Now that the major waves of Dreamforce 2017 have settled, the announcements and a good part of the running commentary has been delivered, it is time for me to have a look at my pre-Dreamforce predictions.
Having been briefed before the event but unluckily not been able to attend (nor having had the time to write this piece earlier, I now have the advantage of having had more ‘thinking time” and can put the main announcements that we were briefed on into a bigger picture.
On the backdrop of an IDC study (sponsored by Salesforce) that postulates 3.3 million new jobs and an overall GDP impact of 859 billion dollar by 2022 in the “Salesforce economy”, the announcements basically revolve around one single topic: How to enable the employees (of Salesforce customers and partners) to deliver to this magnitude.
They were around
· Opening up Trailhead to Salesforce customers in order to support company specific learning maps
· Enabling Lightning, as the platform to become fully themed, i.e. embrace the customers’ brands. Although technologically different I club the ability to create and easily upload branded mobile apps to the app stores into this
· Collaboration using Quip, the software that Salesforce acquired about a year ago, and a new partnership with Google
And in order to emphasize on the fact that they are serious about enabling people individually, Salesforce resuscitated the dot com prefix “my”. Thus myEinstein, myTrailhead, myLightning, mySalesforce, myIOT and mySalesforce got born.
A topic that might be slightly overlooked is covered by two sentences in the announcement of the Google partnership. “Also, Salesforce has named Google Cloud as a preferred public cloud provider to support the company’s rapidly growing global customer bases. Salesforce plans to use Google Cloud Platform for its core services as part of the company’s international infrastructure expansion.” With no further elaboration I can only interpret this as Salesforce following SAP’s multi cloud strategy.
What did I predict?
Following OOW17 and the SAP Hybris Summit in Barcelona I wrote that Salesforce is in a tight spot and that it is not nearly enough to just tick off the accomplishments that were delivered to promise. Looking at the current state trend of business systems I looked at Salesforce strengthening the eco system, adding power to the platform, and leveraging Einstein.
My point of view and analysis
While it seems that I was right on some level, there are some interesting rabbits that Salesforce pulled out of the hat.
Technology needs to serve the users and not the other way round and there are tasks that every user needs to get optimal support for. These are the tasks that need to be done often and the dull tasks that no one really needs to do. Plus, probably the tasks that no one comes around doing because of the previous two. Salesforce seems to have understood this.
Salesforce, in best Microsoft manner, enables this by creating point and click interfaces around complex technologies like (advanced) predictive analytics or IoT. The Salesforce platform also seems to benefit from Einstein permeating it more thoroughly. To me it appears like the days of separate clouds are numbered and that we are moving closer to a suite again – which makes sense as business processes extend across the boundaries of silo’ed functionalities.
I also think that Salesforce did a great move further embracing and empowering the ecosystem. There is a very clear message that Salesforce wants to stand for making it easy for their customers to focus on their customers’ needs. Whether this needed the “my” prefix or not…
By enabling developers, admins, and users, to easily create the applications that they need to more effectively and efficiently meet customer needs they are giving a clear message. On top of this there is an increasing amount of industry specific (Bolt) solutions. Extending the learning platform Trailhead to embrace customers, with branding and content, augments this. It offers Salesforce customers to build and monitor their own learning maps in a corporate environment.
Improved support for collaboration is another aspect of this. Having a platform like Chatter is one thing, leveraging an integrated platform like Quip is on an entirely different level. Quip live apps offer the promise of having all relevant data and documentation for a task in one place – kind of a Slack on steroids. Here also the new integration with the G Suite and Salesforce that will help making data available where it is needed will play its role.
With all these new and enhanced features Salesforce showcases that customer happiness is the end and that the employee is the means to make the customer happy.
The (long overdue) move to allow customers to make Salesforce applications fit into their own brand is only the icing on the cake of this message. While this capability sounds like a little thing it is actually a biggie as it fosters commitment and, so far, was a distinguishing factor in favor of Salesforce competition. It is good to see this now; and it appears to be simpler than in other tools.
All in all this is very good news for Salesforce customers and for their customers. I am looking forward to seeing more of this in action.
Salesforce seemingly starting a multi cloud strategy is an interesting development. While offering customers the in their eyes best cloud alternative (Salesforce, AWS, or Google) is a good thing, it will be interesting to see how these two competing ‘preferred’ clouds will be offered. Both parties have a genuine interest in attracting serious business workloads. It remains to be seen whether there will be a regional overlap or a distinction. It also remains to be seen how AWS reacts to this announcement.
Some words of caution
Salesforce is historically very good at showcasing complex scenarios. In sales processes against competition (especially SAP) Salesforce proves this times and again. Tools like the Einstein Prediction Builder are perfect examples for this. Being able to build a custom AI model on any field or object to predict business outcomes is a great thing. However, it is unclear how the underlying algorithm got trained or how the training got tested. Further, there are still quite some limitations. Some of them one can find out using the Trailhead Einstein Prediction Builder Trail.
As usual, and as with other companies, too, customers are well advised to look under the shiny hood that sales demos are.