Big Data’s Growing Role in Organizational Leadership & Development

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The term big data refers to the large volumes of data that modern businesses generate including web traffic logs, social media posts, blog posts, and video content posted on sites like YouTube. Take note big data encompasses both structured and unstructured digital records. Businesses with the expertise and tools to analyze big data have a huge advantage over competitors because they can make better data-driven decisions. Moreover, they can outwit competitors strategically provided the underlying data analysis is correct.

Traditionally, all data storage and manipulation activities occurred in-house. However, affordable Internet access and proliferation of mobile devices have led to web users generating vast amounts of unstructured data. In fact, industry experts reckon that up to 90% of global data was created in the last two years only. If this growth rate holds true, the world will be home to 44 zettabytes of data by 2020. This translates to each person on Earth generating 1.7 megabytes of new data per second.

Data Collection and Analysis

Digital records collected at the organizational level can be broken down into three main categories: publicly accessible, social media, and streaming data. These data categories are growing so fast, they are expected to double in volume every two years. This has forced business decision makers to rethink their operational strategies. A survey of top executives and C-suite level executives found that 44% believe that data is a key operational tool and should be utilized to enhance strategic decision-making. In addition, 37% of executives feel data can enable businesses to gain deeper insights about their clientele and business. For 30% of executives, data is the right tool for executing faster race-to-market and time-to-answer decisions. At the same time, 25% of executives reckon that businesses should leverage data to steer expansion while 14% say data has revolutionized operations significantly.

Big Data Challenges

Although big data has been useful to businesses, it has posed serious challenges to businesses. For starters, unstructured data normally contains numerous erroneous entries and format inconsistencies. In 2014, these errors forced data scientists to spend more time on data cleaning tasks (50-80% of working time) than on data analysis and insight retrieval (20% of working time). Due to this tedious and time-consuming process, 99.5% of the data generated by humans has never been analyzed. Currently, 67% of businesses are yet to develop and deploy initiatives/policies related to big data.

By 2018, American businesses will be unable to find leaders who can make data-driven decisions to fill 1.5 million vacant positions. The only way organizations can prevent this talent shortage is by ramping up their expenditure on data and analytics training by 50% every year. On the innovation front, businesses are facing several data-related challenges. A major problem is the inability to extract useful insights from data, which inhibits the ability of decision makers to execute the right actions. This also inhibits companies from deploying data as an innovation booster or use data to improve product and service innovation.

Data Utilization across Organizations

In spite of the hype surrounding big data, tech savvy businesses now focus on value extraction rather than velocity or volume. In 2013, organizations across the world spent $31 billion on big data initiatives. By 2018, this figure is expected to rise to $114 billion. It is also worth noting that 54% of businesses have already created and filled chief data officer positions. Up to 79% of leaders believe that failure to leverage big data would lead to the loss of a company’s competitive edge. Furthermore, 39% of leaders who have embraced big data say that their organizations have experienced operational efficiency improvements. Finally, 26% of organizational leaders reckon big data initiatives have enhanced customer experiences greatly while 25% of executives believe that a similar approach has enabled them to identify new product and service opportunities.

How Big Data Is Fueling Business Growth

Business executives are upbeat about the future of big data, especially its impact on growth. For instance, big data analytics has become the key to identifying and segmenting consumers according to income, age, past buying behavior, gender, and profession. At the same time, businesses are using big data to identify growth niches and keep abreast of changes in consumer preferences. Besides these benefits, 37% of executives believe big data is the key to enhancing business-customer interactions and relationships. Moreover, 26% of leaders say big data initiatives could revolutionize research and development activities while 15% are convinced they will redefine organizational structures.

Case Studies

After making a $200,000 big data investment in 2011, Cricket Communications was able to gain insights on mobile app activations, anomalies, and payments. This investment also cut Cricket app outages by 15% leading to a dramatic drop in churn rates. More importantly, Cricket Communications recorded a 500% return on investment (ROI) or $1.3 million in savings annually. Bristol-Meyers Squibb’s $46 billion big data investment reduced the time required to run clinical trial simulations by 98%. It also cut the time required to process 2,000 jobs to 1.2 hours. Prior to this investment, processing several hundred jobs took 60 hours.

Requirements for Handling Big Data

To effectively analyze and understand big data, leaders must be knowledgeable in data collection and research as well as be able to extract insights from multiple data sources. They must also be well versed in data visualization, storage, and security.

Conclusion

Big data has revolutionized the way business leaders make decisions, defend market share, spur growth, and monitor operational efficiency. Fortunately, cloud computing and web-based data analytics and visualization platforms have enabled small businesses that cannot afford to hire in-house data analysts, to gain valuable insights from their data.

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