Moving to the Public Cloud? Do the Math First
A manufacturing executive claims that many companies “didn’t do the math” in terms of rushing to outsource key functions to outside suppliers. Are companies making the same mistake in terms of rushing to public cloud computing infrastructures?
The herd mentality—we know it well. Once a given topic (i.e. agile development, Hadoop “Big Data” implementation, etc.) becomes the darling of business and management publications, a gold rush usually follows to implement. Unfortunately, sometimes there isn’t much, or any, thought put into gauging enterprise fit or building a business case for the latest and most fashionable idea.
Take for example the concept of outsourcing. During the early 2000s, cheap labor rates in China and India caused senior managers to see dollar signs as they could cut labor costs nearly in half, while gaining a specialized workforce dedicated to developing and building products and/or servicing customers.
There was a catch however. When considering topics such as delivery lag times, transportation costs, loss of corporate agility, language and communication barriers and more, the so-called cost savings often failed to materialize.
“About 60% of the companies that offshored manufacturing didn’t really do the math,” says Harry Mosler, an MIT-trained engineer who runs the Reshoring Initiative. “They looked only at the labor rate, they didn’t look at the hidden costs.”
The concept of shifting compute needs to public cloud computing infrastructures is an idea gaining traction. As the C-suite contemplates methods to deliver better, respond to market changes faster and reduce costs, cloud is an increasingly tantalizing option. In fact, the market for public cloud computing is said to be $131B in 2013 and growing, according to a tier one analyst firm.
While companies are choosing cloud for myriad reasons, it’s readily apparent that procuring public infrastructure, development platforms or applications from a cloud provider is really just another form of outsourcing.
This then brings some challenges to the forefront, specifically the need to understand the business case and use cases for cloud computing for your own company. And the needs must go beyond simple cost savings analysis.
Don’t make the same mistakes of those executives who rushed to outsourcing in the past decade. Tally up the cost savings, but also spend time diagnosing “hidden risks” of public cloud in terms of well-known issues of costs of downtime/availability, data security/privacy in a multi-tenant environment and data latency.
In addition, think about the level of control you want over your IT infrastructure. Are you comfortable relying on another vendor for critical IT infrastructure needs? In case of the inevitable IT failure or worse case cyber-attack, are you one of those who would want to start working a problem right away, rather than opening a trouble ticket and waiting for an answer?
You’ll also need to consider skill sets (tally those you have, and those you’ll need), in addition to architecting your various workloads for cloud infrastructures.
Please don’t get me wrong. For many companies, sourcing computing needs to public infrastructures makes a lot of sense, but when only supported by a thorough business case, and detailed risk analysis. You’ll need a thorough understanding of what you’re jumping into before “joining the herd,” especially when an on-premise solution might work better.
In other words, “do the math” (figuratively and literally).
Paul Barsch directs marketing programs for Think Big, a Teradata company. Think Big offers roadmap, architecture, engineering and ongoing support services for data lake and analytic solutions. Paul has also worked in senior marketing roles for global consultancies EDS (now an HP company) and BearingPoint (formerly KPMG Consulting). The opinions expressed here represent those of Paul Barsch, ...
Other Posts by Paul Barsch
The moderated business community for business intelligence, predictive analytics, and data professionals.