Big data use cases and the big data wake up call

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168799489According to recent studies on big data readiness, the majority of companies (more than 60 percent in the latest study of Crisp Research) are not prepared for the challenges of digital transformation. In fact, 58 percent of decision makers surveyed say they have no strategy in place.

The quest for the golden use case

Aside from industries and companies that are forced to invest in big data due to their business model (telecommunication and retail, for example), the first steps for the majority of companies in the DACH region are still very hesitant. Most companies are in a process that I like to call "searching for the golden use case," meaning they think they understand the importance of big data so they start searching for the groundbreaking business case. This case has to prove in a short timeframe that big data is worth the investment. Very often, the result is: nothing.

Faced with unimpressive results, early adopters are asking, are the claims about the huge benefits of big data just more hype, or are we doing something wrong? Where are the big data use cases? And how can we do the same?

If we talk to leaders in enterprises, we get a clear answer: According to a recent study by Accenture and General Electric, 87 percent of enterprises believe big data analytics will redefine the competitive landscape of their industries within the next three years. 89 percent believe that companies that do not adopt a big data analytics strategy in the next year risk losing market share and momentum. Obviously, no hype.

Why risk missing the big data train?

Indeed, there are an increasing number of successful big data use cases from the DACH region as well as from international regions. Let's pick three representative examples:

  • A large retail bank reduced the operational costs of its data warehouse by migrating significant parts of the warehouse from a mainframe environment to a Hadoop platform. The company was not only able to reduce the load on the mainframe and realize significant cost savings, but to accelerate the processing time of all its data exponentially.
  • A large telecommunications provider in Italy decided to gather network coverage data from its competitors by very creative means. The company's vision was to improve its marketing activities and to derive information for investments in its own infrastructure. Only big data technologies could have provided storage for these large amounts of data over a longer period. In-memory analytics technologies were used to recognize potential correlations and to operationalize these models in real-time business processes.
  • One of the world's largest oil companies uses innovative sensor technologies in combination with big data analytics to identify early warnings in the drilling process. A predictive maintenance alert at the optimum time helps to avoid huge costs through unnecessary failures or unnecessary exchange of very expensive material. At the same time, the maintenance team resources can be optimally scheduled through all of the company’s drilling rigs assets.

These real-life examples prove that the use of big data technologies can provide significant added value to the business and lead to a competitive advantage. Big data is not a trend that will disappear after a first hype back into oblivion, but something that has high potential for savings through modernization or the implementation of new business processes. Digital transformation applies to any company and will change processes dramatically. Sooner or later. But it will.

Learning from the big data first movers

What prevents us from moving forward more courageously? Or in other words: which critical success factors can be derived from the above examples?

  1. Leadership: At the beginning of every successful big data project that I came across, there is a top manager who believes in the potential of big data and wants to boost the potential ahead of the competition.
  2. Mentality: traditional project methodologies don't fit for big data. Allow experimentation. Failing fast is a key mentality in order to innovate. Start with existing data, gather additional data and move forward by visually explorating any kind of data. Do not let an initial failure define the whole program as unsuccessful.
  3. People: you need innovative open-minded people. Based on my experience, the business experts who are responsible for the existing processes, often are the wrong people. Understanding data and analytical skills are certainly a prerequisite. And you have to define the role of IT in this changing data play.

What does this mean for your transformation?

If you want to apply digital transformation to your business, you have to start with a process of change. Big data does not work like traditional projects. And this change has to be established top-down in the company. It starts with a leader, who takes responsibility and guides the direction for the company.

From my perspective, this leadership should come from the CIO. He is the only person who can drive technological innovations across all divisions. Silo mentality is the guaranteed brake for digital transformation. Data has to be analyzed in a company-wide manner and – a sole reason for IT ownership – fully compliant with data protection policies.

Hence: Mr. CIO. It's up to you!

Moreover, taking leadership is not only important, it's time-critical. Consider these anecdotes:

  • In every industry, the speed of adopting big data innovations is increasing. And new players with disruptive business models are popping out of the ground.
  • A CIO of a German bank told me last month: "we are missing opportunities." I fully agree. Every month you are not starting your journey, you will lose advantage over your competition or face an increasing threat from new players.
  • Big data technologies help to escape from the modernization trap. According to a lot of reference cases, companies can realize huge cost savings – money, that is urgently needed for investments in agile infrastructures.

Thus, there is a lot for big data leaders to do. In my next blog posts, I will further discuss the success factors for digital transformation: leadership, mentality and people. And I will introduce the concept of a big data lab, which can accelerate this process for you.

Learn more about how companies are succeeding with big data, and let me know about your barriers and successes with implementing big data. Feel free to follow me on twitter @AndiGoedde.

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About Author

Andreas Gödde

Director Business Analytics

Andreas Gödde is specialist for strategies around Big Data Analytics, Digitalization and Internet of Things, helping organizations to get insights from data for business decisions. He leads the presales organization for Business Analytics of SAS in Germany, Austria and Switzerland. Andreas has a 25 years background in advising companies around Business Intelligence, Data Warehouse and Big Data concepts and projects. Andreas graduated in business informatics in Mannheim. He joined SAS in 1994 helping developing and growing the professional services organization in different management roles. In 2006 he moved to the presales organization building up teams for technical and strategic advisory for customers and for emerging technologies and trends like Big Data and the Internet of Things. Before joining SAS he worked for BASF in Ludwigshafen.

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