How to address Big Data as a whole rather than a sum of parts

A new study by CA reveals that while organizations know better than to silo Big Data there also isn’t a clear-cut way on how to integrate it with other lines-of-business.

If you want to get up to speed on a company’s financial outlook, you might get directed to the CFO’s office. If you want to know about who’s getting hired or promoted, the details are probably somewhere within Human Resources. If you want to understand what the company’s customers really want and how to better serve them in the future, you could be walking around for a long time before you’d ever find a similar office for Big Data.

Although some banks and other large enterprises have appointed chief data officers or hired data scientists, many leading companies have them closely tied into existing teams. They know better than to put Big Data into a new operational silo. In fact, the dispersed nature of information and expertise in some organizations could be the one thing that makes Big Data an increasingly big problem, rather than a big opportunity.

Lack of integration

According to a recent Vanson Bourne study, “The State of Big Data Infrastructure: Benchmarking Global Big Data Users to Drive Future Performance”, 27 percent of respondents cited organizational complexity as one of the top five major obstacles to overcome for successful Big Data project implementation.

Despite these obstacles, 84 percent of large organizations either have or plan to implement a Big Data project within the next year. However, the majority of Big Data projects are independent, with one in five organizations having a project limited to a single department or area.

Managers cited the following key drivers for Big Data projects:

 

Data management has always been challenging in the enterprise, with details about customer interactions, for example, spread across myriad systems and pieces of the organization. There has long been a hope to get a “single version of the truth” about who has purchased what, and why, and how those customer relationships can be maintained. Big Data introduces further complexity because it’s about getting insight to unstructured data, such as social media data, which in many cases is external to the organization or hasn’t been managed before.

Point projects miss the point

Big projects may start in isolation because they’re aimed at solving a particular department’s needs. Marketing, for example, may want to better understand how their brand is being perceived and discussed. Sales, on the other hand, may want to forecast demand in ways that weren’t possible before. And according to the mentioned study, more than a quarter of respondents see lack of visibility into information and processes as a potential barrier.

CIOs already know that “point” solutions that tackle just one pain point become like a bandage that eventually becomes too small to cover the wound. Similarly, Big Data point projects will inevitably become more inter-dependent as the processes around it mature.

Singling out Big Data isn’t the answer – it’s really more about holistically leveraging the Big Data stakeholders within the company from Marketing, Sales, Finance, Ops, HR and so on.

This could at least start important conversations about a more unified approach to analytics. You never know where the conversations might lead, but at least you know it’s more likely to take the organization somewhere together.

Note: The study, “The State of Big Data Infrastructure: Benchmarking Global Big Data Users to Drive Future Performance”, surveyed 1,000 IT managers and decision makers in 11 countries to benchmark the state of adoption of Big Data projects amongst global organizations. The key elements of the study focused on the complexities and challenges organizations are facing with their Big Data infrastructure and environment.

How to address Big Data as a whole rather than a sum of parts

Teaser: A new study by CA reveals that while organizations know better than to silo Big Data there also isn’t a clear-cut way on how to integrate it with other lines-of-business. By Jean Healy If you want to get up to speed on a company’s financial outlook, you might get directed to the CFO’s office. If you want to know about who’s getting hired or promoted, the details are probably somewhere within Human Resources. If you want to understand what the company’s customers really want and how to better serve them in the future, you could be walking around for a long time before you’d ever find a similar office for Big Data. Although some banks and other large enterprises have appointed chief data officers or hired data scientists, many leading companies have them closely tied into existing teams. They know better than to put Big Data into a new operational silo. In fact, the dispersed nature of information and expertise in some organizations could be the one thing that makes Big Data an increasingly big problem, rather than a big opportunity. Lack of integration According to a recent Vanson Bourne study, “The State of Big Data Infrastructure: Benchmarking Global Big Data Users to Drive Future Performance”, 27 percent of respondents cited organizational complexity as one of the top five major obstacles to overcome for successful Big Data project implementation. Despite these obstacles, 84 percent of large organizations either have or plan to implement a Big Data project within the next year. However, the majority of Big Data projects are independent, with one in five organizations having a project limited to a single department or area. Managers cited the following key drivers for Big Data projects: • Improving customer experience (60 percent) • Acquiring customers (54 percent) • Keeping up with competition (41 percent). Data management has always been challenging in the enterprise, with details about customer interactions, for example, spread across myriad systems and pieces of the organization. There has long been a hope to get a “single version of the truth” about who has purchased what, and why, and how those customer relationships can be maintained. Big Data introduces further complexity because it’s about getting insight to unstructured data, such as social media data, which in many cases is external to the organization or hasn’t been managed before. Point projects miss the point Big projects may start in isolation because they’re aimed at solving a particular department’s needs. Marketing, for example, may want to better understand how their brand is being perceived and discussed. Sales, on the other hand, may want to forecast demand in ways that weren’t possible before. And according to the mentioned study, more than a quarter of respondents see lack of visibility into information and processes as a potential barrier. CIOs already know that “point” solutions that tackle just one pain point become like a bandage that eventually becomes too small to cover the wound. Similarly, Big Data point projects will inevitably become more inter-dependent as the processes around it mature. Singling out Big Data isn’t the answer – it’s really more about holistically leveraging the Big Data stakeholders within the company from Marketing, Sales, Finance, Ops, HR and so on. This could at least start important conversations about a more unified approach to analytics. You never know where the conversations might lead, but at least you know it’s more likely to take the organization somewhere together. Note: The study, “The State of Big Data Infrastructure: Benchmarking Global Big Data Users to Drive Future Performance”, surveyed 1,000 IT managers and decision makers in 11 countries to benchmark the state of adoption of Big Data projects amongst global organizations. The key elements of the study focused on the complexities and challenges organizations are facing with their Big Data infrastructure and environment. More from CA: Read More (link to registration page for study) Infographic link


Jean joined CA in 2014 as Vice President, Product and Solution Marketing. She previously led…

Sarah is a contributor to the CA Technologies Highlight Blog. She has over a decade…

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