Revisiting show season
Show season changes the CRM market, it always does. One day you’re in the vanilla application software space and a week later you understand the need to incorporate social media, or analytics or machine learning or you see a need for enhanced integration and development through platform services. It goes on.
Today, in the wake of Oracle, Salesforce, Microsoft, and many other companies’ trade shows, we’re again taking a look at the available suites. But this time, we need to think less about what’s been added and how well integrated the components are.
With Oracle now a year into rolling out its cloud strategy, we can’t say we’re in cloud computing’s early days any more. We’re in a race to computing as a ubiquitous utility like electricity, water and natural gas.
Oracle was the last cloud holdout, the last company that led with its legacy on-premise products. Today they’ve reinvented themselves to offer infrastructure, platform and applications or any combination as services. They might talk a good game about supporting legacy customers forever, and that will be necessary, but they’d like nothing better than to convert the legacy base to cloud infrastructure. And make no mistake about it new cloud based apps is the eventual goal. Much the same is true of Microsoft whose end user products like Office are now being delivered by subscription even if some of the software still resides on the desktop.
Salesforce was, of course, born in the cloud and it hasn’t suffered through a transition though for almost 20 years it has been undeniably causing one. The disruption impacted everyone else but the next disruption, or whatever we’ll call it, is affecting even Salesforce. With typical poise Salesforce is taking it all in stride and is even taking a leadership position.
The disruption turns form purely delivering technology to focusing on how it is used. The focus is very important to Salesforce and all the others because it will have a direct impact on how much of its services (we used to call it software but this is now) get bought and deployed.
So we see increasing emphasis on learning how to develop apps and administer them even to the point of opening up the training platform, Trailhead, to enable partners to develop training programs for their custom apps.
In the background there’s also an effort to standardize on processes that deserves attention. Back in the day, a process was carved in stone. Your organization used a 7 step sales process or maybe a 5 step one. Introducing a 7-step process into a 5-step organization was enough to set off a riot. It was something you did only very carefully if at all. In that era there were sales methodology companies (still are) and there were software companies and each would tell you their products were agnostic. They were too, with a little coding.
But today it’s different. The introduction of AI and machine learning has made both methods and applications secondary. Yes they’re still important but, no, they don’t rule the roost. Everywhere sales people seem to be sidestepping the argument about which method is better in favor of adopting an attitude of doing what the AI system suggests is the next thing needed to advance a deal. As it should be.
Platform based CRM with robust partner communities and their apps have brought us to the point of fully integrated and automated business processes. Customization has never been easier thanks to the platform too. The next step in our journey will be inventing new business processes that derive from our need for, and attempt to be, more agile, to flexibly approach new opportunities.
That’s what has been most interesting to me about show season. Each vendor has, in it’s own way, made a tacit nod to the primacy of data and analytics for automating processes. In that event, they’ve also begun closing the door on business processes that momentarily pop out of the automation sluice and into a spreadsheet or other manual thinking.
The change isn’t only recognizable in sales though selling is a big beneficiary with solutions that include SFA, CPQ, admin functions, AI, ML, compensation management and gobs of graphically rich reporting. Marketing is a rich area with its newfound abilities to identify, target, hand off, score, and journey map. And service has its own rich tool set most significantly analytics married to multi-channel abilities to take customers from beginning to end of a support journey without necessarily bringing in a human.
In all of this businesses are freeing up employee time for higher-level tasks that add value to customer experiences well beyond getting a deal or a right answer. This is where the customer facing jobs of the future will come from. They will demand more and different people skills as well as technical mastery.
That’s why this show season has been a turning point. I think it will be looked back on as the time we began a more disciplined approach to customers and employees as people who interact with technology, not just as various flavors of technologists.
Digital hub returns
Digital Hub is not a new idea, it’s been percolating for a few years and its roots can be traced to Dublin, Ireland where, in a cluster of 8 buildings, there’s what might be the original hub. In Dublin it’s made up of 97 companies employing 725 people and it was given a jumpstart by the government in 2003. Elsewhere we might be more attuned to the idea of a tech incubator.
Fast forward, to today and half a world away in Kuala Lumpur, Oracle has employed the hub concept to label its SME incubator and for good reason. More than two-thirds of the world’s total micro and SME market is in the APAC region equal to 266 businesses, according to an article, ”Oracle Corporation opens digital hub in Malaysia” in The StraitsTimes.
According to Oracle managing director of Malaysia Fitri Abdullah, “The KL digital hub is set to leverage Asia Pacific (APAC)’s small and medium enterprises (SMEs) immense growth through providing our Oracle Cloud solutions to streamline operations, boost innovation and build a platform for growth.”
All well and good—and timely too—with Oracle OpenWorld happening next week. Oracle has learned the lesson of its main rivals for supremacy in the cloud that, in addition to creating product (supply), it also needs to create demand, which would seem to turn a foundation of economics on its head. Say’s law states that supply creates its own demand but the literal meaning of the term might not be what applies.
It is true that supply of new category products and services creates its own demand. Often customers aren’t even aware of their need until a product shows up that demonstrates a void in life. For example, how many people really knew they needed an iPhone before it was announced in 2007? By the same token how many businesses knew they needed cloud computing before Salesforce introduced its product in 2000? I was there and I can tell you, not very many at all. Businesses were crying for enterprise software that was easier to install and maintain and that didn’t cost the equivalent of the GDP of an emerging nation. Cloud computing provided that and these attributes are why the cloud succeeded initially.
But now, many years later, the bloom is off the rose, and while I think Say’s law still operates quite well under the right conditions, it doesn’t operate in cloud computing because supply is ubiquitous. Time to focus on demand. We know the cloud and most of us don’t even consider it as risky as having data under the control of a corporation. Just look at Equifax and all of the other data breaches over the last few years, they’ve nearly all been breaches of in-house data centers.
But back to Oracle. Good on them that they’re recognizing the need to generate their own demand in this key segment. We live in a different and later part of the cloud computing cycle, a time when cloud isn’t new or unique. It’s a time when the cloud has been proven better than what it replaces; a time when price concerns are a big part of decisions. With price concerns comes commoditization and automation as cost cutting measures and the soon to be announce Oracle autonomous database is a great example of those trends. There’s a stampede to the cloud happening right now. Perhaps it goes by the name of digital disruption but it amounts to the same thing and low cost producers are in good position to dominate.
I don’t know whom but Oracle will soon have competition in Kuala Lumpur. According to the Oracle story in New Straits Times, another large company (I’m guessing American) will launch another hub there in October. No names yet but if you need some ideas just check out the incubators along Route 101 south of San Francisco.
Finally Oracle
Denis Pombriant, managing principal, Beagle Research Group, LLC
Oracle’s Q1 earnings announcement showed some very good numbers. Overall the company, beginning its second year of aggressive cloud promotion, is showing significant year-over-year improvements thanks to its turn to cloud infrastructure, applications, and platforms. But the numbers, read right, announce the end of the beginning of the end, of sorts, as much as they announce the end of the beginning.
Oracle is the last major software vendor to adopt the cloud as its primary medium, and while it will support its legacy customers as long as necessary (it has a good history of loyalty to customers in this regard) there’s no doubt about its direction. With a legacy installed base, moving to the cloud has been more difficult for Oracle than it has ever been for companies like Salesforce or NetSuite which were both cloud natives from day one.
To make its pivot, Oracle has had to spin up three businesses, one for infrastructure, IaaS, and one each for SaaS and platform (PaaS). Infrastructure is a low margin business because there’s a lot of low priced competition but it’s essential to the company’s strategy because there will be a fraction of its 425,000+ customers who get to the cloud by first only moving locations of their data centers. Without an IaaS business, those customers could go anywhere and keeping them in the software fold would become more difficult.
Oracle’s transition to the cloud removes the last legitimate holdout, the last objection to cloud computing almost anywhere, and with that we can call a top to an age of computing that began with mainframes more than 50 years ago. The logical question now is what’s next? The rest of the industry is not standing still and along with transitioning its customers to the cloud Oracle is continuing to invest in advanced technologies like AI, machine learning (ML), and IoT where it competes with most other vendors.
At the same time that Oracle is competing, it is also leading in database and some of its competitors are also customers. During the earnings call with press and analysts, former CEO, founder and current CTO, Larry Ellison offered a preview of Oracle OpenWorld, which will run during the first week of October in San Francisco. Ellison announced that the next version of the Oracle database would be automated so that better than 99 percent of set up and tuning could be done by the system itself using AI and ML.
So I’m calling another top, in another part of Oracle’s business, database. Most of the competition from the early days of relational databases has either departed or been absorbed by larger entities and Oracle may be the only fully independent vendor left (I can’t think of anyone else). The database industry, along with satellite industries in various forms of hardware, software, and services, once formed the backbone of a major economic driver, the tech industry. In its hayday the industry employed (and still employs) a huge number of people. But with the introduction of an automated database, coupled with an already strong cloud sector, we can see a good deal of automation and commoditization happening that, among other things, is cannibalizing itself, erasing jobs and commoditizing products based on databases.
There’s nothing to be done about it. Business runs on information but it also runs on efficiency and cloud computing and automation are part of a never ending quest to keep overhead low and profits high. The more important question for now is what’s next? What will be the next disruptive innovation, the thing that drives the economy and that hires lots of people and deploys new infrastructure.
Many people figure the next shift will look a lot like today and think IoT and things derived from it might be next in line. I don’t know. Viewed in a certain light, the IoT looks more like a further commoditization and automation of traditional technology than it looks like the next big thing. After all, the IoT is supposed to be about automation using the Internet to communicate between remote devices with sensors and the mother ship for the purpose of dispatching services and supplies, among other things. It’s hard to see how this would lead to a great expansion in employment though it certainly looks like a way to improve capital efficiency and profits.
For the moment, it’s enough to understand that the next major economic move will stand on the shoulders of the current paradigm and that it will be steeped in technology. Iron and stationary steam engines gave way to steel and mobile steam engines. The next decades are likely to look like the cutover from iron to steel. It will be an interesting time, as the Chinese say.
Adaptive Intelligent Applications
Oracle jumped into the AI and machine learning space for its CX products (a.k.a. CRM) and other applications like HCM at OpenWorld with an interesting difference—a huge data store to help educate the algorithms that work for you. Now we’re waiting for products to be delivered this year.
Machine learning depends on data about prior situations that the learning algorithms can use to get smart about a situation. Ten examples are good, 100 are better and generally the more samples there are the more refined a recommendation can be. That’s why machine learning never really ends. Like a great player or team, the learning and practice never stop and neither does the improvement. But it’s worth understanding that improvement beyond a point of basic competency will slow down regardless of what you’re modeling.
When you’re a kid you can make great strides in almost any sport but as you progress those strides become smaller and they’re harder won. Consider Olympic swimming or track and field where athletes try to shave fractions of seconds from world records. Often the difference between gold and silver can be an arcane difference in technique.
In business and machine learning, algorithms don’t stop learning for a very good reason—every new bit of data suggesting some fractional difference could be the harbinger of an evolving trend and the only way to stay abreast of that evolution is to stay current with the data. So you can quickly see that data is critical to the success of machine learning and that’s a big deal because few organizations possess all of the data they would ideally need to feed the algorithms that drive decisions.
Moreover, data quality is also a major issue and while a business might hold a great deal of customer data, its quality or lack—the duplications, misspellings, ambiguous designations, and incompletions—have, for years been the bane of data scientists and analytics users wanting to get information from their data.
Data quality is one thing that will distinguish Oracle’s Adaptive Intelligent Applications. Scheduled for delivery soon, Adaptive Intelligent Applications will work with customer data as well as Oracle’s Data Cloud, a collection of more than 5 billion consumer and business profiles, with over 45,000 attributes. The combination of a business’s specific customer data combined with this third party data will yield important insights that are unique to a business and its customers.
Businesses have always sought out fine differentiators like these solutions can provide to separate them and their rivals. Depending on the stage of market evolution that could mean product differentiation, value added services, product line extension—almost anything. The problem with all of these approaches is that they’re superficial. It’s all vendor, brand, or product centric because that’s all that a business could control prior to the development of very powerful computing and modern analytics and machine learning. If you wanted to peer into the mind of your customers you had to rely on gut feel—usually that of an executive who’d been involved in the industry for a long time.
The trouble with gut instinct is that it’s often wrong. The research that led to a Nobel Economics Prize for Daniel Kahneman—see Michael Lewis’s new book, “The Undoing Project”—shows that the rules of thumb or heuristics that we use in every day fast decision-making are often wrong or reveal a bias. Interestingly, since machine learning is definitely not human, it can avoid heuristics and biases and work the way we work when we concentrate and work slow and perhaps use pencil and paper. But the point of machine learning is to have the benefits of thinking slow and with a pencil but without having to do the work. In the process, machine learning is able to reach more users and prevent more incorrect assumptions from coloring business decisions.
To be clear this does not amount to a one size fits all approach to analytics. The Adaptive Intelligent Applications that Oracle has built also come with supervisory controls that enable users to fine tune their analyses to the specifics of a business’ needs. So the power of Oracle’s Adaptive Intelligent Applications will come from its well-crafted algorithms but also its Data Cloud. But the fact that it might prevent users from using an estimate or rule of thumb might turn out to be just as valuable.
Trump to hold tech conf; I am holding my breath
I swear I was getting through this and trying to move on. She wasn’t my favorite candidate but when you consider the alternative she looked like George Washington in a pantsuit. Like many people I had moved on from denial and anger to Elizabeth Kubler-Ross’ next stage in the grief pyramid called bargaining. He can’t be that bad…they can tame him…I’m going back to work, he can’t chase me there…I’ll be okay.
But noooo! A brief story in the New York Times today says Donald Trump, incipient POTUS is planning to hold a technology conference next week. It’s right here under this headline, “Trump Plans Technology Conference With Silicon Valley Executives.” The article by David Streitfeld, Maggie Haberman, and Michael D. Shear covers a lot of ground what with Trump also seeming to have cancelled the next generation of Air Force One today, which is also in the piece.
Says the article, “The list of those being invited was not immediately clear, but they could include Mark Zuckerberg of Facebook, Timothy D. Cook of Apple and Sundar Pichai of Google.” Sure, that’s right, Silicon Valley CEOs have nothing scheduled that far out so of course they’ll all trudge over to Trump Tower. Whatever it is, when a president asks for your time, he’s doing it in the name of all the American people so you more or less have to attend.
The one saving grace in all this might be (and we really don’t know all the details yet) the fact that these are all consumer technology mavens so far. Maybe Trump has a punch list of social media enhancements to go over or maybe he intends to build a wall between our electrons and the rest of the world. Or maybe Trump just wanted to call a fly-in for rich guys to compare private aircraft. His is bigger, you know.
Regardless, I’ll withhold judgment on Trump’s tech chops until I know if this is just show and tell for social media or if he really wants the skinny on what to expect in areas like machine learning, AI, the IoT, and a half dozen other techno-wizbangs that will rock his world soon. I’ll begin to worry when Ellison, Benioff, and Gates get summoned.
