Case Study

Cutting Enterprise Setup From Days to Minutes at IBM

IBM's big data platforms took days of on-site setup. More than 30 downloadable virtual appliances cut that to minutes, and downloads rose 75x.

Product Manager (hired as User Experience Engineer), IBM May 2012 to December 2014 InfoSphere Streams and BigInsights Growth & PLGProduct Leadership
75x
Downloads after the VM launch
13,125
Customer workdays saved on BigInsights (est.)
24
New contracts in the next 12 months

Situation

When I joined IBM in 2012, InfoSphere Streams and BigInsights could handle huge volumes of data in real time, but getting either one running took several days with IBM engineers on site. Everything at IBM still followed the older mainframe paradigm, so every new customer started with a slow, expensive setup before anyone ran a single query. That did not scale.

I was hired as a User Experience Engineer and soon moved into product management. Both platforms were part of the big data stack folded into IBM's Watson work.

What I Built

  • Ran three product rollouts on InfoSphere Streams and BigInsights, IBM's real-time stream analytics and large-scale data platforms, owning each from scope through launch and adoption.
  • Built more than 30 virtual appliances (VMs) across the organization: the product, setup scripts, instructions and a default dataset, packaged so anyone could download it and run it on a laptop in minutes.
  • Wrote the technical documentation that let anyone who downloaded a VM try the product on their own, before an IBM solutions consultant ever talked to them.
BEFORE Several days IBM engineers on site AFTER Minutes Download a VM, run it on a laptop 75x downloads after launch 16,500 customer workdays saved (est.) 24 new contracts in 12 months
Setup time before and after the VMs, and the results that followed.

The Hardest Problem

Asking why setup worked the way it did. There was no real reason; it was institutional tradition. I came in without the legacy mainframe perspective, which made the question easier to ask, and the first working VM showed there was another way.

Outcome

  • Downloads of both products went up 75 times after launch. The BigInsights VM was downloaded more than 35,000 times and the Streams VM more than 9,000 times.
  • An estimated 16,500 workdays of customer time saved: 13,125 on BigInsights and 3,375 on Streams, at 3 hours saved per download. That is a cautious figure against the several days of on-site setup each VM replaced.
  • 24 new contracts in the next 12 months, signed after sales started demonstrating the product on the VMs.

Skills Demonstrated

Enterprise onboarding and setup, product-led adoption, virtual appliance packaging, sales enablement, technical documentation.

Evaluating me for a role

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