Today’s business climate is moving at breakneck speed, with a volatility that demands companies use big data analytics to respond to fluctuating conditions quickly and decisively.
This capricious environment – combined with the massive growth of data streaming into corporate networks from myriad sources – requires that businesses aiming to stay competitive must abandon making decisions based on gut feelings or instincts and instead apply analytics to gain actionable insight.
To successfully make this paradigm shift, company leaders need to be able to create and sustain a data analytics vision, notes Stacy Blanchard, a senior director of talent and organization at Accenture.
You should start by:
- Identifying the information that must be analyzed.
- Establishing where that data lives and who’s responsible for it.
- Understanding how this information can be captured effectively.
- Designing a plan to turn the insight gained from analytics into action for the business that will boost the bottom line.
- Ensuring that analytics isn’t a siloed function but is integrated into the broader business.
After this initial work to map what data a company needs to analyze and where it resides, one of the most challenging issues associated with launching a big data program is the cultural shift that needs to accompany it.
Here are some tips from eWeek on successfully making that mindset change:
- Traditionally, database administrators have been the only people who manage data, but business leaders, data scientists and marketing folks are all making decisions today based on data. So companies need to plan to make data accessible to these larger groups of people.
- Add a data scientist role to work across the company, looking for trends in the data and advising the CIO on getting the most business value from big data.
- When working with new data sources and new technology, companies must expect to take experimental, iterative approaches to making decisions based on data. Ensure that the staff on these projects thrives in dynamic environments.
Finally, many organizations may be struggling with what questions to ask big data. All companies – regardless of their size or industry – need to begin by asking three questions of big data, notes Piyanka Jain, founder of Aryng, an analytics training and consulting company.
- How is the business doing? Companies can answer this question by creating a financial measurement framework or a scorecard. But the most important step is for the company or department to agree on the key performance indicators (KPIs) that will be used to monitor and measure the health of the business.
- What drives the business? After identifying the KPI, lay out what drives movement of that indicator.
- Who are the customers of the business and what are their needs? Companies can customize their products, messaging and marketing channels after they understand their customers.
“The process of unraveling and understanding of your own business or department is an iterative one,” Jain adds. “The process begins by asking these three questions at the highest level and then iteratively asking hundreds of cascading questions to get deeper breakthrough insights needed to maximize the ROI.”
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- To hear how organizations that have adopted in-memory computing can analyze larger amounts of data in less time – and much faster – than their competitors, watch our on-demand webcast, “In-Memory Computing: Lifting the Burden of Big Data,” presented by Nathaniel Rowe, Research Analyst, Aberdeen Group and Michael O’Connell, PhD, Sr. Director, Analytics, TIBCO Spotfire.
- Download a copy of the Aberdeen In-Memory Big Data whitepaper here.