How to Derive More Business Value from Big Data?

In today's hyper-competitive business environment, almost every organization is seeking to become a data-centric business, which is leading them to invest most of their IT budget in a big data strategy. As an enormous amount of new data is being generated every day, more and more companies are trying to improve the usability of such data. However, finding out the business value in big data is the biggest challenge. Moreover, understanding the association between data and skill set is vital for companies that want to unleash the power of big data.

In a survey, just 18 percent of companies consider they have the skills necessary to collect and use insights effectively, while only 19 percent are confident that their insights-gathering processes contribute directly to sales effectiveness.

Undeniably, data is the new oil for businesses, it doesn't matter what size it is. In order to make this data constructive and actionable for business stakeholders, data science plays an integral role. As other technologies, such as business intelligence dashboards and reporting, benefit from big data, data science will unlock its true value.

Extracting Most from Big Data

Many IT managers don't have a complete understanding of the data available where they can capitalize on big data. The lack of resources and ideas on what to do with this data once they gathered is also making it challenging to extract business value. In this context, data scientists or analytics managers with fuller gratitude of the data, who also understand the business and have a clear vision of the objectives, can proactively provide solutions and options.

When it comes to considering which data needs to translate that can create more business value, comprehending business impact based on analytical insights requires bringing together the right group of people with enhanced skills, and then building the necessary connections between them.

Moreover, leveraging the data hierarchy defines that the real value of data is in the knowledge and understanding. This means businesses need to have the analytical skills and capabilities to recognize and relate the patterns found in the data, the information, to business operations.

Deciphering Data into Business Value

Big data and advanced analytics technology promise unprecedented insight into business operations and customers, enabling companies to not just advance operational efficiency, levels of service, revenue and business models, but also boost customer-centricity.

However, before deep diving into the data to reap big value, organizations need to define the specific business questions and make a strategy to identify the information. As data can be a siren, risky and enticing, any changes in data strategy will require commitment from the top-level leaders for up-front investment and room for research through a few initial projects. To analyze the data, companies will also need to accomplish business objectives and scale their performance.

It is also essential that data and information must be pertinent to a specific purpose. Thus, businesses need to determine what data will be relevant, so they can gather and record it. Data sources may be internal or external, public or limited access, qualitative or quantitative and formal or informal. Once businesses identify the data, there is a need to create a joint task force of business domain experts and data scientists to recognize and prioritize the highest value projects. In case of in-house data science talent absence, companies must find a trusted partner to conduct the first projects hand in hand with business stakeholders.

So, data of any kind enable organizations to derive detailed, accurate insights and act on them with greater speed and agility. And achieving this requires a holistic approach, smart data management, analysis and information intelligence that can create and deliver effective business value.