Big Data: Separating the Hype from Reality in Corporate Culture

Brett MacLaren, Vice President of Enterprise Analytics, Sharp HealthCare

Brett MacLaren, Vice President of Enterprise Analytics, Sharp HealthCare

The term “Big Data” and the relatively broad spectrum of tools, capabilities, and technologies that are associated with it have created sufficient hype amongst executive councils and board rooms across the nation. The relative simplicity of the term belies the complexity of what it entails, which is the promise of harnessing all of the data your organization possesses internally, or has access to through external channels. This data plays an instrumental role in driving business value and enabling the digital transformation of your enterprise.

If only it were that simple. The precept indeed begins simply enough, as all the analog processes and workflows of the world begin to move to digital realm. Businesses should be able to take the data being created, with its ever increasing volume, variety, and velocity, and leverage new high performance technology to extract the business value and lead to improved “data-driven” decision making. In a few specific and often touted instances, particularly in companies that were digital from the start (i.e. Google, Amazon, Netflix), this has been largely successful. This requires massive investments in these enablement technologies and relatively limited human capital with expertise in leveraging them.

There is little doubt that incredible value is buried in those mountains of data, and technology and enablement vendors are quick to promise the relative simplicity of leveraging their mining equipment and services to get to all the gold within.  There's also the promise that these new tools are cheaper, faster, and better than the mining equipment most organizations have been using for the past twenty plus years to refine their data from raw materials to precious decision-driving value. The challenge is that while the tools and hardware themselves may (but not always) be cheaper, you also need people with the expertise to leverage them, while at the same time keep up with the existing demands of your business.  For most organizations this juggling act proves to be quite difficult, with some likening it to changing the tires while your car is in motion. It’s actually a bit more like adding a rocket booster to your car along with the tires you already have—you still need your existing mechanics to keep the car running, but now also need rocket scientists (or, in this case, data scientists) to be able to take full advantage of your new capabilities.

 The precept indeed begins simply enough, as all the analog processes and workflows of the world begin to move to digital realm.   

Equipped with the information, to quote Mark Twain, “there’s gold in them thar hills,” how can organizations properly work towards realizing the promise of Big Data?  The solution seems to boil down to addressing several elements critical to success, some of which are technology related. Perhaps, the most important aspect is where a majority of data and technology initiatives stagnate (or worse, die an expensive and painful death)—corporate culture.

In order to address and evolve the corporate culture to be prepared to harness the value in their data and leverage these tools and technologies effectively, it is highly recommended that an organization first designate a leadership team member to be responsible and accountable for all organizational data. Many larger organizations are filling this relatively new role with the position of Chief Data Officer, who could either report to or be a peer of the CIO. But, regardless of title and reporting relationship, this individual must rank high in the organization and hold the respect of key senior leadership. It is also important that this person not only be data savvy, but politically adept as well. A key part of this role is to evangelize to the organization about the importance of data and the ability to leverage that data to drive business value.  They typically also have oversight over data governance and data quality programs. Ultimately, this role has to play a key partnership role between the business and IT, helping both to recognize data’s critical role as the newest strategic asset of the organization.

As an organization begins their cultural transformation to become more data-centric, they must take steps to develop a culture of data awareness and promote data competency across the enterprise. As IT typically has ownership over the tools and technologies used to access and visualize data, it is critical that they develop strategies to partner with the businesses on leveraging data to implement key performance metrics to measure the success of software implementations and any business process redesign enabled by technology. This is a stepping stone to better business/IT collaboration as well as helping to prevent “shadow IT” cloud based analytics platforms from proliferating in your organization.

Big data and the tools and technologies it represents are clearly cutting edge and are still relatively early in their level of maturity, and with that brings tremendous hope (and hype) about what machine learning, deep learning, and massively parallel processing  can bring to our organizations in terms of future value and bringing data to the point of decision making. Nevertheless, for organizations to be ready to capitalize on this promise, they must first evolve their corporate culture to one that is data-centric. For example, it is widely cited that the average data scientist spends upwards of 80 percent of their efforts performing data cleansing and preparation. If organizations were more data-centric by recognizing the strategic value of their data, and included a focus on how to leverage that data, then these incredibly expensive resources could focus most of their efforts on the high performance tasks they were hired to perform. Now more than ever, the CIO and Data/Analytics leadership must focus on shifting corporate culture in the direction of prioritizing the value of their data. Only then can organizations across the nation truly realize the value promised by Big Data.

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