Blog-Layout

Don’t follow the herd: Why Big Data is often a big mistake

Kegham Arzo • August 9, 2020
Amidst all the reports of yesterday’s garage/spare-room/co-working space start-up becoming today’s multi-billion-dollar enterprise, many traditional industrial companies – large and small, mass-market and niche – feel overwhelmed by the prospect of the digital transformation. While some bury their head in the sand, assuming – despite mounting evidence to the contrary – that their own particular area of industry is somehow safe from digital challengers, others understand the urgency of adapting their business to match the epochal shift in the economy, and are willing to invest in order to push their transformation forward.

This latter group should be commended. As any good shrink will tell you, accepting that you have a problem is both the hardest step to take and also the core prerequisite to beating it. And it is not easy to accept that simply producing what you have always produced and selling it to the customers you have always sold it to is no longer a recipe for success. So industrial companies who have recognised the shift in the economy – and who are prepared to adapt previously profitable business models to an uncertain digital future – have already cleared the highest hurdle. The problem, though, is that they are falling down at the next one.

Digital industrial strategy: keeping the cart behind the horse

This second hurdle consists in turning recognition into a concrete plan of action. All too often, industrials allow their commendable sense of urgency to run away with them and start clutching at straws labelled “Big Data”, “IoT”, or “Industry 4.0” – straws often dangled in front of them by somewhat dubious digital consultants drunk on their own Kool-Aid. Other companies, imbued with the scale of their current operations, are more bullish, wanting to implement revolutionary solutions across the board – in which case the digital consultants offer the same solutions, but with a more upbeat intro. 



In either case, their proposals call for machines “to start talking to each other” (IoT) and for the data they generate in so doing to be analysed in order “to offer customers insights” (Big Data) and “revolutionise production/operations/maintenance” to be ”more efficient and responsive than ever before” (Industry 4.0.); extra marks go to anyone who uses the words “from push to pull”, “artificial intelligence”, or “predictive maintenance” in their PowerPoint presentation.


Pardon my cynical tone, here. I should make clear that none of these things are, in and of themselves, bad ideas. The issue, though, is that they are currently being prescribed as panaceas, usually ignoring the fact they are often fiendishly complicated and very expensive to implement – and that, unless they offer tangible value which can be identified and explained, customers will not pay a premium for them. Essentially, in collecting mind-boggling sums of data first and then asking customers what they want second, industrials are getting the cart before the horse. Or, to riff on this analogy for a moment: Big Data, IoT et al. have a lot of horsepower, but unless a company knows where it needs the cart pulled to, they have a tendency to gallop away into the middle of nowhere.


Big Data: why a tool does not a strategy make


So why isn’t it as easy as hooking up all the machines and raking in the dollars? It would be good to remember here that there’s a reason why most start-ups, as world-changing as they are, are selling non-essential things to consumers using devices already in circulation (i.e. smartphones). For most data-driven digital business models, there is little proprietary technology involved (quick aside: when digital consultants say “technology”, in most cases, they actually mean “software”); the investment risk at the early stage is more-or-less limited to man-hours. That’s how Uber and Airbnb gathered huge amounts of data about how commuters and tourists move around without huge up-front investments; things only get expensive for companies like them when they start spending big in order to fund hyper-growth in winner-takes-all-markets.


For industrials, however, pursuing a Big Data strategy generally does mean a substantial up-front investment in order to develop hardware: sensors need to be designed or bought in and integrated into complex – often system-critical – products; and that’s before the eye-watering volumes of data generated by industrial roll-outs have been collated, stored, and processed (in keeping with the stricter cybersecurity requirements often in place in industry…). GE, for example, found out early on that transforming itself into a digital data broker was a far costlier enterprise than the Silicon Valley evangelists had suggested: its IoT platform swallowed millions of dollars in development costs before the GE Digital business unit set up to run it started to gulp down billions, diverting resources and attention away from core operations as the company’s share price tumbled


In its quest to become “the most digital company on the planet”, meanwhile, consumer goods conglomerate Procter & Gamble fell victim to a similar digital costs spiral without seeing any tangible benefit. Then there’s Ford, which, in pursuit of the car-as-mobility-node dream, started throwing inordinate sums of money into Ford Smart Mobility – while, unfortunately, neglecting to build decent non-digital cars. For further reading on where industrials go wrong with their digital transformations, I would recommend this piece in Harvard Business Review.


From my point of view, the issue is clear: the companies concerned mistook tools – Big Data, IoT – for strategies. “Becoming the most digital company on the planet” for its own sake is not a strategy. A strategy would be to find out what customers’ pain points are and which service offerings they would be willing to pay a premium for. Collecting and analysing data or hooking up machines to talk to each other – “becoming more digital” – may then be the basis for solutions. If so, these solutions will be leaner, simpler, and less expensive than simply try to digitise everything that moves.


Big Data is the cart, not the horse. And if it is implemented for its own sake, it’s frequently a big mistake.

Don’t follow the herd: Why Big Data is often a big mistake

By Kegham Arzo • 09 Aug, 2020
Amidst all the reports of yesterday’s garage/spare-room/co-working space start-up becoming today’s multi-billion-dollar enterprise, many traditional industrial companies – large and small, mass-market and niche – feel overwhelmed by the prospect of the digital transformation. While some bury their head in the sand, assuming – despite mounting evidence to the contrary – that their own particular area of industry is somehow safe from digital challengers, others understand the urgency of adapting their business to match the epochal shift in the economy, and are willing to invest in order to push their transformation forward. This latter group should be commended. As any good shrink will tell you, accepting that you have a problem is both the hardest step to take and also the core prerequisite to beating it. And it is not easy to accept that simply producing what you have always produced and selling it to the customers you have always sold it to is no longer a recipe for success. So industrial companies who have recognised the shift in the economy – and who are prepared to adapt previously profitable business models to an uncertain digital future – have already cleared the highest hurdle. The problem, though, is that they are falling down at the next one. Digital industrial strategy: keeping the cart behind the horse
Foto: unsplash.com

Car parts manufacturer caught in the commoditisation trap

By Kenny Arzo • 26 May, 2020
Today, I came across this article on Reuters about problems at car parts manufacturer Benteler. It caught my attention not only due to the business strategy questions it raises, but also due to an emotional connection I have to the company: Benteler was my first employer. And it was a great place to start my career. Surrounded by top industry professionals, I quickly found myself on a tremendously enriching learning curve – and building friendships with colleagues with whom I am still in contact today. So it is sad to read classic financial press copy like “compounding problems at the family-owned company”, “ill-fated U.S. expansion”, and “restructuring talks with creditors” about a company I owe so much to. It certainly seems like there is a political issue, too: I can understand why the German government might not be so keen to help out a company which fled to neighbouring Austria on a corporate tax dodge and has now come back begging for cash… I think the really interesting question, though, is just what happened to such a large-scale and highly-professional global operation – a textbook example of German family-owned business success – to reach such an unfortunate state? Well, here is my opinion – not as “insider” anymore, but as someone who knows the company and its market well. So let’s start by looking at that market . For decades, Automotive was a continuous growth market in which well-established, globally-active automotive suppliers were able to participate by expanding their manufacturing capacities and growing with the OEMs. This dynamic started to change in 2017, however, in line with shifting customer behaviour. Car ownership among the younger generations started to decrease and in recent years, new business models catering to those who do not buy and run their own vehicles have sprung up, especially in larger cities: car-sharing providers, rent-a-bike schemes, ride-hailing apps. What is more, the new millennium has brought improvements in public transportation together with a growing environmental awareness. In the long term, all of this serves to discourage consumers from buying a car. And now, for the second time in this young century, there has been a breathtakingly sharp drop in demand, sending global volumes plummeting and impacting directly on suppliers who are largely reliant on OEMs.

Don’t listen to the hype: Tesla won’t make it to 2025!

By Kenny Arzo • 05 Mar, 2020
In late January, Tesla’s share price hit a record high and took its market capitalisation to $100 billion. That makes it worth more than the US’ stalwart carmakers Ford and GM – combined – and dwarfs valuations in the historically incredibly successful, highly profitable German automotive industry. Now, I certainly wouldn’t be alone in stating that this is a valuation not supported by the underlying numbers: even the most ardent of Tesla cheerleaders will agree that the dizzying figure says as much about Elon Musk’s gift for marketing and investors’ search for digital outlets for the huge sums of money they have sloshing around. Here’s where I am on my own, though: I don’t just think Tesla is overvalued – I don’t even think Tesla will make it to 2025!
Share by: