Industrial Internet Now

Building an insight-driven business

Having huge amounts of information is one thing. Harnessing data to create new business models is another. Alun Jones, Data Scientist at Konecranes, talks about utilizing machine learning, understanding security issues and improving operational efficiency as steps in building an insight-driven business.

Technology evolves rather quickly, while products inevitably do not. There is a challenge to figuring out how to make certain that older pieces of equipment talk to newer ones.

The Internet of Things (IoT) is relatively new. On the technical side, a lack of standards and protocols persists mainly because of its nature as a converging market place made up of competing players who believe that their individual technologies should be the standard.

Then there is what can be viewed as vendor discrepancy, or where a vendor adds something to a standard because they see it as the way forward. There may be little cause for concern about compatibility when using a manufacturer’s proprietary equipment. Keeping up with updates, however, can prove to be a challenge when combining equipment from different manufacturers. Cultural issues surround the ownership and usage of data, which are internal to organizations.

Utilizing machine learning

Machine learning is really where the benefit of having huge amounts of data comes from. What machine learning does is that it can very quickly go through a very large data set and pick up salient points which you then have to verify in real terms. Using algorithms that learn from data in an iterative manner, machine learning allows computers to detect hidden insights without being explicitly programmed where to search. Machine learning methods drive much of modern data analysis across fields such as engineering and the sciences, and commercial applications.

“Machine learning methods drive much of modern data analysis across fields such as engineering and the sciences, and commercial applications.”

Machine learning will tell you that there is a correlation between this and that, which then implies that if this changes in the future then something else is going to happen. I believe that this has to be verified, always. We have machine learning at a very high level that then picks out the relevant patterns in the data which we can then validate against other sources as well.

While machine learning is already an incredibly powerful tool that can solve difficult classification problems, certain points must still be kept in mind. Increasingly, the role of human input in these automated business processes will involve overseeing and tweaking the machine learning algorithms. After all, algorithms are only as smart as the intelligence put into them. This is where the potential for misunderstanding can arise.

Machine learning depends on small “errors” being made by the machine and has to be done and redone over and over.  A data-driven hypothesis is first derived before it is tested against new data. When the machine hypothesis is found to be incorrect, the machine then refines the algorithm or hypothesis to suit both the new and old data. The process is an ongoing one.

Don’t worry about security

First, don’t be overly anxious about security. Assume security is going to work because there are professionals who will sort matters out, so don’t allow that be a barrier to doing something.

Second, start small. Pilot – and test and test and test. It would also be wise to learn from other people’s experiences. It can become a bit difficult if you pin your hopes on a form of technology and invest in it, only for it not to work. Try and be as flexible as you possibly can. A particular type of technology may be widely used today, but it might change rapidly. As big data introduces a new level of integration complexity, integration technologies then require a common platform that supports data quality and profiling.

Improving operational efficiency

The next thing, which is the crucial part, is harnessing all this data and coming up with new business models. For instance, the steel industry in the UK is going through a very bad patch. Steel plants have had to close in England, enabling former employees to sell their expertise within the industry. The knowledge that these individuals have, as well as the data they have access to, can be used to improve the steelmaking process and optimize operations.

Once operational efficiency has been attained, the next move would be to think about what else all this data allows you to do.

Another way that data can potentially improve the service-based economy is by making manufacturing more flexible and more small-scale. There are opportunities for small-scale manufacturing using Industry 4.0 or IoT in general. Rather than having to build 10,000 of something, for example, you can build 10. Or you can then have a tailored experience.

Generating value from Big Data, and using it as a key component in a business’s growth strategy, is a matter of connecting data to insights to action in a quick, repeatable way. There are more options we haven’t even thought about yet.

Alun Jones works as a Data Scientist at Konecranes

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Interview W/ Alun Jones


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  • Eliahu Gal-Or 13.11.2016 08:14

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Managing change in the connected workplace

The move to the digital world has allowed us to create new value inside the workplace, but adopting the IoT on a wider scale poses a few challenges. Alexander Reay, Chief Digital Officer at Sodash and President of the Nordic IT Association, explores the role an organization’s structure and culture play in maximizing IoT’s potential for businesses. He also talks about the leadership issues that need to be addressed during this transformation.

The Internet of Things (IoT) is very transformative and is reshaping business models. This disruption entails a huge amount of internal change that needs to be addressed in an organization. Alexander Reay, Chief Digital Officer at Sodash and President of the Nordic IT Association, believes that the issue is connected to neither technology nor technology maturity. “It’s a leadership one. It’s about understanding the digital economy – or if you prefer, the platform economy – we’re moving into.”

This transformation through technology, he adds, is a cultural matter. “It’s the impact of how the business and the people in it work. When you’re moving systems into the cloud, the major issue is to actually lead or inspire people who are very much used to the traditional way of doing things to adopt this new method.”

Since digital transformation is something that effects every single part of a business, a leader can’t be expected to do this on his or her own and needs to invest into change agents.

Culture of change

“An organization needs to have a culture of proactive change and the individual spearheading it needs to have a completely systematic and holistic view,” continues Reay. “Leadership in larger enterprises, however, isn’t as agile and usually can’t cope with quick, radical change. By far, that is the biggest barrier in adopting new and better ways of doing things along with rigid old hat organizational structures and governance”

As companies are recast as digital enterprises, and organizations continue to adapt to the IoT and the new demands of managing the physical and the digital, this convergence mandates not only new skills but also different ways of working.

The role of chief digital officer (CDO) involves looking for business opportunities that have been enabled by the digital revolution. It also entails focusing on customers and how their needs might change because of technological developments. It is quite different to that of the chief information officer, whose job — though similarly complex — is more about following procedures and keeping a company’s IT systems running. By contrast, the digital role is to head the transformation.

“This is really a leadership understanding of the technology – how to use it, how to drive new value as result – not the technology itself. So forget thinking of IoT and digitalization as just new technologies.”

As Reay stresses, “This is really a leadership understanding of the technology – how to use it, how to drive new value as result – not the technology itself. So forget thinking of IoT and digitalization as just new technologies. For those companies that get it, digital represents an entirely new way of doing business, moving from using technology as a catalyst for efficiency or effectiveness into driving new value or even changes to entire business models, but most important, they are in the process of changing their corporate culture”.

Difference between network and community

To begin the work of digital delivery, the companies recruiting chief digital officers must break down the walls between the independent vertical structures in their organizations. Reay notes that since we’re used to really siloed innovation, “we’re just about starting to realize the potential of open innovation techniques. What we’re talking about is a completely seamless network.”

It’s one thing to have the infrastructure to create a network and fluidity – those are the technical aspects, according to Reay.

“The real value lies in using that network to create and foster a community or to look at it another way expedite a digital culture, and for that people need to be empowered. Being connected to somebody doesn’t mean that that individual is empowered to be able to add value or even inspired to do so, and that’s the difference between a network and a community, it’s about adoption rate – a network informs, where as a community acts. In a community, people are actively contributing and they’re empowered to do so. That’s why change right now is such a headache for large businesses: they are simply too siloed, lacking the ability to adopt new ways of working quickly enough.”

Security and privacy issues

Another barrier, not just in terms of operability or interoperability, involves security issues. Reay brings up privacy, which to him is an area that is very disruptive in itself. “We’ve got the EU coming out with changes and directives very frequently and cyber-attacks increasing in frequency. The move into IoT requires a completely new set of skills that are needed rather urgently, if you fulfill some of the data regulations,” he adds.

These directives, as well as the cyber security issues that result from having these systems over the internet, have yet to be fully understood because IoT is such a new area.

“Since the EU is putting in these directives, when these new things emerge, they do so within the context of a rigid government system that’s been used for eternity. The key in trying to find new ways of mitigating some of these risks is understanding what leadership roles are really needed.”

Reay observes that large organizations are now rolling out compliance managers across their business units. “This is simply not going to do,” he counters. “There needs to be a Chief Privacy Officer, someone who can run the show at a very single level inside the organization on a strategic level, we are not just talking about technology here. These individuals should be rising through the ranks from a legal perspective, and with heavy sanctions and penalties for privacy breaches, this role should under no circumstances be left to the CISO, CSO, CIO, or CDO’s responsibility”.

Collaboration between machine and human

With the usage or the ability to analyze such massive volumes of data, machine learning starts to play a role. Humans can’t analyze that amount of data, and to Reay, what’s interesting is the new value creation made possible by massive volumes of data collected from connected products and devices. This goes beyond efficiency, smart sensors or the ability to use the IoT to create more efficient productive manufacturing lines.

“For example, artificial intelligence (AI) could be used to process that data to provide insight, resulting in better informed rapid decision making. Doing so could organize a lot of these areas, from efficiency and uptime to the utilization of assets. The maintenance and management aspects are, right now, the areas where we’re going to see machine learning really utilized.”

Ultimately, Reay believes that everything comes down to a human-centric approach.

“What really stands out with the use of AI is that it makes us essentially more human. It’s the same as with digital transformations: it’s not the data we’re interested in. It’s how the data influences our decisions. The collaboration between machine and human is where the real innovations are going to start. The utilization of the interface between AI and humans is going to be where we will see how it is utilized to its full potential.”

Again, when we roll out the IoT, machine learning can be used to improve efficiency and uptime. But, as Reay concludes, “the real utilization is understanding how can we use machine learning to create a positive impact for humanity, the workplace and our customers.”

Alexander Reay works as a Chief Digital Officer at Sodash and is President of the Nordic IT Association

Image credit: Wichy /

Interview W/ Alexander Reay

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Connected cars need to play well with smart cities

As autonomous vehicles and smart city investments continue their blistering growth, experts say it’s vital that these two connected juggernauts work in better synchronicity.

Donal Power, a contributing writer at ReadWrite, talks about a recent report by the International Data Corporation (IDC) that examines the interplay between these two massively transformational technologies. “Despite this spending most smart city initiatives, include smart transportation projects, are focusing on solving peripheral issues, with few big projects tackling core city problems,” notes Power.

Read more about Power’s take on the IDC’s findings at

Image credit: jamesteohart /

Via ReadWrite

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Leading transformation from the top-down

Digital transformation is a matter of organizational change that requires attention and commitment. It impacts not only the business structures but all levels of the organization. Most importantly it is about people, not technologies, reminds Robert Wendelin, PhD (Econ.) Head of IoT at TeliaSonera Finland.

“The primary task of leadership, of course, is to point out the direction of the organization and support its business. In the case of IoT and digitalization the focus is on developing services, which is basically about streamlining and improving processes and functions. Essentially, leadership is about managing the change that enables this development,” Wendelin describes.

Development in any area requires a company strategy that is implemented and clearly understood throughout the organization. “Communicating strategy is not about using fancy words in speeches. Instead, strategy needs to be communicated in a manner that makes it easily understandable to everyone. People can’t commit to something they don’t understand.”

Commitment is another prerequisite for a successful leader. And so is setting up the right KPIs.

“Leaders, as well as employees, need to have a bonus scheme connected to long term KPI’s helping them in making correct decisions and investments instead of sub-optimizing decision making for short term gain. Back in the days I’ve come across many KPI schemes that focus purely on quarterly results, while the results of long term IoT investments only started to show results after two to three years. By that time the massive investments companies have made in achieving long term results have eaten up the quarterly KPI bonuses of the employees. In a situation with short-sighted KPI’s it is very hard to make people commit to achieving the company’s strategic goals, or to generate innovation. So, being a successful leader also means gaining employees’ long term commitment and looking beyond quarterly bonus schemes”, Wendelin states.

The fear of the unknown

Fundamentally, change is the very essence of digitalization. In order to manage this transformation, companies usually hire a CDO to take charge of the change. However, when it comes to managing organizational change, a deep understanding of the business in question is of the utmost importance.

“Strategy needs to be communicated in a manner that makes it easily understandable to everyone. People can’t commit to something they don’t understand.”

“Having a background in ICT is not enough. It’s very dangerous to start changing something if you don’t have a clear view on what it is that needs to be altered. A good CDO understands the baseline and the special characteristics of the industry, as well as the business environment a company operates in,” Wendelin underlines.

Nevertheless, when it comes to the business environment, people tend to overestimate the importance of local differences. This is an issue that most globally operating organizations must tackle when managing change.

“People are different. They come from different backgrounds, speak different languages and have different views on life. But the business they operate usually follows the same principles everywhere in the world. People tend to object to change especially when it comes from someone who is not physically there. Because claiming that the required change is something that can’t be applied to the local market is easier than stepping out of their comfort zone and departing from routines. The biggest hindrance to change is in people’s minds,” Wendelin concludes.

Collaboration for the win-win

Organizational change fueled by digitalization also shapes the form of interaction with external parties.

“Partnerships of today are very different from the partnerships of yesterday. Back in the days it used to be about one giant strategic partner using local subcontractors who, quite frankly, didn’t really have much to say to anything,” Wendelin points out.

Nowadays collaborations between business partners resemble an ecosystem that consists of multiple players of all sizes, who all share the same goals. Building and developing the ecosystem together helps everybody win. “Orchestrating this kind of network is based on the idea that a company should choose the right partners for every business situation,” he says.

With more complex technologies shaping entire industries it makes sense for all actors to form strategic alliances and partnerships. However, learning to rely on multiple external partners in research, development and production is one thing – storing data to somewhere else besides the company’s own servers is another.

“Many establishments are somewhat in love with their in-house data warehouses. The problem is that the space is very limited, and that’s why storing data in the cloud is a trend. Still, many fear that the cloud is not a secure option for data storage. That’s another thing where organizations need effective change management, when it comes to digitalization. You need to have courage to trust,” Wendelin sums up.

Robert Wendelin works as PhD (Econ.) Head of IoT at TeliaSonera Finland Oyj.

Interview w/ Robert Wendelin

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Intelligent alarming leverages Industrial Internet of Things to reduce risks and costs

From geo-awareness capabilities to proactive analysis, modern alarming technologies use connected systems layered with new apps to help eliminate alarm noise and confusion while driving the right corrective actions. According to Alicia Bowers, Senior product marketing manager, Automation Software at GE Digital, every organization can manage alarms.

“With intelligent alarming and the Industrial Internet, companies can send the alarms that matter, when they matter, to the right person. Engineers and operators can receive prioritized alerts with instructions, helping them react to and resolve alarms quickly,” Bowers writes in Automation World.

Bowers also says that with intelligent alarming fueled by the Industrial Internet, companies can take all of the raw alarms in underlying systems and apply a level of analytics to them. Read more at

Image credit: vectorfusionart /

Via Automation World


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  • Babiker Sammbo 24.11.2016 12:01

    A mazing

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