понедельник, 31 марта 2025 г.

The Top Indicators of Marketing Vitality

 


What are the top drivers of marketing vitality—success against key performance indicators—in 2025?

To find out, The CMO Council analyzed data from a wide range of third-party sources, including proprietary insights from quantitative surveys and qualitative interviews.

An infographic (below) covers highlights from the research.

Specifically, it looks at the top organizational behaviors that the researchers found are associated with marketing vitality across five areas: marketing mix and spend, organizational dynamics, customer affinity, market outlook, and technology.


https://bit.ly/4hSbWyD

Building a Strong LinkedIn Profile: The Basics

 


A good LinkedIn profile is key to forging professional connections and capitalizing on opportunities.

So, what makes for a good profile?

An infographic (below) from Media Update covers the basics of building a strong LinkedIn profile.

It provides advice on what to consider across six key areas: the photo, headline, About section, Featured Content section, Activity section, and Experience section.


https://tinyurl.com/2su6u5mh

How to manage cash

 


Learn to manage your cash.
Because revenue growth isn't enough.
And paper profit can't fund growth.

Most CEOs think if sales are up and EBITDA looks good, they’re in the clear.

But they forget one thing:

You can’t spend EBITDA.
You spend cash.

And if you’re not managing it strategically, here’s what you’re risking:

✕ Missed acquisitions and expansion
✕ Operational breakdowns in a downturn
✕ Poor terms when you actually need capital
✕ Declining valuation and investor trust

What great CEOs understand is this:

Cash isn’t a finance department concern.
It’s a leadership priority.

Here’s how they operate differently:

✓ Optimized capital deployment
✓ Proactive debt and liquidity management
✓ Readiness for strategic moves when timing matters most

If you're making decisions without a clear cash strategy, you're flying blind.


https://tinyurl.com/mr2krwr6

Calculating the ROI of AI strategy

 

Christian Cobb


The hype of AI has led to AI “champions”, AI “task forces”, and AI “working groups” at any given company, but we are seeing organizations pivot from aimless AI tinkering to driving real impact. 

Sam Altman has said we will see a billion dollar company run by one person in our lifetimes. Whether or not we do (I think we will), this hammers home the idea that 1) AI’s flexibility means it can support any part of the business and 2) benchmarks for ROI are going to change radically as AI native systems emerge.

In this blog, we’ll break down how you can calculate the ROI of AI Strategy with a simple, actionable approach to get ahead of the crowd. And how you might maximize that return.

A simple frame for AI ROI to set you up for success

Before diving into the details, let’s establish two things:

  1. The definition of ROI hasn’t changed. You need to get more out than you put in.
  2. We need to develop business cases, as (after all) investment decisions are made by humans. 


That is not new. 
What has changed is the flexibility of the technology we are looking to apply. 

That is, AI can support almost any process, function, business unit, or customer interaction.  We’ve found in the past 2 years that answering the questions of where and how to start are deceptively tricky.

 

To simplify, think of AI ROI in three primary buckets:

  1. Cost Efficiency – Reducing costs, increasing productivity, and getting more out of existing assets.
  2. Revenue Optimization – Enhancing customer lifetime value through upsells, cross-sells, and retention improvements.
  3. New Revenue Streams – Unlocking new products, services, or business models.


These also are not new. Any investment will probably fall into one of these categories. This is the best frame to figure out where to go deeper.




Single use case, or flooded with options? Here’s how to prioritize





Organizations making build or buy decisions typically fall into two camps: either they have one clear AI use case or they’re overwhelmed by too many possibilities. 

If you have a single use case: focus on defining one key KPI that aligns with your strategic objectives. If you’re working on AI-powered customer support, for instance, your KPI might be reduced response time or decreased customer churn. Simplifying your objective helps tell your story to stakeholders and streamline execution.

If you are comparing multiple use cases: use the three ROI buckets (cost efficiency, revenue optimization, new revenue streams) to categorize and compare your use cases, apples to apples. This helps prioritize investments with the highest impact. If you really have a lot of use cases, you can start with a simple 1-5 score in each bucket to prioritize and then go deeper.


Three waves of AI adoption: where are you playing?


AI-driven transformation doesn’t happen all at once. AI adoption will unfold in three waves, much like previous revolutionary technologies such as electricity, digital, or mobile:

  • Wave 1: Time, Cost & Efficiency – applying AI to existing ways of working, focusing on time savings, cost reductions, and efficiency gains
  • Wave 2: Quality & Better Output – leveraging AI for better quality and enhanced outcomes. It’s not just about being faster or cheaper; it’s about delivering superior results and higher standards. 
  • Wave 3: New Systems & Transformation – creating entirely new systems and ways to deliver and capture value, and redefining markets. 


It’s important to understand that success in the first wave doesn’t guarantee success in the third. Businesses must plan their AI strategies with a vision for all three waves, ensuring that investments made today help build towards transformative opportunities tomorrow. We advocate for a portfolio approach: invest across all three waves, with a clear vision for the third wave in mind.



Efforts across all waves can begin now and happen simultaneously


Investment in a given wave will naturally have different impacts on returns.




The Three Waves Framework provides a strategic roadmap for growth, ensuring organizations capitalize on immediate opportunities while building toward transformative, long-term change. Its principles are universal, applying to technology, business models, and industry evolution

Where to find higher AI ROI - stacking AI investments


One of the biggest missed opportunities in AI strategy is failing to connect use cases for systemic returns. Let’s look at an example: let’s say a company implements three AI solutions:

  • AI-powered customer support to reduce response time.
  • AI trend prediction to anticipate market demands.
  • AI product design to develop better products.


Individually, each offers a return. But when interconnected, they create 
contagious ROI—customer insights from support feed into trend prediction, which informs better product development, leading to improved sales. The more these AI solutions talk to each other, the more improving one will have compounding, contagious return.



There’s no wrong way to start. Wave 1 improvements reduce costs, but these are the easiest to find and will be adopted quickly. Wave 2 makes for better customer experiences, raising revenue with repeat or new customers from differentiating features. Wave 3 starts to emerge when you have a synergistic system of AI tools that complement each other, adding to the return each provides

What does a good AI use case look like?


To ensure AI delivers real ROI, assess potential projects through this lens:

  1. Does it solve a user problem? If it’s solving a real pain point, adoption is more likely.
  2. Does it solve an organizational problem? If it improves efficiency or revenue, it justifies the investment.
  3. Does it align with your business model? AI should enhance your competitive edge, not distract from it.


Bonus points if your solution also:

  • Solves a leadership problem – e.g., enables strategic decision-making that helps steer the ship.
  • Includes a clear capability vision – e.g., lays the foundation for Wave 3 transformation
  • Activates your data – AI transformation is a data transformation, and figuring out data ASAP is in your best interest. If you wouldn’t bet something dear to you that your data is ready – then it’s not ready.




Key takeaways of calculating ROI of AI

 strategy


  • AI ROI falls into three buckets: cost efficiency, revenue optimization, and new revenue streams.
  • Prioritize AI use cases strategically by aligning them with measurable KPIs and business objectives.
  • AI transformation happens in waves, from cost savings (Wave 1), to better output (Wave 2) to systemic reinvention (Wave 3).
  • Interconnected AI use cases multiply returns, creating a contagious effect of business growth.
  • Successful AI investments require a solid data foundation—if your data isn’t ready, you won’t be able to execute on your AI strategy.



The bottom line: be strategic about AI ROI


AI is one of the most flexible tools we’ve ever had. But flexibility without focus leads to inefficiency. By categorizing use cases, aligning investments to the right wave of AI maturity, and stacking solutions for interconnected value, businesses can unlock real, measurable returns.


https://tinyurl.com/ja5pbtkt



воскресенье, 30 марта 2025 г.

Business Models of Non-Practicing Entities

 


In the discussion of organizations that provide technology or patent rights to others, Non-Practicing Entities or as some of them are called "Patent trolls" are always debated. My objective with this post is to introduce the concepts and explain the frequently disputed business model.

A few words about patents

A patent is an exclusive right to prevent others from making, using, selling or distributing an invention that is considered new, non-obvious and useful or industrially applicable. A patent does not give the proprietor of the patent the right to use the patented invention, should it fall within the scope of an earlier patent. Patents per se has nothing to do with the business model used by the patent holder or the pricing of products; Skype, Google, and other firms known for providing free services to their users, is still developing and filing patents to claim their rights to inventions, primarily to keep competitors away.

A patent is a limited right (often 20 years from the filing date) that the government offers to inventors in exchange for their agreement to share the details of their invention with the public. The patent system incentivizes organizations to invest in research and development, and to disclose instead of keeping inventions secret in exchange for exclusivity. Being able to keep competitors away for a limited time, gives the inventor the chance to recover their up-front investment in making the invention. For a new pharmaceutical drug this investment can be billions of dollars. In contrast to some granted patents covering software or business methods, the investment can in some cases be close to zero excluding the costs of patent filing. Like any other property right, a patent may be sold, licensed, mortgaged, assigned or transferred, given away or abandoned.


Monetizing innovations

A university researcher or single inventor can chose to start a company to manufacture and sell products based on its research outcome, or chose to use the exclusive right status of a patent to become a licensor. This allows the inventor to accumulate capital from licensing the invention so the inventor's time and energy can be spent on pure innovation, allowing others to concentrate on manufacturability and marketing of downstream products. This can be seen as a straight forward application of Adam Smith's division of labor that having a group of people focus exclusively on inventing new things.

There are numbers of research-based companies that develop new technology or pharmaceutical drugs just to license it to other firms to commercialize. The object for transaction can be just the right to exclude someone, or it can be drawings, data, relating non-patented inventions, knowledge in different forms, knowhow etc.

This ability to assign ownership or rights increases the liquidity of patents as property. Third parties can license or acquire patents and the same rights to prevent others from exploiting the inventions, as if they had originally made the inventions themselves. Small companies or individual inventors that don't have the funds to claim their rights against multinational companies can sell their patents to companies willing to enforce them against infringers.


Licensing of patents is nothing new. In 1894, American Bell Telephone Company's R&D department licensed 73 patents from outside inventors, developing only 12 inventions from its own employees.

Cross-licensing of patent rights

It is common for companies engaged in complex technical fields to enter into license agreements associated with the production of a single product. Scott McGregor, President & CEO of Broadcom, has said that "a cell phone these days can have hundreds of devices that are part of it; each one of those can have hundreds of aspects to it. You could literally have a million or more patents that would apply to a single handset". It is therefore common that even competitors license patents to each other under cross-licensing agreements in order to share the benefits of using each other's patented inventions and reduce the risk of being sued by the other party.

When one company sues another (Nokia vs Apple) the other company often countersues the first one (Apple vs Nokia) and the litigation process often results in that the parties come to an agreement, cross license patents, and pay licensing fees to the company with a stronger case. Counter-assertion is an important stabilizing force in many patent disputes.


Non-Practicing Entities - a question of value proposition

A non-practicing entity (NPE) is a patent owner who does not manufacture or use patented inventions but rather than abandoning the rights to exclude, an NPE seeks to license the rights to others. The value proposition is thus not a product or service, but the rights to an invention with or without supporting knowledge and know-how. A single inventor, a university, a research institute, an SME, a multinational company or an investment fund, can all be non-practicing entities, depending on their choice of business model.

The term patent troll is sometimes used for NPEs that enforce its patents against one or more alleged infringers in an aggressive or opportunistic manner. The general idea of these firms is to develop a large patent portfolio and to license these patents to companies that infringe on them or potentially filing lawsuits against these companies if they refuse to take a license. In some cases the NPE analyze popular products on the market to find remote patents that could be infringed, and approach the patent holder to acquire or get a license to sue.

In some cases these firms have as their business model to purchase patents, often cheaply from technology companies forced by bankruptcy to auction its patents, with the sole purpose to sue and enforce it against companies that manufacture or market products, potentially infringing any of the patents. Some of those accused of being patent trolls argue that they are the modern incarnation of Robin Hood helping smaller companies and inventors against large companies who have stolen their ideas.

Legal extortion or value proposition?

To seek to derive income from the enforcement of patent rights is perfectly legal but it sometimes has troubling implications for the makers and sellers of products and services. As the entity is not selling products or services, almost by definition it does not infringe on the patent rights contained by others, thus they are essentially invulnerable to counter-assertion.


This gives NPEs a position to negotiate licensing fees that could be argued to be out of alignment with their contribution to the alleged infringer's product or service. As a result, a patent held by an NPE is often considered more threatening to industry participants than the same patent held by a competitor. As a result of that, there are operating companies that sell their patents to NPEs to assert the patents without the operating company being involved.

The more dubious NPEs can see even a weak patent as a lottery ticket hoping the alleged infringer chose to pay up without completing a lawsuit. If the defendant chooses to litigate then both sides must absorb heavy litigation costs no matter who wins. As even a successful litigant must pay the costs of defending its case, and that the cost can run into the millions, operating companies may chose to pay up even though they probably would win if they take the case all the way through trial, to avoid the time, expense, and uncertainty. This is something that the more dubious NPEs take into consideration when they approach operating companies.

Revenue model of Non-Practicing Entities

NPEs generate revenues through licensing agreements or damages awarded by a court. Licensing agreements can include up-front license fees, milestone payments contingent upon achieving certain goals, and royalty revenue from the commercialization of the licensed technology. Damages are awarded on the basis of how much value the defendant is obtaining as a result of its infringing activity.

Activities performed by Non-Practicing Entities

All NPEs have to manage their patent portfolios, and identifying existing or potential application areas. Independent of being a single inventor, a university or a patent holding company, activities also involve finding potential licensees, negotiating terms and conditions and collecting license fees. Most NPEs also have internal research and development and patent filing and maintenance activities. There is a continuum from organizations that are doing substantial investments in R&D to generate inventions and patents, and organizations focusing on acquiring and aggregating others' patents.

The good guys and the bad guys

The business model of Non-Practicing Entities is widely debated and there are firms with dubious motifs. Companies that do not manufacture or intend to manufacture anything are often seen as profiting from others in a negative way (at least in the media). At the same time companies outsource or move production to low cost countries, leaving the western world to be “the innovators” where the output is innovation and intellectual property.

Good guys can be found in both ends of the scale, providing valuable inventions, knowledge, data, instructions or knowhow to manufacturing companies, or just aggregating and providing the rights reducing the time and cost for manufacturing companies to find all relevant patents covering a technology area. Without the existence of entities willing to buy patents as a last resort there’s no credible threat a single inventor can make towards a large company. A rational defendant will simply carry on knowing the patent can’t be successfully enforced, and inventors at the margins may not undertake their research in the first place.


https://tinyurl.com/4nbwf5e2