Doug Henschen on Analytics, Big Data & Smart Apps
Salesforce Analyst Summit 2016 highlights Wave Analytics Cloud makeover and work in progress on the Internet of Things strategy and Salesforce Thunder.
Salesforce has successfully rebooted its Wave Analytics Cloud. It’s also apparent that company is trying to avoid the sorts of missteps that plagued Wave as it prepares Salesforce Thunder and the Internet of Things (IoT) strategy.
These are my two key takeaways from the January 5-7 Salesforce Analyst Summit in San Francisco, where executives discussed the company’s strategy and laid out product roadmaps for 2016. Execs also acknowledged some of the mistakes that were made in the launch of Wave, which was introduced 15 months ago at Dreamforce 2014.
The first iteration of Wave was basically too expensive, too enterprise focused and packaged too much like a traditional BI platform. Starting with a platform (rather than pre-built apps) was essential, execs here insisted, because partners and customers would ultimately want and need a way to build vertical-industry and custom apps. But the market balked at the cost and complex packaging of the first-generation offering.
The second generation of Wave, introduced in September at Dreamforce 2015, is greatly simplified. For starters, Salesforce ditched separate Builder and Explorer licenses (priced at $250 and $125 per-user, per-month, respectively) and settled on an all-purpose platform license priced at $150 per user, per month. The company also introduced Sales Wave, the first of several planned prebuilt apps priced at $75 per user, per month. The apps are designed to speed and simplify deployment with user- and task-specific data flows and dashboards and templates for customizable analyses and actions.
Sales Wave templates, for example, provide a head start on analyzing sales levels, team performance and pipeline health. Prebuild historical analyses assess revenue by quarter, year-over-year rep productivity, and the length of sales cycles, among other measures. Administrators can set up triggers for recommended actions, such as resetting forecasts or prioritizing deals.
Detailing the Wave roadmap for 2016, Stephanie Buscemi, COO of the Analytics Cloud, said the previously announced Service Wave app will be available in April while a Marketing Wave app is in development. On the platform front she said Salesforce is working on a data-connector framework as well as scheduling capabilities and self-service data-prep options for Salesforce data.
MyPOV on Salesforce Wave
I believe Salesforce is finally on target with Wave’s packaging, pricing and a tighter, clearer focus on offering what Buscemi called “the best analytics option for Salesforce.” Some of the original attractions of Wave, including its user-interfaces and native mobile apps, still stand apart. And from what I hear about the appeal of prebuilt Wave apps (both from Salesforce and from customers), I expect the Salesforce Wave reboot to be a success.
Stay tuned on this front as Salesforce recently hired Microsoft veteran Bob Stutz to service as Chief Analytics Officer. Stutz won’t start until February, but I’d expect more tweaks to Wave as soon as April if adoption isn’t building as quickly as Salesforce would like. Keep in mind that third-party vendors BIRST and GoodData, among others, have been working on their versions of “the best analytics for Salesforce” for quite some time, but they would stress that they can provide insight beyond Salesforce.
Salesforce Thunder and the IoT Strategy
Salesforce announced its IoT Cloud Powered by Salesforce Thunder at Dreamforce 2015. The company even announced initial customers, but at that stage Thunder and the IoT Cloud were nowhere close to testing, let alone general availability. Last year I predicted we wouldn’t see Thunder until Dreamforce 2016, and based on IoT presentations and discussions at the Analyst Summit, I’m convinced that timing will hold.
What’s taking so long? Well, for starters, Thunder had its first customer pilot tests over the recent holidays, according to Adam Bosworth, Salesforce’s Chief Strategic Officer, who is spearheading the development of Thunder and the IoT Cloud. (Bosworth is a storied veteran of Microsoft and Google who’s “a Johnny Appleseed of sorts in the tech industry,” according to a recent profile in the New York Times.)
Bosworth stressed at the Summit that the company “has many months to go” before Thunder and the IoT cloud will be ready. For now he says he’s asking early customers “lots of dumb questions,” like how they intend to make money off of IoT. With so many firms “wallowing” with big data investments, he said Salesforce is intent on starting with practical, revenue-driving use cases.
Salesforce Thunder was described as a kind of enterprise service bus capable of handling high-scale batch data as well as data streaming at rates in excess of 50,000 events per second. Thunder is based on open-source components including Kafka, Cassandra and Spark, but the point is not to establish Salesforce as an IoT infrastructure player.
“When we work with industrial, automotive and connected-device companies, what they are lacking is a way to drive [IoT] adoption,” said Alex Dayon, president of products. “We have to connect IoT with the customer business processes. Our value proposition is to bridge the IoT world – the signals from the machines — with the experience of the customer.”
Talking to execs at the Analyst Summit, it clear that there’s still internal debate about just what Salesforce will deliver with its first-generation IoT offerings. There’s a real danger with IoT offerings, said Bosworth, that customers will expect much more than what companies will be able to deliver. He cited the example of his wife’s connected car, which needs to go to the shop much more frequently than his much older analog car of the same brand. What’s more, the dealer never offers predictive insight into what’s wrong with his wife’s car even though the vehicle is loaded with so-called “smart” sensors.
MyPoV on Salesforce Thunder and the IoT Cloud
Meeting high customer expectations is one challenge. But Salesforce also has formidable internal technical obstacles to overcome. For example, overnight data latency is currently the standard where Wave insights are concerned, while cutting-edge deployments have reduced that data-update latency to about one hour. The trouble is that many IoT scenarios will demand near-real-time analytics, and that’s something Salesforce is still working on.
Dayon and others said the company’s IoT play will be initially be focused on CRM-centric use cases, but in my book, big-data scalability, streaming-data processing and related analytical capabilities all have to be there as Wave and IoT platform-level capabilities. It’s another area where Salesforce will have to decide what it can should offer itself, what it can leave to partners and where, in future, it might have to rely on hyper-scale cloud partners such as Amazon or Microsoft Azure.
We’re venturing deeper, here, into questions that relate to the future of the entire company (and why there was talk of a Microsoft acquisition last year). Where our data-to-decisions research is concerned, suffice it to say that Salesforce has to do more than dabble with IoT and data-science capabilities.