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Yes, You Need a Strategy Behind Your Big Data Featured

Yes, You Need a Strategy Behind Your Big Data Jeremy Bishop

Big data is gaining momentum in almost every industry. Data clearly show this. For instance, IBM reports that 2,500 trillion bytes of data are produced by people daily. CISCO states that the main sources of this data are over 50 billion IoT (Internet of Things) devices and other connected devices that collect, analyze and share it. With all this diverse data, big data presents an excellent opportunity for major insights for the company of any industry, regardless of size. This makes a big data strategy pivotal. With the right big data analysis mechanisms in place, you can know when, where and how to shoot in the most optimal and possible way. Big data and insights from it make targeting accurate and bring out more appealing results.

Therefore, organizations must adopt the proper business strategy, which will make a difference in the directions that define business success. Let us see how it can help you make a difference.

  1. Data-driven decisions

Currently, most organizations analyze only 12% of the information they receive from various sources. This means that 88% of data is untapped. If such massive volumes of data had been analyzed, it would remove the guesswork and enhance decision-making. For instance, such massive data volumes can be analyzed and insights used by marketers to develop plans strategically based on a broad range of patterns. On the other hand, sales teams can extract information that allows them to accurately forecast sales and concentrate on clients most likely to purchase.

  1. Enhanced internal operations

It takes many hours or days for employees to find the necessary data and process it accordingly. Therefore, when data is needed to be retrieved for quick decision making, only 3% of employees can do it faster. However, with big data, the process of retrieving data is streamlined, inefficiencies exposed, quality control enhanced, and improvement experienced in every part of the business. A viable Big Data can benefit any part or department of a business, such as customer service, inventory management, marketing, sales and warehouse department, by enhancing operational processes.

  1. Customer-centred approach

Customer-level data sets allow customer behaviours, needs and demands to be mapped and tracked based on their operations, interactions and transactions. With data sets, the entire customer journey can be understood together with their experiences. An example is Netflix. After assessing its 100 million customers/subscribers, it aligned its content based on consumer preferences, thanks to the proper insights they get from its big data systems.

When combined with analytics, big data sheds more light on aspects like customer loyalty, customer satisfaction, revenue and the cost of serving individual customers. These aspects are critical for customer experience (CX).  

How can you build a big data strategy?

Adopting big data might seem difficult primarily because of a lack of expertise within the organization. However, here are some steps that might help implement the plan:

  1. Define your business goals

Before you adopt big data in your organization, find exactly where data is needed, the problems it can solve and how it can contribute to individual business goals. Big data must tackle key business problems and contribute to corporate business goals.

  1. Get highly skilled personnel

Big data thrives where roles are properly distributed. Therefore, you need to hire the right people to deal with data. Take advantage of the existing employees by reskilling and upskilling them.

  1. Assess the current assessment state

 

Assessing the current state of things might address the company's existing assets, resources, processes, policies and capabilities. This assessment is important for developing an accurate data strategy roadmap that supports what the company aims to be.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

scottkoegler.me/

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