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27.01.2016 10:02

Leveraging the power of industrial data

Eeva Vuorinen, Head of Diagnostics & Henrik Wahlström

Requirements for analytics or entire “signal systems” are increasing in the traditional manufacturing industries. The number of Internet connected devices is increasing, so is the amount of data. Meanwhile the governance of data is becoming an issue. Traditional industry is not entirely utilizing the benefits of the data.

The signal systems concept is used to describe the collecting and analyzing of measurements throughout organizations (and ecosystems), this includes everything from operational data to high-level strategic indicators, both internal and external data. Important from the organization perspective is to understand the complete signal system and to be truly successful, let the right persons in the organization have access to the right information at the right time.

We are at a tipping point

Demand for analytics is increasing while at the same time industry customers are demanding more complex services. In addition, traditional industry customers are demanding faster and faster response to their technical issues and business needs.

The consumer industry is driving the evolution of connected devices forward. The Internet of Things (IoT) has become the driving force for new innovative solutions and business models. Historically the manufacturing industry is used to large amounts of process data but often there is unused potential, as the organization lacks the knowledge and technical resources for ‘big data’ projects. However, customers’ requirements for response time, root-cause analysis and technical problem solving remind us of the fast pace consumer industry. Traditional industries can no longer hide behind the “traditional”.

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Signal systems in the industrial context

The lifespan of an industrial investment is on average longer than in B2C-industries (think of the investment cost of a paper machine or production plant). Therefore the utilized technology will be used for much longer time than consumer electronics (think of how often we change phones), which sets whole different requirements for the signal systems in this type of industry. The knowledge in producing solutions for customers is multi-disciplinary and the requirements can be summarized as follows in order to be successful in projects:

1.     Customer understanding: What do the customers need in order to make the best profit with your solution?

2.     Business understanding: How does the industry ecosystem operate?

3.     Data understanding: What are the signals being monitored and what is possible to be achieved with the data?

4.     Analytics capabilities, e.g., understanding the mathematical models for calculations and finding the essential in the mountains of data

5.     Project management, emphasizing communication and leadership and involving the right people in the organization (including sales departments)

Examine the small picture and scale up

Industry has measurement systems with the ability to analyze events with seconds, meter’s or coordinate precision, and with correct methods these measurement signals are able to give an overall picture of the whole processes. Cloud services have increased in demand as larger-scale and faster data processing is needed. This makes it possible to analyze data on small scale and then scale up the IT infrastructure on demand and create analysis to get an overall holistic perspective of the business. Projects with heaps of data might be daunting at first, however with the right knowledge business goals are achievable.

 

Eeva Vuorinen is the Head of Business Diagnostics at PBI Research Institute.

Henrik Wahlström is working on his second Master’s degree (M.Ec) at PBI. His thesis topic is applying an analytics framework for PBI Research Institute.


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