For the love of technology

It seems almost every newspaper I have opened recently references the unstoppable rise of technology. Everyone seems to love new technology; new devices produce long queues outside apple stores everywhere and the 2013 movie, Her, shows a man falling passionately in love with his smartphone’s operating system, Samantha. This suggests that something psychologically interesting is going on.

Let’s look at the smartphone. According to Reuters, although sales are predicted to be slowing down this year, the numbers are still huge – from 970 million devices in 2013 to 1.4 billion in 2014. In the industrialised world wallet sized computers have penetrated almost every aspect of our lives. We love the ability to share seamlessly with loved ones (or sometimes not so loved ones), simultaneously they provide a constant and enormous feed of data about human behaviour.

In addition, we’re embracing devices not contained in satchels or pockets: Forbes reported 2014 to be the “year of wearable technology”, and Credit Suisse has predicted the industry could reach approximately £30 billion ($50 billion) within five years.

The oldest wearable tech is perhaps the wrist watch, having been around for at least 443 years. Nowadays the smart-watch seems to be on the rise, and while smart-watches are perhaps a step away from being common, there is some wearable tech that is rapidly starting to find its way into daily lives, e.g., wearable activity tracker – the fitbit. Users can monitor their exercise levels with a Smartband that uploads information about daily activity to the cloud. Smart bands are tipped to be big in the market this year, with 8 million units predicted to be sold in 2014.

Google Glass, the odd-looking, head-mounted intelligent device, seems like science fiction, but let’s not be too quick to dismiss this. Wouldn’t it be great for a remote healthcare expert to have access to facilities to talk a local team member through a tricky procedure using virtual glasses? Come to think about it, this isn’t far removed from the wearable cameras law enforcement agencies are increasingly deploying.

GoogleGlass by lawrencegs on Flickr (CC BY 2.0)

Where does this place lean?

What should we make of this love affair with gadgets? What do developments in new technologies mean for lean? For one, technology provides access to data that can inform our decisions in new and interesting ways.

Big data is not new. According to the Telegraph, for over a decade, Tesco has been tracking customers using its clubcard, and tailoring each of its stores with the information provided. Facebook, celebrating its tenth birthday in February 2014, with 1.11 billion members is just one of a number of services affording businesses the ability to precisely target customers.

However, the ways customer data is used is something consumers are becoming increasingly aware of. Recent reports of clubcard data hacking are urging a move towards more secure, regional networks.

It’s not just access to data and customer needs that tech offers us. Automation in logistics is amazing. With the prospect self-driving vehicles, advanced deployment of robotics, human-free warehouses, and drone delivered packages, it seems like there is nothing technology can’t do.

Kuka KR 30 Giant Industrial Robot Arm by Pete Prodoehl on Flicker (CC By-NC-SA 2.0)

Technology is the answer! What was the question?

Thinking like this is tempting, no matter the problem – automation is the answer. It was against that background when I was first employed in lean. Like anywhere, I was employed by an organisation facing a series of challenges. The solution always seemed to be a technological one. This resulted in a familiar problem, an increasing number of electronic systems that provided a solution for only one area. This is partly why I was employed, to get the processes right behind the systems because there was a problem that technology couldn’t fix.

Illustration: research leave committee

I was commissioned to undertake an improvement activity with a member of administrative staff. She was responsible for servicing a senior committee authorising research leave for academic staff. The committee approved staff leave to generate research outcomes: a book, a scientific project, perhaps something that required travel overseas, certainly a dedicated concentration of time off site.

Together we analysed the process and identified waste, 6000 sheets of paper each year were painstakingly written, printed, circulated and reviewed. We needed a system to manage this. A simple and direct way to collate and distribute information. A process the committee could contribute to, directly from their own devices, anywhere. Best of all, it would only have taken a small investment, which we could have paid back relatively quickly in saved printing, paper and postage costs.

As a more mature lean thinker now, as I am sure you are, you would have responded the way my boss did at the time. She said: No. You’ve got it wrong. There’s something missing here. Go back, and find out what is really happening.

I returned home grumpily that evening. After a couple of days cooling off, I returned to this piece of work. We decided to speak with senior staff, some of them on the committee and some of them in other lofty roles. We came across an interesting question. How many applications for research leave had this committee declined? We figured this data would be critical to understanding the value this group added.

The answer? None. Ever.

The level of research was so specialist, in practice none of the committee members could accurately know whether it was appropriate, trusting the judgement of the line manager who had relevant expertise to assess. Neither could the committee arrange cover-work for staff members to complete in the absence of a staff member, this also fell to their line manager.

The committee decided it no longer needed to function. The committee’s duties of approval were discharged to line management in that area. The committee established its strength in reporting and information sharing and a standard note was introduced in pre-existing annual reports.

No paper, no expensive staff time at committee meetings, no need to spend the time to write the paper in the first place, but more importantly no computer system required to manage a process that would be better fulfilled elsewhere by people. It seems so simple, yet, when I look around I still find myself wondering whether this lesson has really been learned; there are some things that technology can’t fix.

The serious technological advantage

I am not arguing against technology, but I propose the key is to utilise technology we use well, which needs a true understanding of purpose, as well as, understanding of what technology has to offer, then we can apply human judgement.

That’s behind a growing movement to ensure we are better able to make the most of tech. Companies like Decoded, based in London and New York, are starting to capitalise on the need to ensure executives understand what computer systems can do. Despite some controversy, a national push to embed computer codingacross the UK indicates how important this is as a foundation for future growth.

Conclusion: lean and artificial intelligence?

What about looking to the future, perhaps to artificial intelligence? Are we facing a time where computers take over deciding what is valued or not? Where machines can apply their judgement?

Unsurprisingly, software already beats humans at searching through legal documentation for information relevant to a big case (such as electronic data mining in the 2001 Enron scandal spotting an email containing the text “I’ll be shredding ‘til 11am” that human readers had missed, subsequently providing evidence that shareholder records were destroyed). More surprisingly, we already have machines that can make legal decisions, both avoiding the fallibility of human judgement, and the expense of it – while not yet replacing people entirely.

In Germany, software has been developed that can interpret child benefit claims. Australian lawyers and mediators currently, very successfully, consult AI on divorce settlements and legal aid matters (a 98% match rate for the legal aid cases, with the remaining 2% found to be borderline). Perhaps this is just the beginning.

Eric Smidt, Chair of Google commented at the World Economic Forum in Davos earlier this year, in the context of employment: “it’s a race between computers and people – and people need to win”.

The impact machine intelligence could have on our lives is almost unimaginable. If super-intelligent machines can replicate themselves, then once the tipping point is crossed things could change very quickly. This is the stuff of science fiction, but some commentators genuinely believe that super-human artificial intelligence could happen before the mid-point of the 2100s. Others urge caution, but many see it as inevitability.

Old computers by Leif K-Brooks on Flickr (CC BY-SA 2.0)

Let’s not forget back in 1997 when a computer (Deep Blue) beat Garry Kasparov at chess and let’s also not forget playing chess is only evidence of beating a human in a very specific field, and Deep Blue arguably won because of a software bug and subsequent human intervention. Alternatively, distributed servers already manage their data in a way we sometimes can’t predict, (and yes, they already do so with superhuman efficiency) and researchers working for Google aren’t always able to understand how their machines can, for example, decipher certain images. Within a set framework, the computer systems have learnt to do this all by themselves.

However far out this might be, as lean thinkers considering the future can perhaps prompt us to reassess what we mean by value, what we mean by value creation, and what value people bring. We have to bank on people remaining competent in what they are uniquely good at and take advantage of that. These conclusions are as relevant to a multi-national leader in operational excellence as they are to the smallest lean start-up.

The conclusions are something we already know. We know that we need leadership and vision. We know we need strategy and stewardship. We know we need people who can take chaotic realities and turn them into opportunities. We know it’s our human capacity to hold contradictory views, to doubt ourselves; and then to innovate, which lies behind so much of lean, the challenge of the 5 whys, the plan-do-study-act cycle and the wisdom to really understand purpose.

Putting this into practice will see us holding our place in a world of machines. If we lose Smidt’s race? Let’s hope our machine overlords are more like the loving AI Samantha than the murderous Hal from 2001: A Space Odyssey.