The Real-World Use of Big Data: How innovative enterprises extract value from uncertain data

In industries throughout the world, executives are recognising the opportunities associated with Big Data. Despite what seems like unrelenting media attention, it can be hard to find in-depth information on what organisations are really doing. To better understand how they view Big Data and to what extent they are currently using it to benefit their businesses, the IBM Institute for Business Value partnered with Saïd Business School at the University of Oxford to conduct the 2012 Big Data @ Work Study. We surveyed 1144 business and IT professionals in 95 countries, and interviewed more than two dozen academics, subject matter experts and business/IT executives. Here, IBM Europe General Manager Rich Hume gives his perspective on the findings.

In the last century, as Europe’s population grew fourfold, our economies expanded by 40 times. This profound increase in prosperity impacted our planet commensurately: in the same period, the exploitation of raw materials grew by 10; fossil fuels by 16, hauls of fish by 35 and water by nine. We know that we must change the way we live and work, not least as our populations start to age and much of our infrastructure begins to creak.

Today, IBM and others remain convinced that data (in quantities so vast and ever-growing that industry folk refer to it as ‘Big Data’) has become the new physical resource that we must tap to help solve all manner of business and societal challenges. Indeed, data promises to do for our era what oil, steam and electricity did for the Industrial Age.

In every city in Europe, a plethora of sensors and gadgets provides real-time data on all manner of events — from hourly energy usage in homes and even individual appliances to the status of a train racing across the countryside. People around the world are communicating and interacting in billions via social networks in ways that were unimaginable just a few years ago.

This digitisation of virtually everything now creates new types of large and real-time data across a broad range of industries. Much of this is non-standard data: for example, streaming, geospatial or sensor-generated data that does not fit neatly into traditional, structured, relational warehouses.

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Today’s advanced analytics technologies enable organisations to extract insights from data with previously unachievable levels of sophistication, speed and accuracy.

Much data is inherently uncertain. That may include sentiment and truthfulness in humans; GPS sensors bouncing signals among Europe’s cityscapes; weather conditions; economic factors and the future. When dealing with these types of data, no amount of data cleansing can correct for it. Yet despite uncertainty, it still contains valuable information. The need to acknowledge and embrace this uncertainty is a hallmark of Big Data.

In response to the Big Data phenomenon, there has been a huge advance in technology that is able to store, access, and analyse these huge new data streams. What’s more, today’s advanced analytics technologies and techniques enable organisations to extract insights from data with previously unachievable levels of sophistication, speed and accuracy.


Big Data, Big Wind

For some time here in Europe, we have seen forward-thinking and innovative enterprises deriving competitive advantage from Big Data. One great example is Vestas Wind Systems A/S, a Danish wind turbine producer.

Wind turbines are a multi-million dollar investment with a typical lifespan of 20 to 30 years. To determine the optimal placement for a turbine, a large number of location-dependent factors must be considered, including temperature, precipitation, wind speed, humidity and atmospheric pressure.

Vestas found that the data analysis process used to create its customer turbine location models was becoming increasingly unsatisfactory. The process took several weeks to execute and could not support analysis of the very large set of data the company deemed necessary for precision turbine placement and power forecasting.

It is imperative that organisations focus Big Data initiatives on areas that can provide the most value to the business. For many industries, this will mean beginning with customer analytics that enable better service as a result of being able to truly understand customer needs.

Its engineers wanted to start developing their own forecasts using actual recorded data for existing customer turbines instead of employing industry models. The challenge was to increase data capacity requirements to a projected six petabytes.

Using one of the world’s largest Big Data solutions on a supercomputer and a modelling solution designed to harvest insights from an expanded set of factors including both structured and unstructured data — the company can now help its customers optimise turbine placement and, as a result, turbine performance.

This new information environment enables the company to manage and analyse weather and location data in ways that were not previously possible in order to gain insights that can lead to improved decisions for wind turbine placement and operations, as well as more accurate power production forecasts.

The detailed models mean greater business case certainty, quicker results and increased predictability and reliability, which decreases cost to customers per kilowatt hour produced — and increases the precision of customer ROI estimates.

These technologies reduce by approximately 97 per cent – from weeks to hours – the response time for business user requests, and greatly improve the effectiveness of turbine placement.


Big Data Winners

I see these kinds of advances across all kinds of industry and enterprise here in Europe. But what are the factors that will determine the winners and losers?

Our study findings show that 63 per cent of those surveyed report that the use of information and analytics, including Big Data, is creating a competitive advantage for their organisations, up from 37 per cent just two years ago — a 70 per cent increase.

Moreover, the survey highlighted five key recommendations for organisations to progress their efforts and seek the greatest business value from Big Data:


1. Commit to customer-centred outcomes
It is imperative that organisations focus Big Data initiatives on areas that can provide the most value to the business. For many industries, this will mean beginning with customer analytics that enable better service as a result of being able to truly understand customer needs and to anticipate future behaviours.

Mass digitisation, one of the forces that helped to create the surge in Big Data, has forever changed the balance of power between the individual and the institution. If organisations are to understand and provide value to empowered customers and citizens, they have to concentrate on getting to know their customers as individuals. They will need to invest in new technologies and advanced analytics to gain better insights into individual customer interactions and preferences.

But today’s customers want more than just understanding. To cultivate meaningful relationships effectively with their customers, organisations must connect with them in ways their customers perceive as valuable.

The value may come through more timely, informed or relevant interactions. It may also come as organisations improve the underlying operations in ways that enhance the overall experience of those interactions. Either way, analytics fuels the insights from Big Data that are increasingly becoming essential to creating that level of depth in these relationships.


2. Develop a Big Data blueprint
A blueprint encompasses the vision, strategy and requirements for Big Data within an organisation and is critical to establishing alignment between the needs of business users and the implementation roadmap of IT. It creates a common understanding of how an enterprise intends to use Big Data to improve its business objectives.

An effective blueprint defines the scope of Big Data within the organisation by identifying the key business challenges to which it will be applied; the business process requirements that define how Big Data will be used and the architecture which includes the data, tools and hardware needed to achieve it. It is the basis for developing a roadmap to guide the organisation through a pragmatic approach to develop and implement its Big Data solutions in ways that create sustainable business value.

At some point in time, new insights will become a commodity. Every competitive organisation will be able to deal with Big Data or they will fall behind. The question will be what to do with Big Data, and how fast.

3. Start with existing data to achieve near-term results
To achieve near-term results while building the momentum and expertise to sustain a Big Data program, it is critical that companies take a pragmatic approach. As respondents confirmed, the most logical and cost-effective place to start looking for new insights is within the enterprise. Looking internally at the outset allows organisations to leverage their existing data, software and skills and to deliver near-term business value and gain important experience as they then consider extending existing capabilities to address more complex sources and types of data. Most organisations will want to do this to take advantage of the information stored in existing repositories while scaling their data warehousing to handle larger volumes and varieties of data.


4. Build analytics capabilities around business priorities
Throughout Europe, organisations are faced with a growing variety of analytics tools while also confronting a critical shortage of analytical skills. Big Data effectiveness hinges on addressing this significant gap. In short, enterprises will have to invest in acquiring both tools and skills. As part of this process, it is expected that new roles and career models will emerge for individuals with the required balance of analytical, functional and IT skills.

Attention to the professional development and career progression of in-house analysts – who are already familiar with the organisation’s unique business processes and challenges – should be a top priority for business executives. At the same time, universities and individuals themselves, regardless of background or speciality, have an obligation to build solid analytical skills.


5. A business case based on measurable outcomes
To develop a comprehensive and viable Big Data strategy and the subsequent roadmap requires a solid, quantifiable business case. Therefore it is important to have the active involvement and sponsorship from one or more business executives throughout this process.

An important principle underlies each of these recommendations: business and IT professionals must work together throughout the Big Data journey. The most effective Big Data solutions identify the business requirements first, and then tailor the infrastructure, data sources, processes and skills to support that business opportunity.

Every 48 hours we now generate the equivalent of all of the data that existed up to 2003. And thanks to advanced computation and analytics, we have the tools to turn that data into insight, knowledge and better decisions.

To compete in a consumer-empowered economy, it is increasingly clear that today’s enterprises must leverage their information assets to gain a comprehensive understanding of markets, customers, products, regulations, competitors, suppliers, employees and more.

Organisations will realise value by effectively managing and analysing the rapidly increasing volume, velocity and variety of new and existing data, and putting the right skills and tools in place to better understand their operations, customers and the marketplace as a whole. At some point in time, new insights will become a commodity. Every competitive organisation will be able to deal with Big Data or they will fall behind.  The question will be what to do with Big Data, and how fast.

That’s why I remain convinced that, whatever the starting point, enterprises around the world will continue to expand the use of Big Data to gain business value and competitive advantage in today’s increasingly globally integrated economy.

About the Author

Rich Hume was appointed general manager of IBM Europe in 2012. He was previously general manager, IBM Global Business Partners, a post he held since 2008. He graduated from Pennsylvania State University with an undergraduate degree in accounting.



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