Tuesday, September 19, 2023

Connectivity Business is More Agile Than We Sometimes Think

If you have been in the connectivity services business long enough, you are aware of the frustrating inability to grow profit margins for the core business or sustain average revenue per unit sold. 


Industry

Gross profit margin

Net profit margin

Software

70%

30%

Semiconductors

60%

25%

Data centers

55%

20%

Telecom service providers

45%

15%

Automobiles

30%

10%

Retail

25%

5%

Consumer staples

20%

5%

Healthcare

15%

10%

Utilities

10%

5%


You have learned to navigate a business whose primary profit generators and business context have changed dramatically over the last quarter century.  By any estimate, global industry revenue sources have changed drastically over the last two decades or so.  


Revenue source

2000

2023

Mobile services

20%

60%

Fixed services

80%

40%

Voice

60%

20%

Home broadband

10%

40%

Consumer revenues

80%

70%

Business revenues

20%

30%


So have profit drivers. Mobility now represents something on the order of 70 percent of all industry profits, while all fixed services together represent about 30 percent. Where voice once represented half of profits in 2000, in 2023 voice represents perhaps 10 percent of profits. 


Consumer services still drive a majority of profits, but there has been a shift to business drivers since 2000. 


Profit source

2000

2023

Mobile services

30%

70%

Fixed services

70%

30%

Voice

50%

10%

Home broadband

20%

60%

Consumer revenues

80%

60%

Business revenues

20%

40%


The other big change has been the evolution of revenue sources since the internet era began, about the mid-1990s, most notably the emergence of home broadband as a consumer revenue driver and business revenues as a bigger source of total revenues. 


In substantial part, business revenues have grown because of the importance of mobility and remote computing, cloud computing and internet access and transport. 


Revenue source

1990

2023

Mobile services

0%

60%

Fixed services

100%

40%

Voice

70%

20%

Home broadband

0%

40%

Consumer revenues

90%

70%

Business revenues

10%

30%


At the same time, network architectures for most networks have changed as well. The single-purpose and application-specific networks (broadcast TV, broadcast radio, cable TV, mobile voice, fixed voice have given way to multimedia (text, image, video) networks. 


That, in turn, has enabled a huge transformation of business models, revenue sources and use cases. Underlying the internet service provider angst about data consumption growth is the shift of entertainment video from linear to on-demand, for example. 


But application-agnostic networks also tend to favor symmetrical bandwidth, as demand sources and sinks become more dynamic. Content delivery networks could assume that almost all bandwidth was in the downstream direction, as content consumers were on one end, content deliverers on the other end. 


Multimedia networks can make fewer such assumptions. Voice traffic is mostly assumed to be symmetrical while much business “data traffic” can take many patterns. 


Among the other key changes, movement of data between data centers and within data centers now dominates most core network traffic, even when all that activity supports data demand by end users at the network edges. 


People might complain that connectivity services are not "agile" enough, but the charge is only partly correct. Perhaps few industries have experienced as much fundamental change in products and revenue drivers over the past couple of decades.


The industry might not be especially "culturally agile" but it has successfully become product lifecycle agile.


Monday, September 18, 2023

“Prime Vision” Applies AI to Thursday Night Football


Prime Vision, an AI-enhanced viewing experience for Amazon Prime’s Thursday Night Football broadcasts, provides a good example of how AI models can, and will be used, to enhance a product, providing indirect monetization in the form of higher subscriptions and lower churn, rather than in terms of direct monetization for use of the feature. 


Prime Vision is an AI-powered streaming experience for Amazon Prime Video customers using computer vision and machine learning to provide viewers with real-time insights and analysis during live sports broadcasts.


Prime Targets identifies the receiver who is most likely to be open on a passing play, using AI to track the movement of the quarterback, receivers, and defenders to calculate the probability of each receiver being open.


The Fourth-Down Decision Guide uses AI to analyze the game situation and calculate the probability of success for both a touchdown and a punt.


Defensive Alerts identifies players on defense who are most likely to rush the quarterback.


Key Plays identifies the plays that had a significant impact on the outcome.


Rapid Recap provides viewers with a quick summary of the game's key plays in a short video.


Friday, September 15, 2023

ISP Calls for Broadband Infra Payments? Hyperscalers Already Pay for Traffic Asymmetries

Virtually lost in all the discussion of payments by a few hyperscale app providers to ISPs based on asymmetrical traffic flows is the reality that ISPs and content domains already have negotiated interconnection agreements that account for such asymmetrical traffic flows.


Though the actual details of interconnection agreements between some internet domains with others are not generally easy to estimate, observers believe most hyperscale app providers already are paying internet service provider domains for asymmetrical traffic flows. 


Company

Estimated Yearly Interconnection Payments (US$)

Meta

300 million to 800 million

Alphabet

200 million to 700 million

Netflix

100 million to 300 million

Amazon

75 million to 200 million

Microsoft

50 million to 100 milliion

Apple

25 million


So when ISPs say they need such payments, what they really are arguing is that they should be paid more. 


Business relationships in any value chain are subject to market forces, of course. There is no ethical reason why commercial agreements between entities “must” take any particular magnitude. 


But it is fairly clear that the present ISP desire for support of their home broadband and mobile infrastructures is a case of “wanting more money” for traffic exchanges that already have negotiated agreements in place.


Name One Major IT Trend that Has Not Altered Investment Priorities

A survey of 500 information technology professionals sponsored by LogicMonitor shows at least half of those respondents believe their infrastructure is not equipped to handle increased artificial intelligence. 


And information technology analysts believe the amount of new investment to support AI could be substantial. 


A study by McKinsey Global Institute estimated that businesses would need to invest $3.5 trillion in AI by 2030 to realize AI benefits.


A study by the Boston Consulting Group suggested  that businesses would need to invest $1.7 trillion in AI by 2025 to realize AI benefits.


A study by PwC suggested that businesses would need to invest $2.2 trillion in AI by 2030 to retrain and reskill workers who are displaced by AI.


Of course, IT professionals often say the existing infra is not prepared for the platforms and functions, when a new technology emerges. In many cases, preparedness is an issue precisely because the capabilities and skills needed to introduce a new platform do not yet exist.  Many past examples include:


Electronic data interchange (EDI)

Enterprise resource planning (ERP)

Customer relationship management (CRM)

Supply chain management (SCM)

Content management systems (CMS)

Virtual private networks (VPNs)

Mobile computing

Cloud gaming

Telehealth

Robotic process automation (RPA). 


And there will always seem to be some new thing that IT professionals report they are not prepared to handle with the existing infra. CIO magazine’s annual surveys have tended to show new concerns every year, for example. 


Innovation

Study

Date of Publication

Cloud computing

The State of the CIO 2011

2011

Bring your own device (BYOD)

The State of the CIO 2014

2014

Social media

The State of the CIO 2015

2015

Big data

The State of the CIO 2016

2016

The Internet of Things (IoT)

The State of the CIO 2017

2017


Among the oft-cited concerns:


  • Lack of skilled talent. AI is a complex technology that requires specialized skills and knowledge. Many organizations do not have the in-house expertise to develop and deploy AI solutions.

  • Data quality and availability. AI algorithms need to be trained on large amounts of high-quality data. However, many organizations lack the necessary data or the resources to collect and clean it.

  • Cost. AI can be a costly investment, especially for small and medium-sized businesses. The cost of developing, deploying, and maintaining AI solutions can be prohibitive for some organizations.

  • Regulatory compliance. AI raises a number of regulatory concerns, such as data privacy and bias. Organizations need to ensure that their AI solutions comply with all applicable regulations.

  • Security risks. AI systems can be vulnerable to cyberattacks. Organizations need to take steps to protect their AI systems from unauthorized access and tampering.

  • Ethical concerns. AI raises a number of ethical concerns, such as bias and discrimination. Organizations need to develop ethical guidelines for the use of AI.


IT professionals believe that they need to make the following investments to adapt their infrastructures for AI, aside from acquiring new AI skills and continuing to streamline code development processes::


  • Data infrastructure. AI algorithms need to be trained on large amounts of data. Organizations need to invest in data infrastructure that can store and process this data efficiently.

  • Compute infrastructure. AI algorithms can be computationally demanding. Organizations need to invest in compute infrastructure that can run these algorithms quickly and efficiently.

  • Networking infrastructure. AI applications often need to access and process data from multiple sources. Organizations need to invest in networking infrastructure that can support this connectivity.

  • Security infrastructure. AI systems can be vulnerable to cyberattacks. Organizations need to invest in security infrastructure that can protect their AI systems from unauthorized access and tampering.

Directv-Dish Merger Fails

Directv’’s termination of its deal to merge with EchoStar, apparently because EchoStar bondholders did not approve, means EchoStar continue...