thomas.wieberneit@aheadcrm.co.nz
Beyond GDPR: Is MyTerms the New Standard for Enforceable Personal Data Agreements?

Beyond GDPR: Is MyTerms the New Standard for Enforceable Personal Data Agreements?

The news IEE just released standard 7012-2025 for machine readable personal privacy terms, nicknamed MyTerms. MyTerms covers interactions and agreements between individuals and service providers they interact with on a network. It defines a way for personal privacy requirements to be expressed as standard-form contractual agreements.  MyTerms is intended to replace today’s “notice and consent” pattern with a standardized, machine-readable contract handshake between an individual and a service provider. The standard considers individuals true first parties who can proffer privacy terms as contractual terms, typically through an automated agent acting on their behalf. The system relies on a neutral, non-business entity that hosts a bounded set of standard-form privacy agreements. These agreements are designed to be understandable and usable in practice by humans and by machines. They must be available in plain-language human-readable form, maintain legally meaningful wording, and also exist in machine-readable structured formats with stable identifiers so software agents can select and process them reliably. When an individual, or their agent, proposes one of these agreements to a service provider, this service provider has a deliberately constrained set of responses to allow model scalability. The service provider may accept the proposed agreement, offer one alternative agreement from the same bounded roster, or reject the proposed agreement. The standard does not expect open-ended negotiation beyond that single alternative choice. If the service provider accepts, the agreement is recorded so that both sides retain matching, immutable copies, including contextual metadata such as time, date, and location, to support later retrieval, audits, and dispute resolution. In parallel, service providers are required to publicly disclose which of the standard agreements they...
Flipping the math: How AI changes Build vs. Buy

Flipping the math: How AI changes Build vs. Buy

For the longest time, companies have been trapped by enterprise software vendors. First by shrink-wrapped software packages. Then by SaaS offerings. Both situations led to what one even in a SaaS world can call shelfware – although these days the shelf is a virtual one instead of a physical one. Buyers still get enticed to purchase more capabilities than they need, which leads to them paying more than necessary while often using software packages that offer overlapping capabilities. One of the promises that SaaS started with, was to end this. Sadly, it looks like this promise was not kept. And this is no wonder; after all vendors want to be sticky. And they need to have increasing revenues. This means that they need to offer an ever-increasing number of capabilities, aka features, to warrant their pricing and eventually regular price increases. Combined with the frequently used strategy of offering related capabilities, i.e., seats for an adjacent software that is not yet needed by a customer, this led to two things: bloat and shelfware. Both go at the expense of the enterprise buyer. Since the dawn of packaged software, the argument to buy, i.e., to voluntarily step into this trap, is the same: Buying is cheaper than building. Which probably was correct. Buying from a specialist was the logical choice. Engineering talent was, and still is, scarce. Building software includes a lengthy process of requirements engineering, years of development and ultimately never-ending maintenance. Just that most of this is true for most implementations of purchased enterprise software, too. And the buying process is arguably broken. Need identification is often done...
Is RevOps the New CRM?

Is RevOps the New CRM?

The Lost Strategy: What CRM Was Supposed to Be CRM at its very origin, was a strategy. With the advent of systems that support the execution of this strategy, the term more and more got shifted to describe a system. This shift can get seen in the words of CRM Godfather Paul Greenberg. His pre-2009 definition of CRM was “a philosophy and a business strategy, supported by a system and a technology designed to improve human interaction in a business environment.” This changed to “Customer Relationship Management is a technology and system that sustains sales, marketing and customer service activities. It is designed to capture and interpret customer data, both structured and unstructured, and to sustain the management of the business side of customer related operations. CRM technology automates processes and workflows and helps organize and interpret data to support a company in engaging its customers more effectively” in acceptance of this change (emphasis by me). These days, people often even mean a sales force automation system, when they say “CRM”. In another dimension, the systems themselves more and more turned into systems of record. Implementations often were management-oriented as opposed to team-oriented, which led to increasing dissatisfaction and the creation of new terms and categories like social CRM, system of engagement, customer data platform, customer engagement, customer experience management, and so on. There is much more, but in consequence, CRM lost both, the “C” and the “R”. CRM turned from a strategy into a glorified rolodex and a tool to manage teams, in particular sales teams, instead of helping organizations and teams to manage and improve the customer...
Zoho One: Did 75,000 Customers Find the Sweet Spot?

Zoho One: Did 75,000 Customers Find the Sweet Spot?

Zoho aspires to deliver the operating system for businesses with the goal of driving customers’ margins by unifying business operations on one single technology platform. The most important part for delivering this vision is Zoho One.  Zoho One is Zoho’s premier bundle of business applications. Currently, Zoho One consists of around 55 applications that support sales, marketing, email and collaboration, helpdesk and customer support, finance, HR, analytics, and business processes. Of these, customers use on average 22.  Zoho One can be licensed as an all-in-one platform but also be part of a journey that starts at first licensing one application, then more and then moving to Zoho One directly or via licensing one of the other suites (such as CRM+, Projects+, Finance+, or Workplace, and others). The most used applications in Zoho One are CRM, Analytics, Books, Meeting, and Workdrive. At the time of writing this, Zoho One has around 75,000 customers, which makes it Zoho’s most popular product. The largest customer has around 32,000 employees. Customers are distributed worldwide in more than 160 countries, with the highest numbers in the United States and the European Union.  Organizations that have implemented Zoho One are from a variety of industries, although the top five industries are the high tech, professional services, Real Estate and Construction, Retail, and Banking/Financial Services/Insurance industries. On November 18, 2025, Zoho announced many enhancements to the suite. The enhancements are focusing around three key areas: ·       Experience ·       Integrations ·       Intelligence The biggest enhancement in the experience category is that Zoho essentially removes the boundaries between the...
The Great GenAI Divide: Debunking the Myth of 95% Failure

The Great GenAI Divide: Debunking the Myth of 95% Failure

These days, we are drowning in conflicting information about the value of generative and/or agentic AI. I, myself am researching for good studies that dive into the ROI that is generated by this technology, with limited success. Most information is anecdotal, or comes from success stories, which cannot get used too literally. Two major 2025 reports from MIT and Wharton, respectively, paint starkly different pictures of AI adoption and adoption success. While the meanwhile often quoted MIT NANDA “report” on the state of AI in business often gets quoted with 95 percent of all businesses not getting any ROI from their gen AI initiatives, a recent study by the Wharton Business School shows a very different result with 74 per cent of enterprises showing a positive ROI. Why is one so pessimistic and the other so optimistic? As I have written before, a closer look at the data reveals the 95% “failure” narrative is a myth, or even a scare, and the real story is probably a different and far more differentiated one, which Wharton names Accountable Acceleration. Is GenAI really a 1-in-20 lottery ticket or is it rather a core business function? So, let’s have a look. Methodology matters – debunking the 95% failure rate In contrast to the NANDA “report” that relies on a fairly small sample of about 150 survey responses and 52 structured interviews, the. Wharton report bases on a large-scale, quantitative and longitudinal study. It surveyed around 800 senior decision-makers at businesses of different sizes and is tracking trends for the third consecutive year. Therefore, its data is built for statistically valid conclusions. In...