To outsource or not to outsource…

Posted in: Business Insights

“Should we be outsourcing part of our IT operations?”

It’s something companies have been asking themselves on and off for the past 20 years. While the question hasn’t changed, the considerations that go into answering it sure have.

In the past, the primary driver of outsourcing was cost efficiency. What could be moved out-of-house for what savings, and were the risks manageable enough to make it worthwhile?

Things have gotten much more complex in the past several years with the massive growth in data and its corresponding rise in value. Today, data is widely regarded as an organization’s most valuable strategic asset. It’s the driver behind product and service development, the key to forecasting trends, and the tool for illuminating new opportunities.

This high-volume, highly valuable data requires active, strategic management, with an increasingly sophisticated IT infrastructure to handle it. Understandably, organizations have some anxiety about entrusting this corporate gold to an outsourced provider. Which is why many choose to keep data management in-house.

The proverbial “double-edged sword”

In-house data management demands many things, talent first and foremost. Sound data management requires a team of experts with in-depth knowledge of how to capture, store, manage, analyze and utilize data and maintain all the associated systems and applications.

Finding the right people at the right skill level — with the right breadth of capabilities — can be an enormous challenge. Yet if you don’t find those people, you risk sub-optimal performance from your data infrastructure as well as underuse of the data itself. In the worst cases, the result can be system failures or security breaches, causing downtime, revenue loss and reputational damage.

That brings us back around to the outsourcing question again. If the right resources are too hard to keep on hand in-house, can an outsourced model fill the gap?

The answer to that question depends on what outsourcing model you’re talking about — and what you want to get from it.

New expectations, new implications

It’s not only companies’ data environments that have become more complex. Their goals in relation to those environments have, too. Which means any outsourcing model has to deliver on an increasingly sophisticated set of expectations: better service quality, higher productivity, access to specialized skills, increased innovation — with security, scalability and agility non-negotiable conditions.

Many organizations look at the traditional “offshoring” outsourced model and wonder if it can meet all of these new expectations. And the truth is, it can’t. But there are other approaches to outsourcing that can.

In my next blog, I’ll compare the various outsourcing options and their pros and cons.


For an in-depth look at choosing the right outsourcing partner, download our white paper.





About the Author

Lynda Partner is a self-professed data addict and experiences the power of data every day as Pythian’s Vice President of Analytics-as-a-Service. The author of Pythian’s Love Your Data mantra, Lynda understands very well how data can transform companies into competitive winners and she was the driving force in adding an analytics practice to Pythian’s database focus. Lynda works with companies around the world and across industries to turn data into insights, predictions and products, and is the co-author of Designing Cloud Platforms.

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