking, cyber-fraud, or other cyber-attacks.

Three in four (76%) of senior leaders in large Irish firms worried about digital threats, while only one in four are confident they can respond to any security incident effectively. This proves that, despite Ireland being supposedly the most cyber-secure country in Europe, senior leaders do not feel confident about their level of security.

Human error and misconfigurations primary source of Kubernetes security snafus, report says

StackRox, a provider of cloud-native, container and Kubernetes security, warned in its previous report that the security implications for Kubernetes were beginning to spill over to adoption – and the release of its updated winter study have proved the company right.

The paper, the winter edition of its State of Container and Kubernetes Security Report, was put together alongside 451 Research and polled more than 500 industry professionals.

94% of those polled said they had experienced security incidents in their container environments during the previous 12 months. As is frequently the case with other cloud security snafus, human error – in this case misconfigured containers – can be found as a root cause, a trend which StackRox said was ‘alarmingly common.’

More than two thirds (69%) of those polled said they had experienced a misconfiguration incident; just over a quarter (27%) found a security incident during runtime, with a similar number (24%0 having a major vulnerability to remediate.

86% of respondents said they were running containerised applications in Kubernetes – the same number as in the spring survey. However, the way Kubernetes is being used is changing rapidly, as more organisations put trust in the hyperscalers managing their workloads. Just over a third (35%) of respondents said they manage Kubernetes directly today – down from 44% six months ago – with more respondents (37%) using Amazon EKS. More than one in five (21%) say they use Azure AKS and Google GKE, with both representing a significant increase from spring.

In a similar theme, maturation is increasing in terms of cloud-only environments. While hybrid deployments remain more popular – 46% compared to 40% for cloud-only – it represented a big drop from the 53% who cited it six months ago. For cloud-only, organisations remain predominantly trusting a single cloud, although multi-cloud deployments are becoming more popular.

The previous report, issued in July, gave more of a general warning on container security. Six months prior, two in three organisations said they had more than 10% of their applications containerised – yet two in five were concerned their container strategy did not sufficiently invest in security. This time around, only 28% of organisations polled said they had fewer than 10% of their containers running in production – down from 39% last time.

“One of the most consistent results we get on our own surveys of DevOps and cloud-native security technologies is how important security is for these environments,” said Fernando Montenegro, principal analyst at 451 Research. “It is interesting to see how this observation fits well with the StackRox study, highlighting the need for both engineering and security professionals to have visibility and properly deploy security controls and practices for container and Kubernetes environments.”

You can read the full report here (email required).

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Security versus productivity: Exploring the double-edged sword of the cloud

Adopting cloud technologies has become a common strategy among organisations across all sectors taking the road towards digital transformation. The benefits are evident: businesses that maximise all that the cloud has to offer often see a significant improvement in productivity.

However, the journey is not without its stumbling blocks and organisations that fail to prepare will all too often end up taking one step forward, two steps back. Migrating to the cloud presents an array of security and implementation risks which must be resolved if the technology is to be truly taken advantage of. The implementation of any new technology often presents plenty of bugs which must be dealt with. Ignore these issues, and businesses will find themselves falling foul of hackers who will capitalise on any chinks in an organisation’s armour. 

So, as organisations transition to the cloud, they face a number of strategic challenges. To what extent should they adopt hybrid multi-cloud technology platforms? How do they keep data safe? And how can they foster a progressive culture that enables them to maintain IT security and drive productivity?

Laying the groundwork

Incorporating any new technology should, of course, be preceded by a well thought out strategy. But businesses striving to gain a competitive edge by speeding up their digital transformation can be tempted into taking shortcuts when migrating to a new technology, and the process can become plagued with mistakes.

Failure to put a robust strategy in place can lead to devastating problems further down the line – a costly error which we’ve seen organisations make far too many times. It’s been reported that in January 2020 alone, 1.5 billion records were breached, highlighting the worrying scale of cyber attacks and data breaches impacting on businesses that continue to operate with a weak IT security infrastructure in place. 

The size of the organisation is immaterial. Attackers have become so sophisticated that no business can claim to be 100% safe. Retail has become one of the most targeted industry sectors, enticing cyber criminals with a rich pool of data where it's all too easy to identify individuals and their payment information. Moreover, what makes this scenario more complex is that retail is undergoing one of the greatest transformations it has experienced in decades. It’s never been more critical for organisations moving to the cloud to develop a robust and secure cloud strategy. 

Security by design

Regardless of size, all businesses need to appreciate that, despite their best efforts, their IT systems will never be entirely secure. As hackers and their methods evolve, organisations will need to stay one step ahead by constantly evaluating and improving security measures. This is only possible if organisations take a ‘security by design’ approach, instead of ‘by addition’. Retrofitting cybersecurity into systems is no longer a sufficient or effective way to operate and will hit an organisation’s back pocket just as hard as it hits its technology infrastructure. 

Since cybersecurity is mission critical, it stands to reason that businesses need to give it the attention, care and resource that it warrants. This means clarifying the separation of layers and functions. In the case of WAN environments, the desired outcome is that they reinforce one another instead of masking blind spots or creating joints that are a point of weakness where threats can infiltrate essential systems. 

Culture: The glue that holds a security strategy together

The concept of a physical office or workspace as a perimeter to be protected is increasingly a thing of the past. Most organisations have capabilities to operate virtually and staff can now work from almost anywhere. And, while the cloud is mostly responsible for enabling these productivity benefits, it creates security threats too.

The reality is that human error is at the root of nearly one in five of data breaches; and whilst almost 75% of attacks are perpetrated from outside an organisation, more than one in four involved insiders. Employees are often the weakest links, and hackers are more than aware of this fact. Educating all colleagues, and not just senior management, about cybersecurity is therefore vital.

Nurturing a security culture across an entire organisation is paramount – if executed effectively, it will transform security from a one-time event and the responsibility of an IT team into being a positive part of the firm’s day to day operations and culture.

Just as organisations need to continuously evaluate the cybersecurity infrastructure in place, they also need to make employee education an ongoing priority. Helping employees to understand the implications of a cybersecurity attack will also highlight the importance of continuous diligence; after all, an organisation’s security will only ever be as strong as its weakest link.

It is only through unifying technology, culture and employees that an organisation’s critical data can remain safe. Succeed at this, and organisations will lay the right foundations in order to confidently explore all the advantages that the cloud has to offer.

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Google adds migration tools with Cornerstone acquisition


Bobby Hellard

20 Feb, 2020

Google has acquired a mainframe- and database-migration specialist as it continues to add tools to help enterprise customers move workloads to public clouds.

Dutch-based Cornerstone Technology provides tools and project-management services for application and database migration.

The firm will be incorporated into Google‘s mainframe-to-GCP service, which customers can access through its professional services and partner networks.

There are no details about the cost of the deal as yet, but the move is in keeping with the company’s enterprise strategy that focuses on helping its existing clients move their legacy workloads to the cloud.

«Easy mainframe migration will go a long way as Google attracts large enterprises to its cloud,» said Matt Eastwood, senior VP of enterprise infrastructure at IDC. «Google Cloud is listening to its customers and meeting them where they are, steadily improving its services and attracting businesses across industries.»

This is the second deal Google has announced in February after the firm’s $2.6bn acquisition of Looker, a service for data analytics for multi-cloud customers.

Moving mission-critical workloads to the cloud can be complex and the aim is for Cornerstone’s expertise and hands-on approach to slowly modernise customer stacks without the need to re-architect all of their legacy applications.

The company provides a migration roadmap which conducts a mainframe assessment to find a suitable path for upgrading. It also converts code languages and databases that help prepare applications for modern infrastructure, which also includes automated data migration.

«We’re migrating both our AS/400 and z/OS systems to more modern technologies like Java and SQL databases,» said Ricardo Orlando, CTO of Brazilian financial services company Boa Vista. «Google Cloud is helping us realise new revenue streams and more effectively deploy our resources.»

Google Cloud acquires Cornerstone to help customers migrate their mainframes

Google Cloud’s shopping list shows no signs of abating, with the company announcing the acquisition of Cornerstone Technology, a mainframe specialist.

The 30-year-old provider, based in the Netherlands, has an overall remit of ‘helping customers protect and improve their investments in essential legacy enterprise applications’, in Cornerstone’s own words. Cornerstone uses automation to break down programs, turn them into services, and then make them cloud-native.

This includes COBOL, which to the potential surprise of many is still used by many enterprises. A recent study from Micro Focus, the language’s arbiter, noted that for more than two thirds of businesses polled, COBOL app modernisation was a preferred strategy to replacement and retirement.

“As the industry increasingly builds applications as a set of services, many customers want to break their mainframe monolith programs into either Java monoliths or Java microservices,” wrote Howard Weale, Google Cloud director of transformation practice in a blog post. “This approach to application modernisation is at the heart of the Cornerstone toolset.”

Google Cloud made a spree of acquisitions in 2019 under the leadership of CEO Thomas Kurian. The standout deal was for business intelligence platform Looker in June, valued as a $2.6 billion all-cash transaction. Other deals were for data migration service provider Alooma in February, storage firm Elastifile in July, and VMware workload runner CloudSimple in November.

The acquisition of Cornerstone will, as the name suggests, form a significant chunk of Google’s ‘mainframe-to-Google-Cloud-Platform’ offerings.

“For decades, companies have relied on a mainframe architecture to run their mission-critical workloads, but it often holds developers back from taking advantage of new technologies that enable them to innovate more quickly,” explained Weale. “Cloud computing presents the opportunity to modernise your applications and your infrastructure, resulting in better capabilities and allocation of your resources so your organisation can focus on your core business.”

The obvious target for this acquisition is IBM, whose mainframe business remains significantly profitable. At the same time the Cornerstone acquisition dropped, this reporter received a separate communique from IBM which touted the company as a top three cloud vendor ‘far ahead’ of Google.

IBM cites Google’s eventual disclosure of its cloud revenues – $2.6bn for the most recent quarter, compared with IBM’s reported $6.8bn – as key. Yet measuring an apples-to-apples comparison across all services remains tricky. For cloud infrastructure services alone, according to figures from Synergy Research earlier this month, Google holds 8% of the market, compared with 6% for IBM.

Financial terms of the Cornerstone acquisition were not disclosed.

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Managing cloud lifecycles


Steve Cassidy

20 Feb, 2020

Hardly anybody talks about lifecycles in IT, least of all me. I don’t see the end of use of any device as a special occasion to be marked and celebrated: I still have working PCs from the late 1990s. Even so, I had to stop and pay attention when I heard a senior exec from Arm – the world’s most popular CPU maker no less – mention that major cloud players are now reinvesting in their data centres on a yearly basis.

This is an incredibly short lifecycle, but when it comes to the cloud there are multiple things that might need to be retired, upgraded or otherwise cycled. One is the data centre hardware itself; this might seem like a very fundamental refresh, and it could transform the customer experience, making things either faster or slower. But, in these days of virtual machines and serverless design, it might equally be completely invisible from the outside, except where it leads to a change in tariffs.

Then there are upgrades to the orchestrator or container OS. These tend to happen with little or no notice, excused by the urgency of applying the latest security updates. As a result, any dependencies on old code or deprecated features may only come to light on the day of the switch. As a savvy cloud customer, your best defences against such upheaval are to spread your systems across multiple suppliers, maintain portfolios of containers running different software versions and take a strong DevOps approach to your own estate.

Other scenarios include the sort of big move when a beta site is finally promoted and becomes the main site, and the eventuality of a cloud provider being taken over by another, resulting in a burst of service changes and tariff renegotiation. Remember, lots of high-tech businesses operate with the express intention of being acquired at some point, once they have a good portfolio of customers, a steady revenue stream and hence a high share price. Such a strategy is music to the ears of venture capitalist backers, eager to recoup their investment and profits; I will leave you to consider whether it’s well suited to cloud services, which place a high emphasis on continuous and uninterrupted service. There’s a reason why many cloud company contracts are all about inhibiting customer mobility.

Migration patterns

It’s clear that, when we’re talking about the cloud, “lifecycle” entails a spread of quite different activities, and bringing them all together under one banner doesn’t do you much good: the lessons learnt from going through one of the above events won’t do much to help with others. 

However, the situation doesn’t have to be complicated – at least not if you actually have developers, and aren’t just stuck with a narrow selection of package providers. If you are in this lucky position, and you’ve been listening to at least the tone of your development team’s comments on the various fads and fashions in development, there’s a fair chance that your IT portfolio will have been built with the sorts of tools that produce nice, mobile and tablet-friendly, infinitely resizeable, bandwidth-aware, cloud-scalable websites. If that’s what you’re working with, it can be relatively easy to ride out lifecycle events.

Unfortunately, this is by no means universally the case, especially not for systems that have been around long enough for large parts of the business to have been built on them. If you already have a code base that works, it can be tough to secure the development time and cost commitment to move it from (say) QuickBASIC or COBOL onto Ruby on Rails, Java or PHP. 

Yet this is itself one of the most significant lifecycle events, or at least part of it. It may seem a stretch to refer to code migration as a lifecycle end, but when you first unleash your prototype on a public cloud platform, nobody really knows how it’s going to perform, or how resource-hungry it might be, and your production systems person is not going to want those kind of unknowns messing up their carefully controlled production space. The requirements for releasing that prototype into the big bad world thus emerge from the development and testing process. 

That output ought to, at least, incorporate a statement about what needs to be done, and after how long, with an eye on three quite distinct systems. First, there’s the prototype in its current state, which at this point is probably still languishing on Amazon or Azure. Then, of course, there’s the predecessor system, which is going to hang around for a couple of quarters at least as your fallback of last resort. Then there’s the finished, deployed product – which, despite your diligent testing, will still have bugs that need finding and fixing. Redevelopment involves managing not one, but three overlapping lifecycles.

If you’re wondering how much of this is specific to the cloud, you have a good point. You would have had very similar concerns as a project manager in 1978, working in MACRO-11 or FORTRAN. Those systems lack the dynamic resource management aspect of a cloud service, but while cloud suppliers may seek to sell the whole idea of the “journey to the cloud”, for most businesses reliability, rather than flexibility, remains the priority. 

The question, indeed, is whether your boringly constant compute loads are actually at the end of their unglamorous lifecycle at all. It’s possible to bring up some very ancient operating systems and app loads entirely in cloud-resident servers, precisely because many corporates have concluded that their code doesn’t need reworking. Rather, they have chosen to lift and shift entire server rooms of hardware into virtual machines, in strategies that can only in the very loosest sense be described as “cloud-centric”.

Fun with the law

Despite the best efforts of man and machine, cloud services go down. And when it happens, it’s remarkable how even grizzled business people think that legally mandated compensation will be an immediate and useful remedy. Yes, of course, you will have confirmed your provider’s refund and compensation policy before signing up, but remember that when they run into a hosting issue, or when their orchestrator software is compromised by an infrastructure attack, they will suddenly be obliged to pay out not just for you, but for everybody on their hosting platform. What’s the effect going to be on their bottom line, and on future charges?

If you’ve been good about developing a serverless platform, hopping from one cloud host to another isn’t going to be a big issue. Even if you’re in the middle of a contract, you may be able to reduce your charges from the cloud provider you’re leaving, simply by winding down whatever you were previously running on their platform. After all, the whole point of elastic cloud compute is that you can turn the demand up and down as needed.

Sometimes you might end up in the opposite situation, where you reach the end of a fixed-term contract and have no option but to move on. This comes up more often than your classic techie or development person imagines, thanks to the provider’s imperative to get the best value out of whatever hardware is currently sitting in the hosting centre. If there’s spare capacity in the short term, it makes sense for the vendor to cut you a time-limited deal, perhaps keeping your cloud portfolio on a hosting platform from a few years ago and thereby not overlapping the reinvestment costs on their newer – possibly less compatible – platform.

Hardware and software changes

For some reason that nobody seems minded to contest, it’s assumed in the cloud industry that customers will be agile enough to handle cloud vendors making root and branch changes to the software platform with effectively no notice. You come in to the office with your coffee and doughnuts, to be greeted by a “please wait” or a similarly opaque error, which means that your cloud login and resources are now being managed by something quite new, and apparently untested with at least your password database, if not the content of your various memberships and virtual machines. 

Most people active in IT operations management would not want to characterise this as a lifecycle opportunity. That particular field of business is particularly big on control and forward planning, which are somewhat at odds with the idea of giant cloud suppliers changing environments around without warning. When you and 100 million other users are suddenly switched to an unfamiliar system, the behaviour you have to adopt comes not from the cloud vocabulary, but rather from the British government: we’re talking about cyber-resilience. 

If that sounds like a buzzword, it sort of is. Cyber-resilience is a new philosophy, established more in the UK than the US, which encourages you to anticipate the problem of increasingly unreliable cloud services. It’s not a question of what plan B might look like: it is, rather, what you can say about plan Z. And that’s sound sense, because finding your main cloud supplier has changed software stack could be as disastrous for your business as a ransomware attack. It can also mark a very sharp lifecycle judgement, because your duty isn’t to meekly follow your provider’s software roadmap: it’s to make sure that a rational spread of cloud services, and a minimalist and functionally driven approach to your own systems designs, gives you the widest possible range of workable, reachable, high-performance assets. 

Don’t panic!

If you’re already invested in cloud infrastructure, this talk might seem fanciful; in reality, few businesses experience the full force of all these different scenarios. The biggest difficulties with the cloud usually involve remembering where you left all your experiments, who has copies of which data sets, and how to identify your data once it skips off to the dark web. The dominant mode here is all about things that live on too long past their rightful end, and that’s slightly more manageable than the abrupt cessations of access or service we’ve been discussing.

Even so, it’s important to carry out the thought experiments, and to recognise that lifecycles can be chaotic things that require a proactive mindset. One could even say that the lifecycle of the “lifecycle” – in the sense of a predictable, manageable process – is coming to an end, as the new era of resilience dawns.

Partnerships key for public cloud vendors to succeed in IoT analytics, says ABI Research

The hyperscale cloud providers are looking at Internet of Things (IoT) offerings and connectivity amid a swath of emerging technologies – and according to a new note from ABI Research, cloud suppliers will grow their share of IoT data and analytics management revenues from $6 billion (£4.6bn) to $56bn (£43bn) in the next six years.

The way to do this, the analyst firm notes, is through partnerships. As ABI sees it, public cloud vendor revenues, while impressive, still come primarily through streaming, storage, and data orchestration. Analytics services across cloud vendors, however, are less differentiated – and therefore the need for collaboration is key for now.

One area in which public clouds are doing it for themselves is through streaming. ABI said this was the one analytics technology that all cloud vendors were building into their solution portfolios; Amazon Web Services (AWS), Microsoft, Google, IBM and Oracle all touting proprietary offerings while Cloudera, Teradata et al were building solutions leveraging open source technology.

Ultimately, a lot of strategy right now is focused on co-opetition in the IoT space. AWS and Azure, for instance, have partnered with Seeq for its advanced analytics capabilities, while Oracle, Cisco, and Huawei are expanding their edge portfolio.

“The overall approach shown by cloud suppliers in their analytics services reflects the dilemma they face in the complex IoT partnership ecosystem,” said Kateryna Dubrova, ABI research analyst. “Effectively, do they rely on partners for analytics services, or do they build analytics services that compete with them?

“Ultimately, businesses are moving to an analytics-driven business model which will require both infrastructure and services for continuous intelligence,” Dubrova added. “Cloud vendor strategies need to align with this reality to take advantage of analytics value and revenues that will transition to predictive and prescriptive solutions.”

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Don’t forget to budget for business objectives to gain digital transformation ROI

Digital transformation is hugely important and extremely difficult. No matter what form an organisation’s transformation takes, it’s bound to introduce new and unanticipated challenges and costs even as it leads to positive long-term outcomes.

While increased challenges and costs are a normal part of digital transformation, they can trigger C-suite leaders to recalibrate their thinking of transformation initiatives and ask to see immediate proof of ROI. When this question inevitably comes up, leaders tend to look for obvious ways to deliver a positive ROI no matter how early in the transformation process they may be.

Too often, the “obvious” solution is to reduce staff whose work is scheduled to be made redundant by new digital processes. In reality, though, such a simplistic solution to the complex problem of calculating the ROI of something as complex as a digital transformation rarely works. In fact, in our experience, immediate downsizing of experienced staff is one of the biggest possible ROI killers in digital transformation initiatives. 

Here’s a look at why, and what organisations can do to realise a sustainable and positive ROI.

Why downsizing tanks the ROI of digital transformation

The simple reason downsizing ends up costing more money than a company will save is that it causes an immediate and dramatic loss of institutional knowledge. We tend to underestimate the value of institutional knowledge, mostly because it’s not often discussed and it’s nearly impossible to quantify. However, underestimating its value can prove expensive in short order.

What usually happens is that, when transformation initiatives aim to digitise processes, internal leaders assume they no longer need employees who used to handle those processes manually. These people are downsized. Short-term ROI numbers look amazing: the savings resulting from a change in headcount makes the digital transformation initiative look like an immediate success.

In reality, though, what typically happens is that, shortly after downsizing or right-sizing a particular team, the organisation realises it still needs certain key skills and that those skills were directly provided by the people who were let go. If the organisation is lucky, it’s able to rehire these people – as contractors – at a significant premium. If not, the downsized workers aren’t interested in returning and the organisation ends up paying their old salary (or more) for a less-experienced person to fill the role.

All told, we usually see it as 30% to 50% less expensive to maintain existing staffing levels during digital transformation initiatives than to develop new employees. Let’s take a look at why.

The ROI-positive alternative to downsizing

A more cost-effective alternative to downsizing current staff following the engagement of a digital transformation initiative is to retain and reskill your best employees. While you may not need all of the skills you have on staff today, it’s rarely wise to let that talent go when you don’t yet know what the final state of your organisation will be post transformation. 

We are constantly amazed at how adaptive teams are to new challenges and opportunities when given the chance to make meaningful contributions in new areas of the business – and they do so with a base of institutional knowledge that can’t easily be recreated.

What’s more, when you maintain your existing workforce, the only cost you incur is that of retraining. You won’t be training for corporate, culture, or industry knowledge, as you would with a new employee. Once your existing employees learn the skills necessary to do the work your organisation now needs, they’ll be able to execute more efficiently than new employees would thanks to their deep institutional knowledge.

Today, with the presence of employer review sites like Glassdoor, it’s important to remember that your current and former employees have a voice and that voice can and will impact your reputation. Get enough negative reviews about how you handled the execution of a strategic initiative, and you could find yourself struggling to recruit the talent you need to get your new digital processes off the ground. This is an all-too-common situation where nobody wins.

ROI-positive digital transformation demands a big-picture view

Even in the best of times, calculating the ROI of a digital transformation initiative can be difficult. The amount of change introduced into a business during these initiatives is substantial. When the alternative to transformation is risking your relevance with customers, partners, and employees, taking the time to invest in the upfront work and the complex management needed to successfully execute the transformation will be worth its weight in gold as the business executes in new ways.

While the most successful digital transformation initiatives define goals from the beginning, many initiatives launch without any clear, measurable goals. If this describes your organisation, take heart: it’s not too late to calculate ROI. Keep in mind, though, that to do so in a way that accurately reflects your financial reality for the long term, you’ll have to look beyond the simplistic short-term measure of cutting costs by downsizing your staff.

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