HPE debuts new Opportunity Engine for fast AI insights

Using trillions of data points this cloud-based machine learning platform can provide the optimal IT solution in seconds.

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HP Enterprise has announced what it calls the Software Defined Opportunity Engine (SDOE), a cloud-based machine-learning platform that enables partners that sell HPE gear to cut the time to create custom sales proposals from weeks to just 45 seconds.

In a blog post announcing the service, HPE Storage senior vice president and general manager Tom Black said SDOE does away with an outdated IT infrastructure-buying process at a time when digital transformation has never been more critical.

“With our new SDOE tool, customers receive fast, tailored quotes, informed by real-world data based on their own IT environment, to optimize their infrastructure and accelerate their digital transformations,” Black wrote.

SDOE is for both HPE channel partners and customers alike. It takes a snapshot of the customer’s workloads, configuration and usage patterns to generate a quote for the best solution for the customer in under a minute. The old method required multiple visits by resellers or HPE itself to take an inventory and gather usage data on the equipment before finally coming back with an offer. That meant weeks.

SDOE uses HPE InfoSight, HPE’s database which collects system and use information from HPE’s customer installed base to automatically remediate infrastructure issues. InfoSight is primarily for technical support scenarios. Started in 2010, InfoSight has collected 1,250 trillion data points in a data lake that has been built up from HPE customers. Now HPE is using it to move beyond technical support to rapid sales prep.

“Some months back, I looked at the team and said, look, if we know that much about our customers and their systems, why don't we tap into that data lake and use that to, to basically, auto create a suggested upgrade path. So we did that. It taps into InfoSight data lake as well as our services data lake to understand kind of where people are in their service contracts. And it completely changes the go to market model for us, our partners and our customers,” Black told me.

So instead of numerous visits to get an inventory and determine what best suits the customer, SDOE taps into HPE’s quoting system that sellers and partners uses and generates a legally binding quote, and then takes all that information and delivers the pitch, usually it's a six to 10 page Word document or more in PowerPoint that describes for the customer, what is the proposal, here's your upgrade options, whether it's outright purchase or if GreenLake metered use will better serve the customer, he said.

While SDOE is based on HPE’s installed base of storage and servers, a second piece of the puzzle comes from the recently acquired CloudPhysics assessment tool, which analyzes on-premises IT environments much in the same way as InfoSight  but covers all of the competition as well. It then makes recommendations for cloud migrations, application modernization and infrastructure.

The CloudPhysics data lake—which includes more than 200 trillion data samples from more than one million virtual machines—combined with HPE’s InfoSight can provide a fuller picture of their IT infrastructure and not just their HPE gear. The CloudPhysics deal has just closed, and there HPE needs time to integrate its data lake with InfoSight, according to Black.

Black said currently SDOE is just for storage systems. “You know, we will evaluate down the road, how to expand that I don't want to comment on other businesses and their current engagement level, but it's proven to be extremely powerful. We did pilots late last year, and we found that the proposals generated as reviewed by our top-tier solutions, architects in the field had 95-plus% accuracy. The sellers love it, the partners love it,” he said.

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