Private Blockchain for Telecom?

Private blockchain might seem a non sequitur. After all, the whole foundation of blockchain is its distributed ledger. Private blockchain has a single entity as the keeper of the register. 

But that private aspect might be attractive to some connectivity providers, as a means of supporting transactions for its own business partners and customers. By definition, transactions can be a revenue driver only when the blockchain provider can impose a transaction cost. 

A private blockchain provides some advantages such as processing speed and transaction cost, many argue.  Perhaps private blockchain makes more sense for relatively closed ecosystems, while public blockchain is better suited for very loosely-coupled ecosystems. 

source: 101 Blockchains  

Blockchain has the potential to be for connectivity provider “value” what the Internet has been for “information.” A loosely-coupled system can innovate much faster, add partners with little friction and reduce costs and time to market. 

Think of the analogy of a marketplace or exchange: to the extent blockchain verifies identity and secures transactions, it facilitates any-to-any transactions. 

source: Deloitte 

To the extent that blockchain lowers transaction costs, it enables ecosystems to function with less friction. To that same extent, it might allow connectivity providers to construct platform business models, where revenue is generated in some way without direct payment of recurring subscription fees. 

The obvious example is a revenue model where transaction fees are the driver, as would be the case for e-commerce sites. 

source: Infosys 

"Dumb Pipe" is an "Every Industry" Issue

Commoditization is about as fundamental a process as exists in virtually every industry, which is why the search for differentiation in every industry is so feverish. One might say the same about the search for new value creation that drives much differentiation. 

One of the connectivity industry’s responses to deregulation and privatization that became global in the 1980s is “segmentation.” Creating a niche of customers, products or solutions is one way to increase perceived value. 

The computing industry likewise has been driven by Moore’s Law, in particular the increasing power and ever-lower computational cost that have “commoditized” computing.  

Other key trends since the end of the monopoly era are lower prices, lower profit margins, and an  end to industry moats (allowing new competitors to emerge). The computing industry arguably has faced similar developments. Are they all related? 

Almost certainly, one might argue. Commoditization of connectivity and computing tasks--with lower prices and higher capabilities--underpins the modern internet and all next-generation networks (computing or communications). 

Most observers might agree that competition leads to lower retail prices, causes supplier restructuring to lower operating costs and boost marketing. Most might also agree that competition affects value. As core products are commoditized, the search for new forms of value intensifies. 

But commoditization might also be an evergreen problem for the connectivity and computing  industries. Some might argue it is a primary innovative force. Richard Slater, Amido principal consultant, argues that commoditization of IT in fact drives innovation.

Commodity electricity leads to commodity computing (PCs). Commodity computing leads to commodity business computing (data centers).

Commodity data centers lead to commodity cloud delivery (public cloud). Commodity public cloud leads to cloud diversity (public, private, hybrid, multi and poly cloud). 

Commodity cloud diversity leads to commoditized data, he argues. We might suggest that commoditized data leads to commoditized insight, as well. In other words, ample big data combined with ample artificial intelligence to mine that data will lessen the value of insight itself. 

Once every competitor can do so, the value of that insight is itself commoditized. 

“Industry-specific clouds are part of a cyclical pattern of commoditization, and by that, I mean that where there is a need, or demand, for something, typically there will be a move towards commoditizing the answer to that need,” he said. 

Most connectivity and computing firm executives likely would agree, at least privately. No public company executive would be caught saying--in public and on the record--that the existing core business is commoditized and that every succeeding value-creation effort similarly will be commoditized. 

The unspoken but implicit reality is that profit margins also will be commoditized as value is likewise commoditized. This is the reality behind the phrase “dumb pipe.” Observers often warn about commoditization, but it remains an arguably fundamental process.  

What often is not recognized is that the internet is built on dumb pipe. By definition, the value of apps, services and content is structurally separated from the transmission network functions. 

Think of the ecosystem roles played by electricity, computer chips, shipping, roads, water systems or waste management. Then think of all the value created by apps, services, products and content that use electricity, roads, shipping, chips and water. 

The same analogy applies to communications networks. They are essential, but essentially commoditized. We might debate the extent to which that happens in markets with facilities-based competition or wholesale mechanisms; markets with fewer or more platforms. But the commoditized character remains. 

Like it or not, Slater seems to imply, each advance in communications or computing gets commoditized, setting the stage for the next evolution, which in turn is commoditized. That will drive the search for creating new sources of value, endlessly. 

“We have seen the same in IT, to satisfy the need of running a business process we had servers, then virtual machines, then virtual machines in the cloud, then PaaS and then SaaS,” he said. “Industry-specific clouds is about commoditizing a common need, typically this is taking the form of emphasizing specific quality attributes of that cloud.” 

Like it or not, commoditization drives prices and value in every industry. The search for additional value continues precisely for that reason.

European Business Shows Significant Interest in Fixed Wireless

5G fixed wireless does not necessarily have to garner huge market share to be market-changing in the home broadband business. It might be important even in the business segment of the market. In some cases, the amount of market share fixed wireless represents could affect service provider revenue in significant ways.

The real importance might well come in some highly-competitive, large and saturated markets where home broadband is nearly a zero-sum game. In such markets, one supplier’s gain is balanced by another supplier’s loss.

 

And in such markets, a small shift of market share represents significant incremental revenue. In the U.S. market, market share shifts as small as two percent represent $4 billion in annual revenue.

 

New lines of business worth $1 billion annually are a reasonable test of feasibility for many larger tier-one service providers. Any new proposed line of business generating less than $1 billion in annual revenue is too small to bother with. So fixed wireless easily passes the test of value. 

Among the potential new use cases for 5G--not simply a replacement for 4G phone services--is fixed wireless for business or consumer internet access. According to Omdia, perhaps 25 percent of European enterprises with 250 or more employees plan to use fixed wireless access in place of a cabled connection. 

Nearly 35 percent of small or mid-sized businesses with 50 to 249 employees report they will use, or will consider using, fixed wireless.

source: Omdia 

If actual buying is even half that level, it is significant. 

"Telco as a Platform" Will be Tough

Telco as a platform is a buzz phrase that is equally hard to understand.  Analysts at Appledore Research, for example, urge telcos to become platforms. What they mean is that telcos need to disaggregate functions and value, 

In one sense, the notion is that business models can diverge. “We identify five new types of telco business that will result from embracing Telecom as a Platform: The Utility Telco, the Network Sharer, the Neutral Host, the Innovation Telco and the Hyperscale Platform,” Appledore says. 

Generally speaking, the idea is that telco platforms are “open rather than closed,” with roles that can range from simple “bit pipe” operated at low cost to wholesale models to strategies that require creating or owning applications and services of many types. 

Typically, the advice is to use the open approach to build ecosystems of value, as Rakuten is doing. The key observation, however, is that the Rakuten approach involves using the telecom network to support applications and services that Rakuten itself owns, as well as third party apps and services. 

source: STL Partners   

Still, disaggregating the functions necessarily builds on the idea that the transport and access networks themselves are going to become a commodity, as the telco ecosystem mimics the internet itself: any lawful app accessible by any customer or user irrespective of the transmission network. 

By definition, transport becomes a simple “bit pipe” function, largely undifferentiated and no longer providing any gatekeeper role. That does not preclude a telco owning and operating other assets also able to use the bit pipe. Rakuten might be a good present example of that. 

On the other hand, it must also be noted that this requires that telco efforts move beyond the traditional core skill set of building and operating communication networks. Anybody with long roots in the industry knows that is both difficult and rarely successful at scale. 

In fact, virtually all equity analysts consistently recommend against such an approach. Business analysts, on the other hand, routinely argue there is almost no other long-term growth strategy. 

 

source: Appledore Research 

Of course, there are several ways the term “platform” is used. It sometimes is a business model. 

About “40 percent of the world’s top 30 brands are now platform businesses ,” BearingPoint consultants have argued. Platform business models involve making money from transactions that happen on the platform. 

In that sense, eBay is a platform; Amazon is a platform; Apple is a platform; YouTube is a platform. 

But “platform” sometimes is used in the computing industry sense, where the telco network is a foundation for other apps to use. Think of the roles played by Intel, Microsoft Windows, Linux or computers themselves. 

In the computing business, a platform is a set of hardware or software upon which other third-party apps can run. So Windows has always been seen as a platform, as have the Intel line of processors. 

In that sense, the internet is a platform for both communications and applications. But there is a new sense of the term that refers strictly to business model, not computing or communications infrastructure. 

In the internet era a new meaning has emerged. A platform is a business model based on an entity that acts as an exchange, connecting buyers and sellers. 

source: Simon Torrence 

A platform business model essentially involves becoming an exchange or marketplace. A pipe model requires a firm to be a direct supplier of some essential input in the value chain.

A platform functions as a matchmaker, bringing buyers and sellers together, but classically not owning the products sold on the exchange. A pipe business creates and then sells a product directly to customers. Amazon is a platform; telcos and infrastructure suppliers are pipes. 

Amazon is a platform. Etsy is a platform. Uber and Lyft are platforms. Airbnb is a platform. All connect buyers with sellers; sellers with sellers or buyers with buyers. None of those platforms “owns” the assets traded on the exchange. 

It all boils down to “who makes the money” and “how” the money is made. Even when understood as a business-to-business marketplace, a bandwidth exchange, for example, a key principle is that buyer and seller transactions volume is how the platform makes money. 

A true platform in the digital commerce  sense does not own the actual products purchased using the platform, and makes money by a commission or fee for using the platform to complete a transaction. A ridesharing platform does not own the vehicles used by drivers. A short-term lodging platform does not own the rooms and properties available for rental. An e-commerce site does not own the products bought and sold using the platform. 

In that sense, no telco I can think of actually operates as a full platform, yet. Service providers always make money directly from selling services (access and transport). Sometimes they also own apps that run on the network. But few actually operate as actual exchanges, making money from transaction fees. 

If by “platform” one means a business model based on transactions, few telcos will be able to manage the transition. A platform business model essentially involves becoming an exchange or marketplace. A pipe model requires a firm to be a direct supplier of some essential input in the value chain.

A platform functions as a matchmaker, bringing buyers and sellers together, but classically not owning the products sold on the exchange. A pipe business creates and then sells a product directly to customers. Amazon is a platform; telcos and infrastructure suppliers are pipes. 

Platform creation is not especially easy for a connectivity services provider. If you think about every business as either a “pipe” or a “platform,” then most businesses are “pipes.” They create a specific set of products and sell them to customers. That is a classic “one-sided market.”

A bandwidth exchange might be one example of an actual connectivity business platform. The operator of the exchange would federate business access to networks of all sorts, allowing customers to buy and sell use of any of the assets. The exchange could focus on consumers, business-to-business, carrier-to-carrier, app to app; computing as a service or almost any combination of those transactions. 

But the exchange might not actually own any of the underlying networks. By that measure, “becoming a platform” is a tall order.

Prepare for Digital Transformation Disappointment

Prepare for digital transformation disappointment. The investments firms and organizations are rushing to make to “digitally transform” will largely fail, history suggests. For starters, the theory is that whole business processes can be transformed.

But those are the thorniest, toughest problems to solve in the short to medium term, as human organization and habits must change, not simply the computer tools people use. 

Secondly, DX necessarily involves big changes in how things are done, requiring significant application of computing technology. Historically, big information technology projects have  failed about 70 percent of the time.

Finally, understanding how best to use a new technology approach takes some time, as suggested by prior technology paradoxes. 

Many technologists noted the lag of productivity growth in the 1970s and 1980s as computer technology was introduced. In the 1970s and 1980s, business investment in computer technology were increasing by more than 20 percent per year. But productivity growth fell, instead of increasing. 

So the productivity paradox is not new.  Massive investments in technology do not always result in measurable gains. In fact, sometimes negative productivity results. 

Information technology investments did not measurably help improve white collar job productivity for decades in the 1980s and earlier.  In fact, it can be argued that researchers have failed to measure any improvement in productivity. So some might argue nearly all the investment has been wasted.

Some now argue there is a similar lag between the massive introduction of new information technology and measurable productivity results, and that this lag might conceivably take a decade or two decades to emerge. 

The Solow productivity paradox suggests that applied technology can boost--or lower--productivity. Though perhaps shocking, it appears that technology adoption productivity impact can be negative. 

The productivity paradox was what we began to call it. In fact, investing in more information technology has often and consistently failed to boost productivity. Others would argue the gains are there; just hard to measure. Still, it is hard to claim improvement when we cannot measure it. 

Most of us are hopeful about the value of internet of things. But productivity always is hard to measure, and is harder when many inputs change simultaneously. Consider the impact of electricity on agricultural productivity.

“While initial adoption offered direct benefits from 1915 to 1930, productivity grew at a faster rate beginning in 1935, as electricity, along with other inputs in the economy such as the personal automobile, enabled new, more efficient and effective ways of working,” the National Bureau of Economic Research says.  

There are at least two big problems with the “electricity caused productivity   to rise” argument. The first is that other inputs also changed, so we cannot isolate any specific driver. Note that the automobile, also generally considered a general-purpose technology, also was introduced at the same time.

Since 1970, global productivity growth has slowed, despite an increasingly application of technology in the economy overall, starting especially in the 1980s. “From 1978 through 1982 U.S. manufacturing productivity was essentially flat,” said Wickham Skinner, writing in the Harvard Business Review. 

Skinner argues that there is a “40 40 20” rule where it comes to measurable IT investment benefits. Roughly 40 percent of any manufacturing-based competitive advantage derives from long-term changes in manufacturing structure (decisions about the number, size, location, and capacity of facilities) and basic approaches in materials and workforce management.

Another 40 percent of improvement comes from major changes in equipment and process technology.

The final 20 percent of gain is produced by conventional approaches to productivity improvement (substitute capital for labor).

Cloud computing also is viewed as something of a disappointment by C suite executives, as important as it is.  

 

A corollary: has information technology boosted living standards? Not so much,  some say.

By the late 1990s, increased computing power combined with the Internet to create a new period of productivity growth that seemed more durable. By 2004, productivity growth had slowed again to its earlier lethargic pace. 

Today, despite very real advances in processing speed, broadband penetration, artificial intelligence and other things, we seem to be in the midst of a second productivity paradox in which we see digital technology everywhere except in the economic statistics.

Despite the promise of big data, industrial enterprises are struggling to maximize its value.  A survey conducted by IDG showed that “extracting business value from that data is the biggest challenge the Industrial IoT presents.”

Why? Abundant data by itself solves nothing, says Jeremiah Stone, GM of Asset Performance Management at GE Digital.

Its unstructured nature, sheer volume, and variety exceed human capacity and traditional tools to organize it efficiently and at a cost which supports return on investment requirements, he argues.

At least so far, firms  "rarely" have had clear success with big data or artificial intelligence projects. "Only 15 percent of surveyed businesses report deploying big data projects to production,” says IDC analyst Merv Adrian.

So we might as well be prepared for a similar wave of disappointment over digital transformation. The payoff might be a decade or more into the future, for firms investing now.

OECD Service Provider Revenue is Flat Through 2018

In a nutshell, here is the business model problem for telecom service providers in the Economic Cooperation and Development countries: flat or declining revenue. 

source: OECD

Internet of Things Devices in OECD Countries

One cannot easily correlate connected sensors with consumer broadband, as connected sensor devices are sometimes used by consumers, but also by enterprises and other organizations. Still, in some Organization for Economic Cooperation and Development countries there are as many as 40 machine-to-machine connections per 100 persons. 

The OECD average is about 27 M2M connections per 100 persons. 

source: OECD