Big Data — big usage

The spread across sectors

The definition of Big Dataⁱⁱ in Figure 1 illustrates how enterprise data and financial data can be seen as subsets of the vast range of data — ‘Big Data’ — that’s now available to a business. And it’s growing rapidly — data from outside the enterprise is proliferating on websites, in social media and other forms of communication across the internet.

The sectors that initially made the most use of data were those that had the most of it — the likes of retailers, insurance companies, banks and airlines.

Now, however, businesses in almost every sector are using data analytics to improve efficiency and the services they offer.

Figure 1: Big Data defined

Financial data:
Standard financial metrics, well-tracked
and understood
Enterprise data:
The above, plus broader operational and transactional data that may be used to bolster analysis and forecasting
Big Data:
The above, plus new types of internal and external data, much of which is unstructured, but some of which could yield new insights into business performance, risks and opportunities.

The big changes driven by Big Data:ⁱⁱⁱ

Farming:
Tractors with sensors can collect data on seeding rates, crop yield and ground conditions, allowing farmers to predict production rates more accurately. Farmers can also analyse weather patterns to better prepare for poor conditions.^iv

Manufacturing:
Manufacturers are using advanced analytics to manage the risk of potential faults in equipment and product anomalies during production. They are also using it for forecasting, inventory management and production planning.^v

Retail:
Retailers are using data to forecast customer demand and understand their preferences, allowing them to become more proactive and better able to predict behaviour. They are also using Big Data to create new digital product offerings.^vi

Transportation:
Players in the transportation industries (such as airlines, rail and trucking companies) are using predictive analytics to manage their costs through preventative maintenance scheduling, inventory parts management and warranty claim management.^viiThe airline industry is using analytics to understand customers, predict demand and optimise pricing.^viii

Telecommunications:
Telecoms providers are using analytics and Big Data to reduce customer acquisition costs, segment target subscriber audiences and rank prospective subscribers according to their propensity to buy.^ix

Financial institutions:
Banks and insurance companies are using predictive analytics software for fraud analysis,^x while credit card companies use analytics to manage credit lines and collections.^xi

Cities:
City administrators are increasingly using Big Data to understand the needs of their citizens and proactively plan for future needs in transport, policing, health care and more.^xii

Education:
Educators are using data from student tests and assessments to determine patterns and performance levels. This is helping them to adapt courses and tailor the way they teach.^xiii

Health care:
To improve health care delivery and reduce costs, health care organisations are using Big Data analytics to analyse large amounts of structured and unstructured data to improve the efficiency and quality of care.^xiv

Getting to the heart of the business
Big Data isn’t just about improving services and efficiency levels. It can also have applications in every aspect of the business model, as illustrated here using the retail sector:

“ … businesses in almost every sector are using data analytics to improve efficiency and the services they offer.”

Do you believe that your business handles sensitive customer data well enough to fully deserve trust in its brand?

Yes it does
It does not
There is room for improvement
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