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Industrial analytics thought leadership-series.

How will industrial analytics, Industry 4.0, IIoT and digital transformation change businesses? And ultimately the world? We ask industry leaders to share their view on these technologies, how we use them, and where they will take us.

Kjartan Kalstad:

Too much spaceship. Too little airbus

Let’s not overcomplicate change. There is so much innovation to be done with the tool box already at hand. Don’t wait for future technology, if you can innovate here and now, is the message from McKinsey partner Kjartan Kalstad.

”It doesn’t have to be that complicated to enhance your business. Let me illustrate by the story about small firm renting out ski boxes for the car. They couldn’t afford a huge Amazon style algorithm. Instead they asked every customer, where the holidays would be spent with ski box on top. One month after return the company sends a personal hand-written postcard asking about the trip to location X and also included personal details. Very simple. Extraordinary customer experience,” says partner Kjartan Kalstad from McKinsey.

”I’ve taken part in innovation workshops with C-level in many companies, and some of them are too much spaceship and too little airbus. The mindset in large companies is actually a barrier. If you overcomplicate innovation, it will be another excuse for waiting and doing nothing. You can wait for better data, better platforms and more certainty, but maybe the certainty will come from testing, learning and failure. Innovation comes hand in hand with appetite for risk,” he says.

“There is so much a company can do for their customers today with data and current analytics in the broadest sense. Products, customers and processes can be optimized right now. The potential is there.”

Think use cases

The great interest in new technologies like robotics, AI, IoT and blockchain brings with it the obstacle of thinking in technology before thinking in business, according to Kjartan Kalstad.

“You may have data and you may sense that they can be valuable, but you must start the other way around with the use case. What problem do we want to solve, and do we have data to support us? The customer delivery notice maybe critical in your business, but sometimes it’s not precise. The delivery time may be affected by the weather or something else. Now you can start using data to enhance the precision in the critical delivery notice to the customer,” he exemplifies.

The cultural switch from operations to innovation is of course a big shift in mindset for seasoned operational managers in established companies. Kjartan Kalstad sees a need for educating COO’s, CMO’s, production managers and others about how analytics in the broadest possible meaning of the word can help solve problems. Lack of experience with innovation leads to low risk appetite in the traditional industrial culture that focuses on operational excellence and incremental change.

Good tech and bad tech

“Technology can be used both for good and for bad. Decades ago all we were discussing about DNA research was the cloning of human beings. Now we see cures being developed for genetic diseases, pandemic diseases and we see new solutions to problems with the world’s food supply. I think we will see the same pattern with AI and advanced analytics”, he says.

The global awakening to the effect of data, analytics and digitization is maybe most visible in EU, where GDPR and tighter regulation of big tech is a distinct agenda. It is a growing trend that technology must be applied and implemented in a sustainable manner respecting values in society.

“I am a true believer in the value of digital transformation, but we must be aware of the misuse of data, and we must highlight the positive cases. We have a need of proper governance in both companies and society to get the best of these powerful tools,” says Kjartan Kalstad.

Industrial maturity

According to Kalstad there is a lot of potential in the analytical tool box already at hand. There is no need to wait for AI and futuristic robotics, and that argument is especially true for industrial use.

“Domain scientists have been using math and statistics for decades. In many industries you have a strong tradition for being scientific and evidence based, and in the hype surrounding AI there’s a tendency to neglect the full breadth of analytics,” he says.

McKinsey is partnering with Camo Analytics and this has given an in-depth look into multivariate analysis.

From mad men to math men

“We were impressed with what we saw, and we see potential in broadening these capabilities to new areas, new industries and new professions in the organizations. More and more will be fact based and supported by data. Even in marketing and sales you see this trend. The phrase ‘from mad men to math women and men’ tries to capture this trend,” says Kjartan Kalstad.

”We will se analytics eat its way from core analytical areas to every function in a company including HR. The use of analytics will penetrate silo walls and the professionalism will be driven by a need to find root causes and work with them,” he says.

The need to understand the customer will be a huge driver for analytics, and it is already having great importance in tele and banking.

“GDPR is a challenge to all working with customer facing data,” says Kjartan Kalstad. “In the B2B space we will probably move faster towards an automated technological chain working with data between companies. Also, internally the penetration of IoT is not limited by a regulatory scheme, and the sensor technology holds huge potential in combination with industrial analytics in development, production and distribution.”

Kjartan Kalstad:

Passionate about change

Kjartan Kalstad is a partner in McKinsey’s Telecommunications, Media, Technology, and Consumer Practices, and he leads the organization work in TMT globally. Kjartan has ~12 years of experience across industries in both EMEA and APAC giving him deep knowledge of large-scale transformations, digital growth enabled by analytics as well as transactions and mergers. He is passionate about change and transformation leading some of McKinsey’s knowledge efforts om agile organizations, transformational change, change management and digital growth. Prior to McKinsey, Kjartan worked in Statistics Norway and in the National Institute of Public Health. He holds a MSc in Economics from University of Warwick.

Follow Kjartan here:

“Domain scientists have been using math and statistics for decades. In many industries you have a strong tradition for being scientific and evidence based, and in the hype surrounding AI there’s a tendency to neglect the full breadth of analytics.”

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