Who’s there?: The rise of multienterprise business networks

Not everything about business is technology, but every business has to leverage technology everywhere

Over the last few years, executives discussed redesigning their businesses for the safe, secure and accurate flow of actionable data with as little human involvement and oversight as possible, a change Google describes as removing the “human toil” from economic activity. Business leaders called this process optimization, a process often resisted by employees which in turn slows an organization’s digital efforts. Organizations big and small have been forced to embrace a cloud- and digital-first posture to maintain business continuity and participate in everyday economic activity. In short, these efforts are being done to maintain relevance. As a result, nontechnology-savvy executives and employees will exit the workforce exponentially over the next five years.     

In this transformative period, future managers train now at new entry-level IT jobs, even as IT services vendors and other players in the technology ecosystem complain about a shortage of STEM talent in the hiring markets. The talent that does come on in new roles spread across a digitally savvy enterprise understands application interfaces, which align human interaction with technology and data platforms. By entering the business in this capacity, the incoming talent gains experience across the various elements of the business operation that executive managers require while also ensuring they are fully digitally versed for the Business of One.

Adding further complexity has been the disaggregation of business functions or value among different business entities. In technology we see this as the IP-centric elements of a business being split away from the labor, or task-centric functions. Looking at semiconductors, for example, some on Wall Street are calling for Intel to be split between the IP-laden aspect of chip design and the capital-intensive aspect of fabrication plants capable of manufacturing those designs reliably at scale. They are two businesses with entirely different rhythms and economic drivers, yet neither can thrive without the other.

The work-around to this business disaggregation taking place is to establish a network of businesses with complementary value propositions. This network is increasingly being called the multienterprise business network (MEBN). Many technology-centric firms describe this as their platform. But platforms are a stage on which something is performed, and that performance is the outcome enabled by multiple different parties. As such, viewing MEBNs from solely a technology-centric view can miss the point entirely.

As the Business of One evolves, legacy technology vendors selling on technical merits, or speeds and feeds, and selling just to IT face tremendous market pressures to pivot to selling business outcomes. Today’s reality requires understanding customers’ busines objectives and speaking directly to business decision makers.

For Technology Business Research’s (TBR) Digital Practice, this necessitates taking our core value proposition of vendor-centric business analysis of technology companies across a standard technology business value chain and combining it with additional considerations about industries and the operating best practices of business ecosystems that tie back to the specific use case and the personas integral to that use case. After having established those core frameworks, the analysis then ties back to time horizon and MEBN participant. In short, what is in it for the MEBN participant at what stage (commonly referred to as Horizon 1, 2 and 3 in today’s frameworks) in the MEBN product road map.

To illustrate the intent here, consider the creation of an MEBN for the utilization, storage and maintenance of autonomous vehicles. Having autonomous vehicles moving about a defined geography would clearly be the Horizon 3 aspiration, which is nowhere near commercial reality today.

Horizon 1 would be delivering an immediate level of business value creation to entice the participants necessary for that Horizon 3 aspiration. For example, gas stations, mechanics and parking garages, at a minimum, will need to be recruited into the MEBN for autonomous vehicles. Later, additional services for the auto owner could be added such as online ordering with brick-and-mortar pickup across various nontech-centric small businesses providing localized services. Creating a buyer network in Horizon 1 for today’s cars and owners has to provide sufficient business value for enrolling participants.

The capital investment in the technology infrastructure likely must come from the Horizon 3 business benefactor and be viewed as a long-term investment to facilitate the recruitment of the necessary member participants. In the end, those autonomous vehicles will need the fueling, maintenance and parking services to function and the adjacent human services of pickup and delivery to increase their utilization rates beyond a source of human transport. Yes, it requires a technology value chain as its backbone, but nontechnology participants are just as necessary to flesh it out into a thriving MEBN of buyers and sellers who may not even concern themselves with the technology underpinnings at all.

More colloquially, few singer-songwriters would have the capital necessary to build the technology assets for downloading music over the internet. But once Apple took a long view to their investment posture, it was able to build out a robust MEBN that profited many artists, disrupted traditional nontechnology businesses, and delivered value to many customers in the form of the iTunes platform, which itself has been disrupted by streaming services such as Spotify and Pandora.

TBR’s Digital Practice remit is to take its core value proposition of discrete company business model analysis and apply it to the MEBNs by isolating the different components through a series of frameworks. In doing this, we will then be able to assess the financial impact for the different member participants across the near-term, mid-term and long-term horizons.

Industries have different automation leverage points, enabling different personas; inexpensive tech makes possible a myriad use cases

Compute ubiquity has been well documented. The multimillion-dollar supercomputer performance of yesteryear is now contained in smartphones. The first IBM PC chip, the 8088, is now matched by CPUs the size of a grain of sand that cost $0.10 to produce. Historically, the heavily regulated industries of financial services and healthcare were early technology adopters, given the risk exposure of noncompliance with government regulation. As the cost of compute was brought down to incredibly inexpensive price points, compute expanded from those back-office functions into front offices. Today, we are at a point where, as on EY executive summed it up in analyst interaction when peppered with multiple questions: “We can do whatever you want; you just have to make up your minds.”

Making up our minds translates into codification of standard business results to digitize activity in a consistent way, and this sits at the heart of multiple game-changing technologies including AI, machine learning and blockchain. And these are horizontal technological capabilities that cascade through a variety of industries. Retail, once cost-conscious, was one of the later industries to adopt technology. Amazon, as we know, has disrupted this sector at the detriment of many high-profile brick-and-mortar brands of yesteryear.

TBR will use this construct to incubate standard coverage of markets, facilitating a way to bring analysis of that market to a vendor-centric view. TBR’s Digital Transformation research portfolio will serve as the vehicle to introduce these frameworks. The inaugural Digital Transformation Blockchain Market Landscape is set to publish in April 2021 and Digital Transformation IIoT Market Landscape will be published in June 2021. These reports will follow a semiannual publication cadence.

IBM-Red Hat economic implications: Is disruptive state the new steady state?

IBM’s assets combined with Red Hat’s business monetization models are a good bet to provide a scaled, secure and trusted platform, if IBM can adjust internally and convince its clients to do the same.

The market splash

When a blue-chip bellwether company buys a firm that broke the lock on proprietary operating system dominance something big is afoot. IBM’s market luster has faded somewhat, and the financial sharks are circling with calls for CEO Virginia Rometty’s head and for IBM to be broken up and sold off to warm the cockles of institutional investors’ hearts, who cannot see the market implications beyond 90 days. IBM has been here before, in the late 1980s when Digital Equipment Corporation had a higher market valuation than IBM based on a single architecture and operating system as opposed to IBM’s six or so disparate computing architectures and operating systems. IBM’s first effort to course correct with the 9370 minicomputer was essentially dead on arrival, but its second shot, the AS/400, lives on in server closets to this day as the iSeries.

But this new challenge is different, and IBM knows it. Its executives talk about how “the axis has flipped.” At TBR, we talk of the Business of One as others label this moment as Industrial 4.0. The core revolves around cheap compute. Moore’s law has been the fundamental economic axiom driving the rapid rise and fall of technology vendors for at least 60 years, though some say its effects are waning. Despite the undeniable shift, innovations around cheaper and cheaper compute, storage and networking sources will continue in ways fascinating to fathom, especially as quantum computing nears commercial viability. At once scale means nothing and everything in this Business of One era.

Scale: Vital and trivial at the same time

Scale means nothing amid the development of new ideas.

Scale means everything when it comes time to ensure business commerce can leverage the new ideas in ways that protect brand, customer privacy and regulatory compliance.

IBM understands this as well as, if not better than, any of its competitors. The challenge for IBM is the same one faced by Satya Nadella when he took over Microsoft: how to change a deeply ingrained and highly successful corporate culture to align to these new, seemingly contradictory market realities. A lot of economists get lost in the buzz of hypergrowth for scaled public cloud revenue. Public cloud, at its core, is nothing but a commodity utility offering. It has never been the IBM play, and it ought not to become its play now. The company’s domain is enterprise IT, not easy storage of family photos or digital music. Amazon, Azure and Google (“Amazurgle”), and emerging regional rivals, can meet these demands, especially when such companies derive the bulk of their revenue elsewhere through advertising or e-commerce.

What IBM has to learn is how to compensate the management layers on companywide execution rather than on siloed execution. You cannot hold firm on razor sales when to lose that sale means risking a lifetime of highly profitable razor blade sales.

The technology assets IBM stands to gain in the acquisition are well documented, particularly in a recent commentary by TBR Senior Analyst Cassandra Mooshian. But TBR has covered IBM and Red Hat for years, and after one particular Red Hat analyst day, TBR summed up Red Hat CEO Jim Whitehurst’s business strategy as “deja vu all over again.” Essentially Red Hat aimed, and is still aiming, to do in the PaaS layer what it did in the enterprise operating system layer. Red Hat’s success with this strategy would prove a boon to IBM, and IBM’s long working history with open-source communities should allay many (but obviously not all) of the concerns within those communities around the business following the proposed acquisition.

Postcards from the edge: Complexity is here — wish it were not

“Analog dollars to digital pennies” is a phrase used to discuss the continued compression on technology price points as Moore’s Law economics, coupled with continued IP abstraction, creates economic trigger events aimed squarely at legacy business model best practices. Recently, I attended analyst events in New York City — one sponsored by Lenovo and one by Canonical — that outline these economic trigger events, albeit from different sides of the same coin.

Canonical CEO Mark Shuttleworth used the term “economic trigger events” often in his opening remarks. The idea is that technologies and new price points create trigger events that result in new economic fundamentals where some participants will be disruptors and some will be disrupted.

The rise in the hype cycle around edge computing as it joins forces with cloud, artificial intelligence (AI)/machine learning, and Internet of Things (IoT) creates a veritable Gatling gun of economic trigger events. These events accelerate business model disruption as we pivot to the Business of One era.

The disruption sits atop the continued economic pressure from commoditized hardware. What’s behind it all is that while infrastructure is valuable, it is not valued. In short, the margin moves out of infrastructure and into the business outcome. Technology enablement is less constrained by affordability and more by determining what business value can be derived from the application or use case.

Rather than being the lead decision in business investment decision making, infrastructure acquisition becomes the derived decision. The service attach rate or services drag becomes the fuzzy guide point for new inventions and new business models. Broad, ubiquitous ecosystems become imperative to generating sufficient margin in the digital penny world to justify the ongoing development, monitoring, and maintenance of secure flexible infrastructures that won’t break and will keep data secure and private.

For Canonical, this means focusing on the connection between operating system and cloud control planes to ensure a single code set operates silicon as large as high-performance computers (HPCs) and as small as single-purpose IoT devices. Compute infrastructure is assumed to work, until it breaks, and then users realize just how valuable that hidden infrastructure provisioning is.

As Canonical is hardening the abstraction layer to ensure seamless interoperability, Lenovo (and many other hardware manufacturers) create purpose-built appliances optimized for edge workloads. In some instances, these will be small appliances simply capturing data and routing it back to clouds for ingestion into massive analytics engines. In other situations, it will be very-high-performance compute engines with GPU accelerators in simple, easy-to-operate form factors where AI inference in real time has to be performed at the edge. Here again, the assumption will be that the edge appliance can operate (in a retail convenience store, for example) without the need for any technically savvy personnel to monitor, manage or provision the device on-site.

Look for more detailed special reports from TBR on the Lenovo and Canonical industry events in the next few weeks.


EY, SAP and Microsoft: A powerful triad for the Business of One era

Attending several EY analyst events in the past month has been a real eye-opener to the changing dynamics of a company that has traditionally been viewed as an advisory-led firm with strong credentials in the tax, audit and advisory domains, yet until recently offered precious little in the way of IT-centric services. This is not your father’s EY, as the company has been investing heavily in partnerships and in automating its IP in ways that radically reduce “run the business” IT costs while continuing to excel at “transform the business” advisory engagements.

A large part of EY’s accelerating performance can be laid at the feet of its partner ecosystem where the company has deepened partnerships with technology providers such as SAP and Microsoft, whose own services firms lack permission to play in the C-Suite or are just taxed based on current workloads and the industrywide skills shortage.

In short, the “axis has flipped” on what works with respect to ecosystem participation in the Business of One era, and this partnership triad appears to have many of the emerging bases covered. Figure 1 outlines the way in which TBR segments services portfolio options in one of its core market landscape constructs. TBR segments services into several different components, and it is through this kind of analysis that the power of the EY, Microsoft and SAP relationships truly come to life.

At the top of the triangle (A) sits the advisory-led services, where EY has competed successfully for decades. Here is where board and C-Suite objectives get clarified and then codified for execution by the IT practitioners in the front-office (C), middle-office (T) and back-office (B) layers. While both SAP and Microsoft have some advisory offerings, EY has the account credibility and existing relationships with the C-Suite, especially with the CFO through the company’s audit and tax services. In this way, EY can pull SAP and Microsoft into accounts where they have previously not had much visibility.

The front- and back-office technology segments are where Microsoft and SAP, respectively, have strong brand credentials. Microsoft has essentially owned the business productivity space for decades through Microsoft Office and has done an excellent job pivoting that business over from license to subscription software in the move to Office 365. SAP, likewise, has been a long-term premier provider of the core back-office systems of record now being migrated to the cloud as adoption there accelerates.

Lastly, and most importantly, is the middle-office integration layer, where the power of the partnership will bear the most aggregate benefit, as each participant has valuable domain knowledge to contribute. SAP has tight rules and policy guidelines by industry, Microsoft has the platform and tool sets to rival any competing cloud platform through Azure, and EY has the skills in translating business objectives into IT policies and rules for process optimization. The end result for enterprise customers is a faster, more economical and more agile use of IT for digital transformation.

The assessment by no means says that collectively EY, Microsoft and SAP will become Business of One de facto standards, but it does suggest these three working together in major accounts will give many of their competitors pause.

Intelligent use of artificial intelligence: A tech provider’s guide to automation success

The enterprise automation market opportunity is nearing a tipping point where proof-of-concept tests using adaptive, emerging technologies are hardening and scaling. The gap increasingly widens between leaders and laggards, with leaders now moving from obvious cost take out initiatives into creative destruction pilots for new revenue sources in adjacent markets. Amazon (Nasdaq: AMZN), for example, has been throwing knockout punches against traditional brick-and-mortar firms and is now taking aim at legacy grocers with its Whole Foods acquisition, which moves the company into adjacent markets. As little as one-tenth of data center personnel are required to monitor and maintain enterprise compute instances as more and more compute provisioning becomes abstracted and automated to create building blocks on the way to utility computing, a concept first raised before the turn of the century. Like it or not, we are on the way to Skynet.

By Executive Analysts Geoff Woollacott and Stephen Davidson


The Business of One era requires new business planning and management practices

A new generation of incredibly powerful, flexible and responsive businesses is reshaping markets. Their ability to serve single customers at scale is what TBR terms the “Business of One.” The environmental forces triggering this shift are vast. Information velocity accelerates globally; digital information expands exponentially; competitive advantage windows compress rapidly; task work automates; acute labor shortages persist in new skill work; and new business risks pressure public policy. In the aggregate this confluence of technology-enabled business factors disrupts traditional business, education and public policy best practices. Technology vendor and enterprise business models must evolve, as evidenced by the market capitalizations of relatively new businesses such as Facebook, Amazon, Apple, Netflix and Google (FAANG) while more established firms have languished. In the Business of One era, success will rest upon rapid iterations rather than deliberate cadences, ecosystem participation for assembling complementary assets rather than amassing scale advantage, subscription monetization cycles rather than transactional product sales, and highly automated processes and customer access points rather than labor-intensive task work and repetitive, overlapping paper trails to establish commercial trust.