aheadCRM - Blog #SaaS

The Sovereign Cloud Illusion: Political Fig Leaf or Just Good PR?

Mon, 23 Mar 2026 07:51:20 -0400

The enterprise software market is currently intoxicated by a brand-new buzzword cocktail. If you walk the halls of any major European tech conference today, you will inevitably be assaulted by phrases like "data sovereignty" and "sovereign cloud." Software vendors are practically falling over themselves to announce their compliance with the impending EU AI Act. We are led to believe that a magical new era of localized, ultra-secure computing has arrived. Do not let the marketing brochures fool you. A closer inspection of these architectural marvels reveals that vendor stock prices are the only things reaching the cloud faster than your unsecured customer data.

The recent CRMKonvo discussion with Christian Knoll, CEO of Spice CRM, highlighted a glaring disconnect between the political theater of data sovereignty and the concrete reality of enterprise architecture. The narrative being pushed by the major hyperscalers is masterful. They propose that establishing a data center on European soil instantly absolves an organization of all compliance sins. This is a dangerous oversimplification that fundamentally misunderstands how modern CRM and CDP systems function.

TL;DR

If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers).

https://youtube.com/live/Vz6PHLY-Yuk

Else, be my guest and continue to read.

Or do both …

The American Elephant in the Brandenburg Data Center

Let us address the most prominent piece of vendor fiction currently circulating the market. The German Federal Office for Information Security is cooperating with Amazon Web Services to build a "sovereign" cloud region in Germany. SAP is loudly expanding its sovereign cloud offerings across Europe. The pitch is incredibly seductive for panicked C-level executives. You get all the infinite scalability of a hyperscaler with a lovely European flag painted on the server rack.

Christian rightly identifies this as a political fig leaf. Let’s apply some basic architectural rigor to this scenario. If a data center is physically located in Brandenburg but the operating entity ultimately rolls up to an American parent corporation, your data is only as sovereign as the next international legal dispute allows it to be. The underlying legal frameworks and extraterritorial reach of foreign governments do not politely stop at the walls of a German server farm. Remember the judge at the international criminal court in Den Haag losing access to his Microsoft account? This incident made the court move to OpenDesk. The lesson? Claiming true sovereignty while relying entirely on an infrastructure stack owned by a foreign monopoly is architecturally unsound. It is the equivalent of building a highly secure vault but giving the master key to a landlord who lives on another continent.

This is not to say that localized data centers are completely useless. They do solve latency issues and check a number of localized compliance boxes. However, confusing geographic data residency with actual operational sovereignty is a mistake that can eventually cost enterprise buyers millions in painful migrations. True sovereignty is about control. If your entire Customer Experience stack relies on a single vendor ecosystem, you do not have control. You merely have a very expensive subscription.

Architectural Resilience and the Death of the Single-Vendor Strategy

The conversation quickly moved past the marketing hype to the actual meat of the issue. Risk mitigation is a core driver of any sensible IT strategy. Christian brought up a wonderfully simple analogy. He noted that you do not keep all your cash in a single bank account. Why on earth would you put all your mission-critical customer data, your CRM logic, and your CDP insights into a single hyperscaler basket?

The tech industry suffers from severe amnesia. We have seen the disastrous consequences of single-point-of-failure architectures more than once. When the OVHcloud data centers in France literally burned to the ground, organizations that lacked hybrid failovers lost everything. Beyond physical disasters, we are seeing a rise in arbitrary vendor lockouts. What is your disaster recovery plan if a hyperscaler decides your account violated an obscure term of service and shuts off your access overnight? If your answer involves submitting a support ticket and praying, you should think deep and hard whether you can improve your strategy.

Smart organizations are actively swinging the pendulum back toward hybrid architectures. This does not mean abandoning the cloud. It means architecting for failure. We are seeing a resurgence of strategies where a primary CRM instance runs in a public cloud, but a fully functional, replicated instance is maintained on-premise or with a specialized local host. This approach drastically reduces the blast radius of a cloud outage or a geopolitical dispute. It requires more engineering effort upfront, but it is the only way to guarantee business continuity in a volatile market. The introduction of the NIS2 directive in Europe will only accelerate this trend, forcing companies to prove their resilience rather than just claiming it.

The Generative AI Magic Trick

No discussion of modern enterprise software is complete without addressing the elephant in the room. Artificial Intelligence is currently the ultimate shiny object. Every vendor is promising to revolutionize your CX with Generative AI, LLMs, and RAG architectures. The reality is far less glamorous and significantly more dangerous.

The rush to implement AI features is causing companies to abandon basic data hygiene. Organizations, or their employees, are piping sensitive customer profiles from their CRM systems directly into public LLM APIs. This is a catastrophic failure of data governance. When you send unencrypted customer data to a public AI service, you are essentially training someone else’s model with your proprietary assets, although your contract may say something else.

Christian offered a breath of fresh air on this topic. He pointed out that AI models rarely need to know the actual identity of your customer to perform complex analysis. The sensible architectural approach is to implement a strict anonymization layer before any data leaves your controlled environment. You scramble the PII, send the structural data to the LLM for processing, and then decrypt the insights locally.

Furthermore, the idea that every company needs to rely on massive, general-purpose models from OpenAI or Google is a fallacy. For most specialized CRM tasks, smaller, possibly locally hosted models are more than sufficient. They are also far more efficient. You can run specialized, fine-tuned models on your own infrastructure. This eliminates the data privacy risk entirely and often results in faster, more accurate outcomes for specific business processes. Do not buy into the vendor narrative that you must surrender your data to utilize artificial intelligence.

Conclusion: Reclaiming the Stack

The European drive for data sovereignty is currently trapped between a political ideal and a monopolized reality. The initiatives are forcing necessary conversations at the board level, which is a positive development. Executives are finally waking up to the risks of total dependency.

However, concrete action requires moving beyond the vendor rhetoric. True data sovereignty is not something you can purchase out of a box from a hyperscaler. It is an architectural discipline. It requires a relentless focus on data classification, strategic redundancy, and a willingness to utilize smaller, local infrastructure providers where appropriate. The enterprise software market will always try to sell you a magic pill. Your job as a technology leader is to recognize that this pill is mostly sugar. Roll up your sleeves, and do the hard architectural work yourself.

The Buyer's Reality Check: Navigating the Sovereign Data Circus

If you are an enterprise software buyer staring down a multi-million-dollar CX transformation, the current landscape of AI and data sovereignty can feel like navigating a minefield blindfolded. Do not let the slick presentations dictate your strategy. Here are three concrete recommendations to keep your architecture sound and your budget intact.

Integration Realities Over Hyperscaler Promises

The most beautiful sovereign cloud architecture is utterly worthless if it cannot talk to your legacy systems. Vendors love to sell a vision of a unified platform, but the reality of enterprise IT is still a messy web of APIs and batch transfers. Focus your evaluation on integration capabilities. If a "sovereign" CDP requires a proprietary connector that locks you into a specific hyperscaler's ecosystem, you are just trading a compliance risk for an integration nightmare. Demand open standards and ensure your data can easily migrate out of the platform before you ever sign the contract.

Data Quality Trumps Generative Hype

Generative AI and RAG architectures are mathematically fascinating, but they are entirely dependent on the quality of the underlying data. If your CRM is filled with duplicate records, outdated contacts, and inconsistent formatting, plugging an LLM into it will only allow you to generate incorrect insights at an unprecedented speed. Stop obsessing over the latest AI models and redirect that budget toward aggressive data cleansing and governance. A simple rules-based engine running on pristine data will consistently outperform a massive neural network trained on garbage.

The Human-in-the-Loop Necessity

The tech industry is desperately trying to sell the dream of fully autonomous customer experience systems. This is a dangerous fantasy. AI models hallucinate; algorithms exhibit bias; and automated workflows fail spectacularly when encountering edge cases. You must architect a mandatory "human-in-the-loop" step for any process that directly impacts customer relationships or touches sensitive data. Use AI to augment your agents by summarizing histories or suggesting next best actions. Do not allow an algorithm to make final, unreviewed and irreversible decisions about your customers. Automation without strategy and oversight is just a highly efficient way to ruin your brand reputation.

SaaS or the Rise of the Undead

Tue, 07 Jan 2025 20:02:39 -0500

SaaS is dead! It will be replaced by agentic systems that replace coded business logic by AI agents that autonomously interact to bring said business logic to life, just smarter. Satya Nadella said it - or at least something in these lines, if I believe all the pundits around. His words lit up the Internet. And Satya Nadella being the CEO of a 3 trillion dollar company is the ultimate fount of truth and wisdom, when it comes to business applications. Is he not?

So, what should we take from his statements? After all, the words of the CEO of one of the top 3 valuable companies on this Earth carry some weight.

Let me start straight.

I call BS!

SaaS, first of all, is a delivery model of logic that also had some implications on vendors‘ business models and their approaches to pricing. For a variety of good and not so good reasons this delivery model succeeded vs. the prevalent model of on-premises software. Some of the more important reasons have been “no lock in by vendors”, “only pay for what you use”, “reduction of own infrastructure cost”. Of course, there are more. All of them being true – or not so much. One thing is for sure, SaaS led to a considerable centralization of compute resources. Hyperscalers emerged. Vendors took over the management of the application stack for their clients. It is very hard to envision that this gets reverted any time soon, even in a world with increasing trust issues and a good argument for edge computing.

What SaaS is not, or only marginally, is a way of creating business logic. Of course, software architecture changed to support multi tenancy vs. single tenancy, but this is rather an internal reason to make this delivery model more efficient for vendors. Clients do not care about single- or multi-tenancy, as long as their requirements are met. Just to be clear, multi tenancy, and with it, SaaS, first of all is a means to make software delivery and maintenance more efficient for the vendors. The benefits of this efficiency gain may or may not be forwarded to customers.

What Nadella suggests is a totally different way to build application logic. Instead of formulating it by coding and/or rule systems that automate a process, he envisions a network of specialized artificial agents that collaborate flexibly to achieve the desired outcome. Sounds cool and modern, doesn’t it?

Just that it ain’t work.

For several reasons.

Chief of them are accuracy, reliability and predictability. While coding and rule-based systems deliver predictable and repeatable – i.e., auditable – outcomes, the current breed of artificial agents does not. Instead, they are probabilistic and very likely deliver good results, which is often not good enough. And this is not fully mitigated by technologies like RAG. And in the vast majority of situations, businesses and their managers prefer, even need predictability. How well agents based on different foundation models fare in “consequential real-world tasks” is impressively evaluated in a research study titled “The AgentCompany”. The researchers found that even the best model (Claude 3.5 Sonnet) manages to complete only 24 per cent of the total of 175 tasks. I’d say that this is quite sobering. Research conducted by the Australian National Science Agency on the usefulness of Microsoft’s Copilot vs. expectations shows mixed results, too. Now, one can say that it doesn’t really matter whether a human employee or an AI agent makes the mistake as the result is the same. I, myself, use this argument a lot. But in this situation, we are talking about trading a predictable outcome for a probabilistic one.

Then, there is cost. Running large language models, let alone train them, is incredibly costly. Why would a CFO or his/her CEO in their sane mind replace their expensive systems with even more expensive systems? These systems being AI based cannot be the justification, cool or not. OpenAI is losing $5 bn in 2024 on revenues of $3.7 bn. Microsoft is planning to invest $80 bn into AI-ready data centers in its fiscal year 2025 alone. It would be naïve to assume that these are done out of charity and that there is no intention to create revenues out of these investments. So, the only reasons for doing so, are the agent-based system delivering far superior capabilities or saving even more money somewhere else.

But Nadella is right, too!

SaaS does not live up to many of its promises. We still do see considerable lock-in, we see pricing that is geared towards vendors and, in my opinion, worst of all, we see considerable “siloisation” of business logic, which led to disjointed data and, in consequence, broken processes. In addition, codified business logic has a high cost of change. Additionally, SaaS software traditionally offers less scope for customization than on premises software did.

In this sense, SaaS, or business software in general, needs an overhaul, although one can argue that few of these problems are SaaS specific and that it is in no way sure that agentic systems will resolve them.

Agentic systems require a data harmonization to work. Whether they access a multitude of different databases or just one, directly or via an abstraction layer doesn’t matter. The bottom line is that there is a considerable drive towards quality data.

Architecting systems based on autonomous agents that interact with each other has the potential of making applications truly smart. Theoretically, they can adapt their behavior automatically based upon changing customer/user requirements. Easier adaptation of systems is the holy grail for some time. Microservices and composable architectures are good examples for this force.

The necessary technologies are there and “only” need to be combined.

Staying close to architecture, agentic systems are platform systems, i.e., they strongly prefer a single (family of) vendor(s). For connected agents to work properly, they need a common language that all of them understand – aka an interaction protocol. This is entirely possible, but mandatory to avoid rising integration cost.

Pricing is different, non-technical, topic. Yours truly and other people have written about this topic. Here a good one by Phil Wainewright. Agentic software offers the possibility to achieve outcome orientated pricing and to align vendors’ and their customers’ interests. However, as Phil writes succinctly “Throughout the history of Saas, people have been talking about outcomes-based pricing, but while it sounds attractive on paper, it's really hard to deliver in practice.” Still, pricing models will change as there is no coupling between agents and users anymore in agentic systems.

Let me add another point. The interaction with software is traditionally built not around how humans interact but around the limitations of how computers – machines – can interact. I do not say that GUIs and point-and-click are all bad, but still, they are a band aid to enable the effective and efficient interaction with software. With the advent of NLP, NLU, NLG and LLMs, these limitations do not really exist anymore. Instead, humans can now interact with computers in human ways and are no more confined to the application window. This is game changing.

So, what now? BS or not?

In summary, one needs to read Nadella through a Microsoft lens. Agentic systems offer the possibility of drastically simplifying the (business) software stack by migrating a vast variety of different tasks into different types of software agents that work in orchestration. Doing so, is certainly changing the SaaS world into something that looks very different from now. Microsoft as a technology vendor supports nearly all of these tasks to an extent. Apart from his click-bait type of terminology he has a point or two.

But is SaaS dead? By no means.

Can a world as Nadella sketches it evolve? Sure as!

It only needs three ingredients to make this new world of SaaS happen:

A bold vendor that offers considerable business functionalities via working agentic software
At attractive pricing
That convinces enterprising businesses that it is well worth the plunge

Exciting times ahead!

This is the way of SugarCRM - a CRMKonvo

Sun, 13 Dec 2020 12:37:07 -0500

In this conversation we had the pleasure of talking to Clint Oram, chief strategy officer and one of the founders of SugarCRM. We discussed 2021 trends to find out which ones Cllint does see and, of course, which path SugarCRM is following on its trajectory to becoming a platform player and participating in the #ClashOfTitans.

This couldn't be covered without discussing the reasons for SugarCRM leaving the initially highly successful path of using Open Source Software (hint: there have been very good reasons) and what it entails to become - and stay - successful. Clint related a very valuable personal story here to make his point: It is not only about having the right idea. There is so much more to it - but watch it in the CRMKonvo.

It being the season, we also asked him about which trends he sees and what customers are asking for. Good answers here.

The worst word of the year? "New normal". Well, I cannot but agree here ... although ... something has changed, hasn't it?

Enjoy this awesome CRMKonvo.

https://youtu.be/mJ-YU3FhifA

Clouds, Data Models, and Experiences - Three Entities, One Topic

Mon, 02 Dec 2019 12:00:47 -0500

After having covered some press releases about new releases and commenting some interesting organizational changes it is time to have a look at another topic – the need for consistency in a suite of cloud products. Consistency not only in the most obvious part of a family of products and solutions – the user interface – but the more important aspect of consistency, namely the data model. If you wonder how this relates to customer experience I invite you to read on. This post is actually spurred by a brief conversation that I had with Jon Reed of Diginomica about this very topic during one of the recent CRM Playaz episodes. Btw, if you do not yet listen in to the LinkedIn conversations of CRM Playaz Paul Greenberg and Brent Leary, discussing important developments and current events in the world of CRM – then you should. Really! But I digress. Back to the topic. The question is about whether it is necessary to have a unique data model or not. And this question might be answered differently, based upon the definition of ‘data model’. There is no doubt that a unique data model across applications is very helpful, actually a necessity. Where there is doubt, is whether this data model needs to be defined on database level or not in order to be really helpful. My point of view is that it does not need to be defined on database level. This point of view might be contradicting some ‘common sense’ wisdom and the strategy that some very successful companies are pursuing, including Oracle – as it seems – and Zoho. In the good old days before the advent of the ‘New Dimension’ products, SAP had one, too. On top of it sat R/3. Just to be sure: Having a common ‘data model’ across applications is a huge advantage. There is no doubt about this. But let’s dig into the two main possibilities on how to achieve and implement one. One possibility is to model and fix it on database level. To define and model it in a way that every attribute and relation has its one-to-one representation on the database. This model most certainly has some advantages. It offers one consistent and unique model of describing what is important for and about organizations and (business) transactions. It gives utmost control and precision about semantics and it makes it very easy to understand what a business concept is about. It is also performing well – if not normalized too far. This is the winning model, if it is correct and thought through – and can be kept stable. As I said above, it is the concept that Oracle and Zoho are pursuing. And I am not the one to say that either of these example companies has not thought through this approach of defining and implementing an enterprise data model. In fact I am very sure that they did! And they did even more. They did something that other companies, including SAP, and as far as I see, Salesforce, omitted to do for too long after the cloud and therefore silo’ed solutions emerged. The advantage of cloud solutions and best-of-breed solutions is that they focus on solving few problems, but these very well; and the customers without the necessity to buy much functionality they neither want nor need, get just what they want. However, with this comes a challenge, the challenge of diverging data models. Each of the applications, even within the same family of cloud applications, often has different data models. This is due to the fact that they are optimized for different tasks, so can be viewed as being quite natural. Just that it isn’t. It is the easy way. And it doesn’t work in a platform economy. Not at all. As I have written before, a platform constitutes of four pillars:

The technology platform
Tools that enable and provide insight
Productivity tools
And an ecosystem

The latter three pillars suffer, if the former does not provide for a unique, yet extensible, data model with well-defined semantics If the latter three suffer, so will business applications built on top of the platform. As ecosystem players provide own applications and extensions to existing applications, it is necessary to have a common language that describes how business entities look like, how they relate to each other and how they are governed. In times of make or buy decisions frequently being decided towards buy the right way to go is to offer a business meta data model that fulfils three main conditions:

It provides a definition of the main business objects from a business point of view.
It is extensible.
It allows for centralized maintenance across applications within an ecosystem.

Now, it should be documented as well, but that is another story … At SAP, in ancient times sincerely, this was a job done by the data dictionary (minus the documentation); partly done, to be honest. The data dictionary was an abstraction of the physical data model to describe business entities. Just that it was more geared towards abstracting from the database, as opposed to defining a business language. There are different ways to implement this business meta data model in a cloud first world. Microsoft developed the common data model, which enables no- and low code development across its ecosystem. Also providing the development tools and its own environments, Microsoft is essentially leading the pack. Salesforce promotes its own Canonical Data Model with industry flavors. Salesforce’s challenge is that it is a CRM company and not covering the full value chain. And there is another one, which I’ll mention a bit later. Zoho has gone forward similarly, staying in full control of their own destiny by not having acquired a single vendor so far (which makes up for an admirable strategy and success story). The company builds its apps around the concept of what they call data pillars, which are controlled by some apps that act as a database. Other apps use this database. Within its ecosystem these apps can be enhanced by means that stretch from no-code to professional coding. One of Zoho’s challenges is that the ecosystem still needs to get strengthened to be really on an eye-to-eye level with the big four. SAP is currently working on SAP Graph, which is a wrapper around the APIs of SAP’s existing products, creating a harmonized, business oriented API layer that can and should be used by application developers. They are coming bit late, but with a good and important approach. Additionally, SAP is working on SCP based micro services that manage the access and usage of business objects across applications. Done right these services could also have the ability to extend the business objects of the underlying and connected applications. One challenge is to keep these services in synch with SAP Graph. Ideally they are the same. The combination of SAP Graph and the micro services can be a real winner if the services do not only allow the management of data access but also the customer/partner specific extension of the data model and with it the corresponding web services. It cannot be overestimated: With the help of a common data model and semantics customers, vendors and partners can easily and consistently extend application families to serve their customers and users. This is the foundation for any attempt at providing positive and lasting experiences. On top of their own models, and jointly, Microsoft, Adobe, and SAP, together with a growing number of additional partners, are working on the Open Data Initiative ODI, which is ‘a common data model, and a common data lake’ that helps avoiding data silos and their integration. Having this data lake, based upon a well-defined semantics, and a well-defined API as given by a single data model across all applications of an ecosystem, is what enables the creation of engagements that can result in memorable experiences. Everything, and I mean everything, that creates insight and enables corresponding action powering engagements and experiences, depends on a data model like this. The power of ODI cannot be underestimated. The strength of ODI lies in its being cross ecosystem as it spawns across at least two major ones, therefore bringing the concept of a unified data model to a whole new level. Its weakness lies in not covering some more important ecosystems. But then this post is not about deficiencies of an initiative. It is about the importance of having and offering a joint data model and API for ecosystems. The importance of this cannot be underestimated as well. And decision makers need to have a hard look at where platforms are moving with regards to this topic.

Clash of Titans - The War Cry: Oracle and Salesforce

Tue, 11 Sep 2018 09:29:28 -0400

More Food for Thought

In the last article Clash of Titans – Microsoft and SAP weigh in of this little series, I discussed the strategy of two of the big four and how they are positioned in the platform play of the business software titans – and others. This article covers the other two: Oracle and Salesforce. These business software vendors are competing in a market that is changing – commoditizing – at a fast rate towards an experience market, and probably beyond, if I follow the argumentation and thoughs of CRM godfather and friend Paul Greenberg. Business application vendors can stay really successful only if they morph into platform players. And this platform is more than just a technology platform, but encompasses four dimensions. The four dimensions that are paramount to be able to deliver great engagements that result in lasting positive experiences are

Platform (IaaS/PaaS)
Ecosystem
Insight
Productivity

In this article I look at Oracle and Salesforce and how they position themselves in this game of thrones. But now, without further ado, let’s dig into the topic.

Oracle

Since the launch of what originally was project Fusion and now is Oracle CX, the company has done a remarkable pivot from being an on premise company to becoming a cloud company. The company has its strength in being a full stack provider with a full range of business applications. However, its main strenght is owning the gold standard database engine that runs the majority of business workloads worldwide. From its overall technological profile one could position Oracle somewhere between SAP and Microsoft as it with Open Office also owns a full fledged office suite that helps on the productivity side. However, Oracle is not a public cloud IaaS player although, at its core, it is rather a technology company than a business software company. The main purpose of the Oracle cloud is running Oracle applications, and running them efficiently. And to further reduce the resulting risk of customers defecting to other vendors Oracle introduced its Cloud at Customer back in 2016, which was actually a pretty good idea. This is also evidenced by Microsoft copying it with the Azure Stack. Ecosystem-wise, Oracle appears to be trailing Microsoft, Salesforce, and SAP. While the company owns significant assets that have their roots in the open source community, like Java, or Open Office, Oracle does not have the reputation of being much of an ecosystem player, but more of a kind of bully. Still, Oracle has a good number of implementation partners. Insight is one thing where Oracle has strengths. For one there is a full stack of business applications that are capable of delivering a lot of important data into Oracle’s machine learning algorithms. But there is more. The database. Especially since the introduction of the Autonomous Oracle Database Service. This service promises to bring down cost, while increasing performance and delivering unprecedented scalability and security. And it delivers data that can be used for improving one of the most worrisome challenges: It delivers the insight on security problems and is capable of acting on it. This is a value proposition that currently none of the other vendors can claim to have. Although it is only a temporary advantage, as so frequently in this business. Oracle owns a good number of productivity tools, namely the above mentioned Open Office. It has also intelligence built into the business applications – and the administration layers – that increase staff productivity. So, they are playing fairly well in this dimension, too. In my eyes Oracle should work on becoming more approachable, and getting rid of the image of being a bully. Improving on the ecosystem frontier while using the great database asset that the company has could make it an even more formidable player than it already is. Oh, yeah, and do not set your sights too much on AWS. Microsoft is your real opponent.

Salesforce

Salesforce surely is the current synonym for CRM software, and this not only because the company wisely chose this acronym as its stock ticker symbol. Evolving from its origins the company has evolved its portfolio into a wide variety of customer facing applications. The company also has realized long ago that business applications will get commoditized and that there consequently is a need for a platform, which can get used by its vast ecosystem of ISV’s and implementation partners. The platform that helped Salesforce starting their ecosystem is Force.com and, in combination with being an ecosystem player at its heart it was able to create one that is probably rivalled only by Microsoft’s. Salesforce’s Trailhead education platform is even better than what Microsoft offers. While the technical platform is (mostly) limited to customer facing applications, which also has a challenge on the data side, discussed below, the thriving ecosystem is Salesforce’s biggest asset. The combination of ecosystem and relentless focus on customer facing applications resulted in Salesforce taking an undisputed leadership position in the wider CRM market. Well, a strong sales strategy and execution helped to get there, too; still helps. However, as mentioned above, the company’s focus on CRM-like applications and then e-commerce results in limited access to data. And data is the raw material for insight – which is actionable information. From an insight angle, Salesforce has created its Einstein layer, which is embedded into the applications. Embedded intelligence is what can create immediate value for business users. It provides predictive analytics and recommendations, sometimes even prescriptions to users and/or takes away tedious tasks. And this is exactly where Salesforce’s data challenge lies. Salesforce has a lot of customer and order data, but none of supply chains or relations outside a company realm. This is where Oracle, SAP, and especially Microsoft have an edge. This was also an important reason for Salesforce attempting to acquire LinkedIn and looking at acquiring Twitter. The company finally acquired Mulesoft, which can alleviate the data weakness to some extent, while also serving as an improved glue between Salesforce owned applications and Salesforce to non Salesforce integrations. Mulesoft connects processes and therefore gives access to business data which it can also feed into Einstein’s machine learning capabilities. The main productivity tools that Salesforce offers, are Chatter, the embedded analytics applications including the Salesforce Inbox and the Lightning UI. With these the company covers business productivity but still trails the ability that e.g. Microsoft can offer with the office suite of products. In summary, Salesforce is a formidable player. Right now, no competitor can afford ignoring them in the wider CRM area. It, however, is not all hunkydory in downtown San Francisco. The company is in need of getting more access to data and better access to the supply side of businesses instead of focusing on the demand side, where it is undoubtedly very strong. Another facet is the need to staying perceived as the innovator of the industry. This one is particularly important as it helps Salesforce command premium prices, which keep it profitable. While, from a customer experience point of view one cannot go around Salesforce, the company’s low profitabilty is an achilles heel that the competition does attack and will continue to do to. In order to not run into the risk of getting sidelined, Salesforce needs to continue playing its strength in innovation while improving on its profitability – without increasing prices.

In Summary

Salesforce is sitting on the throne that the other three companies are after. However, it is not a stable position. Salesforce owns the definition of CX, but it is dangerously limited in its scope. Looking at the big four, Salesforce for SAP and Microsoft is the enemy’s enemy, that keeps them in a carefully balanced alliance … which probably gets instable if Salesforce shows signs of being dethroned – by either Microsoft or SAP. Having said this, I do not see Oracle as being one of the top three vendors, rather a number four. This is in spite of its tremendous database force, which already is attacked, too. Oracle is lashing out at Amazon, both Microsoft and SAP have Salesforce in their sights, for time being. The company that should get into the sights of everyone else is Microsoft. Microsoft has all it takes to become the number one, including the most compelling strategy for small and emerging companies. Then we see some smaller players like e.g. Freshworks or Zoho that have the chance of disrupting the big players from below. But is this a fixed outcome? Not by far. All these companies are playing their strengths. And then we have the big infrastructure players, too. Amazon, Google, and Alibaba. And then there is Apple. These companies, plus the likes of Facebook and Netflix, sit on the one commodity that becomes more valuable by the minute: Data. Alea iacta est! Non tacitus!

Clash of Titans: Microsoft and SAP weigh in

Tue, 28 Aug 2018 10:37:42 -0400

A little recap

As it has been some time since I published Clash of Titans – Platform Play, the first part of this little series, let me start with a little recap. The business applications market, especially the CRM market, is evolving fast. CRM has morphed from concentrating on transactions to become an enabler of engagements. Engagements in turn result in experiences. And positive experiences are what companies want to achieve. In a digital world this is possible only if companies rely on a foundation, a (technical) platform. Becoming the provider of the dominant technical platform therefore has become the main goal of of the big business software vendors. However, even governing a great technical platform is not enough. Software vendors that want to be successful platform players need to be able to deliver on four areas to succeed:

Platform (IaaS/PaaS)
Ecosystem
Insight
Productivity

Only if they deliver on all four aspects are ‘platform players’ able to provide their customers with what they need to involve themselves in digital engagements that result in sustainably positive experiences. I will look at how the big four are measuring up in this and the next article of this little series. Microsoft and SAP will be the starters. Then I will look at Oracle and Salesforce. I might conclude with some surprise additions. But let the games begin!

Microsoft

Microsoft is the (not so, if you look sharply) hidden champion of this game. Actually, I think that Microsoft is the 800 pound gorilla in this game. It is Microsoft’s objective to become the fabric that connects enterprises of all sizes with their stakeholders, including the customers’ personal lives. And, as I have written earlier, they have all the ingredients they need to achieve this objective. With Azure there is one of the strongest IaaS and PaaS games in the play. Including Azure Stack, Microsoft is capable of offering hybrid deployments. And in all seriousness, hybrid clouds are here to stay for quite a while. The Power* series of tools and applications helps extending the business applications and the development environments are very powerful. Microsoft is the clear leader when it comes to productivity applications outside the core business applications, which are also tightly integrated into the business applications for further impact. On the insight side the company has few equals, being able to leverage the power of both, LinkedIn and Bing, their own search engine, and the wealth of data that comes from a plethora of different devices. This is combined with strong analytics and machine learning capabilities, which can create insight out of all the data. Last but not least, Microsoft has one of the strongest ecosystems on this planet. What they do not have themselves, someone else is developing. Microsoft then embraces the partnership angle. A very visible example for this is the current strategic partnership with Adobe. Microsoft till recently did not have an enterprise grade multichannel marketing engine. Nor an ecommerce system. Adobe has both. Microsoft is reselling Adobe as part of their strategic partnership. Finally, there is something else that needs to be considered. As stated above, the enterprise market is saturated. All big vendors, and many more small ones, are tackling the SMB market. Microsoft Dynamics is not as high end as the competition but very suitable for the higher end of the SMB market. This makes Microsoft interesting for companies that would not look at SAP, Salesforce, or Oracle. Microsoft also runs a very strong partnership with Nimble, which opens up the Microsoft Dynamics world for small, but growing businesses. On the flip side: Microsoft is not (yet) universally perceived as a business applications company. Still, the company is in a position that none of the other vendors can take (yet): None of them is able to combine the enterprise value chain with a productivity suite as powerful as Microsoft’s and a reach to the end customer. Add some tremendous data assets and a strong ecosystem to the mix. Exactly this breadth and width of the offering is Microsoft’s biggest strength, which covers for functional weaknesses in some areas like supply chain, ecommerce or marketing. If Microsoft is able to mitigate these weaknesses while continuing to play to its strengths, the company should be able to gain considerable market share on cost of one or more of the other three.

SAP

Using Microsoft’s objective as a guideline, SAP is currently the business vendor that is closest to being the fabric of enterprises. The reason for this is the access to data in combination with the ability to support the whole value chain of companies across a wide range of industries and sizes. Looking at the enterprise software market, SAP is the clear leader in ERP software. On top of this, SAP has Ariba. Ariba, or the SAP Business Network is one of the largest, if not the largest, business market places around. In combination, SAP can say that nearly 80 per cent of all business transactions touch an SAP system, one time or another. On top of this, with Gigya SAP owns one of the strongest Customer Identity and Access Management platforms around. Via this platform SAP manages more than 1.3 billion identities, along with their consents, across hundreds of sites. The smart progressive profiling methodology that is built into this software also helps with building valuable profiles out of these mere identities. In combination with SAP’s strong analytics capabilities, the company is able to generate extremely valuable insight to businesses. In addition SAP, like Microsoft and Oracle, covers the complete value chain of businesses, just that SAP’s offering is probably stronger than that of the competition. This, again, gives SAP customers vast amounts of consistent data that can be utilized to offer more value to their customers. This application strength in what SAP calls the ‘digital core’ is also a good part of its platform. Add to it an SAP Cloud Platform (SCP) that offers the majority of services that an agile business needs and that gets increasingly stronger we have a very strong (PaaS) platform play. This platform, along with one of the strongest partner ecosystems around can open up the SMB market, and hence strong growth, for SAP. Talking about its ecosystem, SAP has a wide variety of implementation and consulting partners, that support each other and get support via platforms like the SAP Community Network SCN, or the SAP Partner Edge. SAP positions itself as an enterprise software player, as opposed to a full stack player like, e.g. Microsoft. Consequently, the company’s IaaS capabilities are limited. Instead, SAP is pursuing a multi cloud approach by being able to have its software run on all major infrastructures. This is a smart move as it keeps the company’s independence while offering choice to clients. One of the company’s better kept secrets – SAP Business by Design – is a central element of its strategy to address midmarket companies. Apart from the prevailing (but increasingly wrong) opinion that SAP is difficult to deal with, SAP’s weakest spot is productivity in the sense of office products. The company covers this topic via integrations with Microsoft’s suite of applications, and probably Google apps soon. But, to be sure, efficient, and automated execution of business processes is at the heart of SAP’s value proposition. If SAP continues to play on its ERP strength while pursuing the newly established focus on its Customer Experience unit it has a good chance to stay one of the dominant players.

In Summary

Here we have two companies that are greatly positioned in a platform market. With different starting points and strenghts they share similar visions. And they work hard towards it. Exciting times. But let us see how Oracle and Salesforce are playing their cards – or should be. A bientot!

SAP acquires CallidusCloud - Take Two

Thu, 12 Apr 2018 17:41:25 -0400

The News

SAP has recently announced the completion of the acquisition of Callidus Software, Inc. Unsurprisingly, CallidusCloud’s assets shall get consolidated under the umbrella of SAP Hybris leveraging the customer relationships that the existing leadership team, which shall continue to lead their team, has built. CallidusCloud is a leader in sales performance management and in the CPQ area and also has some more interesting assets, notably their contract lifecycle management offering, which ties nicely into the CPQ piece. The CPQ software has a (first) working integration into SAP’s Cloud for Sales, which got announced in September 2017 and that gets continuously improved. One seemingly simple, yet powerful feature of the CPQ software is the indicator for margin health that gets updated as a sales representative works upon a quote. The software’s ability to generate multi-level workflows based upon changes of prices or contract clauses creates an efficient workflow, which includes the customer when using the portal based delivery of documents during negotiations. All in all the software is geared towards making the sales process efficient. CallidusCloud’s solutions shall be sold standalone as well as integrated into SAP solutions and a roadmap shall get announced at SAPPHIRENOW in June 2018. I have done a brief initial analysis of this acquisition right after the plan got announced and followed up with some musings about how CPQ can be delivered in a customer experience fashion.

The Bigger Picture

With CallidusCloud’s CPQ SAP now has at minimum three configuration engines that can get used by customers:

ERP Variant Configurator
SAP Hybris CPQ
CallidusCloud CPQ

A fourth one comes into the picture if I add the Internet Pricing Configurator, IPC, a Java engine which runs embedded in SAP CRM and that is, using ‘condition technique’, mostly compatible to the configuration engine within ERP. For tech aficionados: The user exits that are available to manipulate how the access sequences are used, are working differently, and require Java skills, as opposed to ABAP skills. SAP Hybris CPQ can be seen as an advanced version of IPC, which got moved under the Hybris umbrella as SAP correctly sees CPQ as an important part of the glue between frontoffice and backoffice. Still, although being a Java engine, it is deployed on premise only – as far as I know, while CallidusCloud is, of course, a web based system. To my best knowledge SAP has about 3,000 customers that are using the ERP Variant Configurator and/or SAP Hybris CPQ and/or IPC. I am more than happy to get corrected on both of these two pieces of information. On top of SAP’s own configuration engines there are partner engines, for me most notably, In Mind. In Mind is a cloud based CPQ engine with a focus on the manufacturing industry. It is built on top of the SAP Cloud Platform. The company got founded by former SAP people with significant experience in the manufacturing industry and configuration. One could say that one of their objectives is to close the gaps in the configuration area that SAP did not address. I had the pleasure of working with some members of their team and am still impressed about their knowledge and dedication. Then there are of course more third parties. In summary, customers have choice. But, they have choice. Which means a challenge: Which software to look at in which situations? Of course the different products have different strengths and weaknesses. The usual conundrum of software selection. And right now there is little advice on what to do, at least up to and until SAPPHIRE NOW.

My PoV and Advice

One thing is for sure: Going forward, CallidusCloud will be strategic for SAP; maybe not to the extent as Hybris E-Commerce was back when it was acquired, but CallidusCloud will make up an important pillar in SAP’s strategy. SAP Hybris CPQ and the Variant Configurator are on premise products. They are particularly strong when it comes to heavy duty configuration and to Solution Configuration. They also work well within the SAP ERP (and supposedly S/4HANA) ecosystem. With graphical user interfaces that can get bolted on top of them, companies that have complex configuration requirements and that do not need or want a cloud based engine get one of the more powerful tools that are around. Being a Java engine, SAP Hybris CPQ can also be integrated into a Hybris Commerce environment. If CPQ shall be used web based and out of offices by salespersons then the first choice for an SAP customer is CallidusCloud. Doing the whole process, including the initial contract generation piece and keeping an overview on the state of negotiations, is a huge benefit. CallidusCloud also may continue to be a good choice for non-SAP customers. Being a long standing Salesforce partner the integration into Salesforce at this point is rather better than the integration into SAP Hybris – although this is likely to change. Additionally, I have heard mixed accounts about Steelbrick, Salesforce’s own CPQ solution. However, CallidusCloud CPQ is far less about solution configuration as SAP Hybris CPQ, although I have seen some prototype functionality that suggests a move into this direction. If a cloud solution with stronger configuration capabilities than CallidusCloud currently offers is needed, then there is In Mind. With or without CallidusCloud CPQ it is worthwhile for customers to have a look at their CLM solution, which can be implemented standalone.

Advice for Customers

This leads me to the following recommendations for SAP customers:

If you already run SAP Hybris CPQ, continue using it until you realized a meaningful ROI, as it will stay around. There are too many customers for SAP to abandon it.
If you do not yet have a CPQ and are at least initially not too heavy on the configuration then CallidusCloud is the first option to look at – unless you are cloud averse, in which case it is SAP Hybris CPQ. But be aware that the setup of CallidusCloud is, and will likely continue to be, easier than the setup of SAP Hybris CPQ.
If you are heavy on configuration and solution configuration, want a cloud based CPQ solution, and ideally are in the manufacturing industry, then have a good look at In Mind. The caveat that I, sadly, need to make here is that the position of In Mind as a company got somewhat weakened although they are still on SAP’s price list.

Advice for SAP

It is good that SAP intends to provide a roadmap already at SAPPHIRE NOW. In order to alleviate fears and mitigate the FUD that the competition doubtless creates, it should be pretty precise, aggressive, yet credible. The roadmap should especially consider guidance to customers on when to choose which of the existing solutions. It is almost inevitable that there is an overlap of use cases that cannot get resolved; still this is a much needed piece of advice. The second important part is, of course, detailing how especially the integrations into SAP Hybris Cloud for Sales and SAP Hybris Commerce will develop. Tight integration is a key asset. Third, I’d hope to hear about an easy-to-implement license conversion program for those customers who have just bought in to SAP Hybris CPQ, knowing that they will not need its full powers, and wish to migrate. While this might not be a great number of clients, it would show an immense customer orientation, help against the still existing image of SAP being hard to deal with, and be a quick and easy way into reference implementations. Lastly, and knowing that this is a difficult proposition, the announcement of an easy migration path from SAP Hybris CPQ to CallidusCloud would be the icing on the cake.

Salesforce acquires MuleSoft - A Defensive Move

Thu, 22 Mar 2018 11:31:41 -0400

The News

On March 20, 2018 Salesforce announced the signature of a definitive agreement to acquire Mulesoft for a whopping 6.5 billion USD – whopping because the 2017 Mulesoft revenues have been at just $296.5 Million, albeit with a $1 billion target for 2021. The press release states that “together, Salesforce and MuleSoft will accelerate customers’ digital transformations, enabling them to unlock data across legacy systems, cloud apps, and devices to make smarter, faster decisions and create highly differentiated, connected, customer experiences.” Mulesoft is recognized by Gartner as a leader in the 2017 Enterprise Integration Platform as a Service Quadrant.

The Bigger Picture

As I have stated repeatedly before, most recently here, the enterprise software market is engaged in something that can be called a platform war. There are a few big players and some emergent players in the enterprise software market, and then we have a number of companies that come from the infrastructure side of the house. Business applications get commoditized. Therefore the platform becomes crucial in a battle for dominance. And it is not a given that there will be a dominance. Looking at the 4 big software vendors, Microsoft, Oracle, Salesforce, and SAP, they all have different legacies, strengths and weaknesses. They share one weakness, which is that their core business is in a mainly saturated enterprise market. All of them want and need to play their strengths, while mitigating their weaknesses in order to become the dominant player. Looking at Salesforce, one of its key strengths is the brand. Right or wrong, pretty much the first name that comes to mind when thinking CRM is … Salesforce. And sure, Salesforce builds good, sometimes even great, software, based on a strong business model. And where there is a need, the company is strong enough to buy leading players, like ten days ago Cloudcraze and now Mulesoft. There are some weaknesses or risks, though:

Salesforce focuses on CRM, which might end up being a corner
It is hard for enterprise level companies to scale down to become more attractive to SMBs. Salesforce addresses this e.g. with Salesforce Essentials. Mulesoft can play a role here, too.
While Salesforce is profitable, it is not that profitable with an EPS of $0.26 according to the FY 2017 annual report. With a relatively high price point this is a risk factor. Salesforce battles this by staying a thought leader, delivering best-of-breed applications, and now strengthening its integration ability.
The many acquisitions need integration, so do seamlessly connected processes that digitally transforming companies require and demand. Here Mulesoft comes into the picture.
Last but not least, Salesforce is challenged getting at sufficient data to feed advanced machine learning models. Here Mulesoft will again play a role

My PoV and Analysis

This acquisition is a defensive move – a strong one, but still a defensive one. It fortifies the position while enabling Salesforce to address some of its challenges that I laid out above. For Salesforce it is necessary, even mandatory, to be able to seamlessly integrate into the application systems of other vendors. CRM and the plethora of applications around, is not and never will be the core application any company on this planet runs. It is important, yes, but an ERP is more important. Salesforce is not an ERP company. Salesforce is closer to the saturated enterprise end of the market than to the underserved SMB end of the market. Salesforce does not have the wide and powerful access to data that the core competition has. And data nowadays is truly King. Salesforce has strong, very strong, competition. Salesforce is clearly aware of all this. And then it cannot be denied that currently there is a need to connect applications that live in different clouds. Besides becoming the default plumbing between applications that are built on the Salesforce platform(s) and acquired applications that are not, Mulesoft can become the foundation for a platform of platforms that bolsters the claim of ease of integration. The first three challenges above can clearly get addressed by Mulesoft. How big an opportunity (or threat, if this was a competitive bid) Salesforce sees can get estimated by the price the company is willing to pay. But the main reason for the acquisition seems to be around the word data. In the words of Benioff: “Together, Salesforce and MuleSoft will enable customers to connect all of the information throughout their enterprise, across all public and privat clouds and data sources …”. This statement clearly not only addresses first party data but also third party data and hints into connecting to social media. Identity, profiles, and of course consents, are a main topic here. Will we see a CIAM acquisition next? The company is clearly playing a combination of ‘best of integration’ with ‘best of breed’ game. The integration part ring fences the application part, while making them more attractive with its ability to dig into data. And oh, it also helps with the price point. Really, a strong move. Strong enough? Time will tell.

Salesforce Sales Cloud Supercharged - Einstein's next Move

Fri, 09 Mar 2018 12:17:16 -0500

The News

A few days ago Salesforce announced an update to its sales cloud that features Einstein powered predictions, insights, and productivity. The press release is linked above or alternatively you can read it below, along with some comments of mine. Salesforce is (again) addressing the three main issues that plague CRM implementations since Tom Siebel coined this term. Let me paraphrase them>

Salespeople do not find the time to do their job, which is selling. Instead they are spending an inordinate amount of time entering data that supposedly only helps their management controlling them a little more.
Sales managers do not have enough visibility into what is going on in their area of responsibility, what their team is doing (and why), whether they are doing the right thing. The same problem, of course, applies to the Head of Sales, just at a bigger scale.
Sales operations is charged with creating meaningful reports that tell the one single truth. This they need to do using data that resides somewhere, data that is distributed, instead of some central consolidated place. Data that is essentially not fully trustworthy.

Salesforce is doing this using a triple of features:

The Salesforce resident AI: Einstein to help sales persons identify the most promising opportunities to work upon
The Salesforce Inbox that increases productivity by attributing emails to the right accounts as well as connecting to the calendar
Sales Analytics to help salespeople and their management to visualize, interpret, and use the available data

The Press Release

Ask any rep what their favorite part of the day is, and chances are that their answers won’t involve the words “logging” or “data.” Ask managers what they really want from their sales teams, and I bet you that they’ll ask for more visibility into what their reps are doing and for their reps to spend more time talking to customers, building relationships. As for sales operations? They probably would prefer if answering business questions didn’t involve four systems, two excel sheets, and a pivot table. These traditional systems don’t set sales teams up for success today or in the future. In fact, having all of these disparate systems causes sales reps to spend 25% of their time logging data instead of doing what really matters -- building relationships and selling. Which is why we’re introducing a supercharged Sales Cloud Einstein. Bringing together Sales Cloud Einstein, Salesforce Inbox, and Sales Analytics, to deliver more predictions, insights and productivity gains than ever before. It’s bringing the power of artificial intelligence to every step of the sales process. So how does it all work? Great question. Let’s break it down. AI with Sales Cloud Einstein AI is continuing to take center stage, revolutionizing the way we work. With Einstein, AI prioritizes focus on the most critical areas to help every sales rep increase their productivity and win rates. Features like Einstein Lead Scoring can turn mountains of data into critical signals that have the power of identifying the leads that are most likely to convert, and Einstein Opportunity Scoring can identify a poorly-performing opportunity proactively so a sales rep can keep it on track -- before it falls off. Einstein Opportunity Insights give reps the ability to address at-risk deals and learn best practices from the most successful ones. And, when reps are armed with the right insights about their accounts’ businesses, conversations become more efficient and effective, enabling reps to sell more. Productivity with Salesforce Inbox Did you know that on average, sales reps spend 64% of their time on non-selling tasks like data entry? With Salesforce Inbox reps can maximize the time they spend selling by taking advantage of automated data capture--all of those emails are logged to the right records, automatically. With built-in email productivity, reps can eliminate the hassle of scheduling meetings. Plus, they can see their top email priorities, right on their phones, and, get visibility into their opportunities, leads, accounts, and contacts. Reports and Dashboards with Sales Analytics Instead of exporting, collating, aligning and analyzing, sales teams can just click in to built-in analytics, with ready-made dashboards that make it easy to understand and explore whitespace and team performance. Reps can uncover pipeline trends, and take action immediately. Sales leaders can understand how the team is functioning across regions and products, and identify top sellers, as well as those that may need more coaching. And, it’s easy to analyze deals from lead to close with over 40 out-of-the-box KPIs. By combining all three products, we’re able to create a Sales Cloud Einstein that is a predictive data scientist for every sales team. A constant companion that drives productivity through efficiency and insights. No more point systems, no more multiple contracts, no more copy-and-paste, no more switching. Just a clean, easy, modern solution to make every company a smarter, more efficient, more productive, customer-focused company. Sales Cloud Einstein (now including Salesforce Inbox and Sales Analytics) is priced at $50 per user, per month. Click here to learn more about Sales Cloud Einstein.

The Bigger Picture

Artificial intelligence / machine learning will continue to permeate business applications. The good news is that there is less and less talk about AI, if not in a kind of personal way, like Einstein or Leonardo (and yeah, I know that Leonardo does not only cover AI). This shows that the big vendors are more and more going away from a technology narrative to a results narrative. AI is not a means by itself but a means to an end. And this end is doing more with less effort.

My PoV and Analysis

By addressing these three pain points of sales teams Salesforce is partly using some pages out of the Nimble playbook. Especially the mobile app for the Salesforce Inbox looks remarkably familiar to me. I do not say that this is a copy, but that moves like this one are actually inevitable, and that CRM (and CEM) solutions will become ever more similar. The combination of these three features and how they are laid out now tells the same story that I heard about the same time from clari, a company founded in 2013 and that focuses on “transforming the way they sell, make decisions, and grow”. Now, SAP, Oracle and Microsoft are telling the same story. This, along with the observation that even small companies are more and more referring to the term platform, reiterates that business applications are commoditizing fast and that the main battleground is becoming the fabric of a business, i.e. becoming the platform of choice. For Salesforce this is an important move as, all Salesforce “hype” taken away, there is a perception out in the market that the Salesforce architecture is aging. On top of this Salesforce is not a bargain (judging by the list prices) nor is the company riding on a high profitability. And the other 3 of the big four can tell end-to-end stories that cover the full value chain. Plus all of the big four are clawing their way from the enterprise market down to the midmarket and eventually the smaller businesses, which is the place where the opportunity lies. With that, Microsoft, Oracle, and SAP being able to tell a story of a more modern platform, and being attacked by small and nimble players that can ride on Salesforce’s and other platforms, Salesforce needs to continue to show that it is on the forefront of innovation with the benefits of all user groups in mind. I think that this worked out fine with this release. Salesforce is at least on par with the competition. But is this a super charged sales cloud? No, it isn’t. Unless the previous engine was seriously underpowered – which it wasn’t. The race towards becoming the platform of choice continues.

Sharing Economy - A Rant

Mon, 26 Feb 2018 04:34:39 -0500

In the past weeks I have been to some events. Their main topic has been ‘digital transformation’, which is a term that currently gets used all over the place. The good news is that people mostly seem to have understood that digital transformation most of all is a business transformation, with IT being an enabler, not a driver. However, and that’s the bad news, one term popped up everywhere like a bad charm.

Sharing Economy

And the usual suspect companies are cited as the trailblazers of this sharing economy:

Airbnb is apparently the biggest hotel chain. But it does now own a single hotel, rather than a bed
Uber, the biggest taxi corporation. It does not own a single taxi

I even heard Amazon and Alibaba being mentioned in this context. And then there are plenty more companies that one could mention, like TaskRabbit, Lyft, Zaarly, you name them. There are few terms that make me flinch like this one, maybe ‘democratization of . Why? Because the term does not describe the concept behind the model. Instead it creates a cozy feeling of perhaps doing something good by sharing one’s possessions with someone else. The Oxford Dictionary defines the verb share as ‘have a portion of (something) with another or others’. Sharing in its original context is about jointly using or enjoying something, in a wider sense it is about giving someone else access to something. In any case it has some altruistic touch to it. What the above mentioned companies are about is, positively speaking, helping me to give access to something that I have, be it a room somewhere else or a cab ride, or my skills. They are platforms, or market places; and the economy that they are defining is a platform economy. And mostly, they are not doing it from an outside-in view but from an inside-out view. Uber does not care whether the drivers that offer their services via the Uber platform are well off or not. Uber certainly does not want the drivers as employees, but looks at them as independent contractors. Airbnb has long ago ceased to be a place where people gave access to their place, just because they do not need it for some time. Instead, it is a place where renters seek to generate revenues, often as a business model. I did it, too. For the record: I also paid taxes on the revenues. Admittedly, using these companies customers can often get what they need cheaper, and regularly with a better customer experience than traditional service providers offer. However, apart from curiosity, the main driver for their adoption stays the price on the demand side, and the promise of (easy) revenue on the supply side. How do they achieve this? By outsourcing cost of providing the actual service while charging for providing access to it. Which again shows that these companies are not about sharing but about being the man in the middle. They are offering a platform. And platforms are about controlling products and services that get commoditized – or about commoditizing them. This commoditization may be of business applications, of taxi rides, overnight stays, of a carpenter’s services. Platforms are about dominance, dominance in the own eco system as well as across them. Don’t get me wrong. Platforms and platform businesses are not vile per se. Good platforms are mandatory for businesses to be able to provide customer- and employee engagements that are geared towards delivering great experiences. But a platform business is about the platform and is not equal to sharing economy. And the business that those trailblazers are involved in is about the platform, and nothing else. We all should keep this in mind.