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April 24, 2017

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Common Barriers to Analytics Success

By John Desborough

Common Barriers to Analytics Success

The number of organizations implementing analytics and big data projects has increased but many still struggle with a number of challenges in terms of achieving the returns on investment for which they had hoped.

If you read the surveys being produced by the myriad of vendors in the marketplace, you will see that most of the organizations responding to the survey have employed data analytics. Most use analytics for IT Operations Management and for Security. Other common use cases include fraud analytics, big data analytics and IT governance/compliance.

Challenges identified by the respondents in these surveys typically include infrastructure requirements, scaling challenges, staffing requirements, expense and slow analytics/technical challenges. The 'need for speed' was highlighted across the 30+ survey results that I reviewed.

What is "fast"? For those organizations who want real-time analytics, response is required within milliseconds. The majority of the surveys indicate that "human real-time" - five seconds to five minutes latency - is acceptable.

Unfortunately, the majority of organizations identify that their current technology is incapable of delivering on the human real-time analytics. Being able to shift to real-time or machine data analytics will require most organizations to upgrade their infrastructure and to define a limited number of critical use cases that will fit within the financial parameters of their capabilities.

From a staffing perspective, the organizations who undertake real-time analytics have invested in hiring data scientists and/or several senior data analysts - and skewing their salary grids in doing so. These resources are scarce in Canada and come at a premium in the marketplace. We are seeing a lot of organizations hiring university graduates from schools that have created BI & Analytics programs specifically to develop future data scientists and aligning them with senior internal resources to mentor them in the business of the organization.

All in all, firms who have successfully launched analytics programs have taken the time to address these barriers one by one, in a series of 'pilots' that have generated positive outcomes for the organization. With each successful pilot, they have reinvested the cost savings/realized benefits back into the program. By focusing on one pilot/one barrier at a time, they have found a path to success.

For most of the organizations, across all the surveys reviewed, the biggest challenge still facing them is how to address cloud vs on-premise (or is it hybrid?) deployment of analytics functionality. More to come on that challenge in another post.



John Desborough is a Director, Consulting and Technology Solutions at MNP. He is an accomplished business solutions program manager and business transformation architect with 30+ years in the information and technology consulting domain. John has extensive background in information management and governance with both public and private sector clients on a global scale. Drop John a line to discuss this topic in more detail: [email protected]