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Stop waiting for perfection

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These days, people should stop waiting for perfection and instead experiment, find errors and turn them into innovation, writes WERNER VOGELS, the CTO of Amazon.com.

“Man errs as long as he doth strive.” Goethe, the German prince of poets, knew that already more than 200 years ago. His words still ring true today, but with a crucial difference: Striving alone is not enough. You have to strive faster than the rest. And while there’s nothing wrong with striving for perfection, in today’s digital world you can no longer wait until your products are near perfection before offering them to your customers. If so, you will fall behind in your market.

So if you can’t wait for perfection, what should you do instead? I believe the answer is to experiment aggressively with your product development, accepting the possibility that some of your experiments will fail.

Anyone who has listened to, or worked with, management gurus know their mantra: Failure is a necessary part of progress. That’s true, but there’s often a big gap between the management theory and the reality on the ground. People want to experiment and learn from things that go wrong. But in the flurry of day-to-day business, they’re not given enough time to really reflect on the cause of an error and what to do differently next time.

The solution is to find a systematic approach that prevents errors from repeating themselves.

From perfection to anti-fragility

In finding such a systematic way, you first need to distinguish between two types of errors that can happen in your company: those of technology and those of human decision-making. The nice thing is: if you know how to deal effectively with the first, you might end up being better in the second, making better decisions. The financial mathematician and essayist Nassim Taleb offers an interesting take on this issue. He has argued that errors are incredibly valuable because they lead to innovation. He uses the term ‘anti-fragility’ to make his point. Today’s digital business models require smaller, frequent releases to reduce risk. That means the technologies underpinning these new business models must be more than just robust. They must be ‘anti-fragile’. The main feature of anti-fragile technology is that it can ‘err’ without falling apart. In fact, a crisis can make it even better.

At Amazon, we also require our systems and customer solutions to be anti-fragile, and we do that by designing our systems to stand the test of time. Our systems must be able to evolve and become more resilient to failure. They must become more powerful and more feature-rich over time as a result of learning from customer feedback and any failure modes they may encounter while operating the systems.

An example of a German company that has become ‘anti-fragile’ is HARTING, the world’s leading provider of heavy pluggable connectors for machines and plants. HARTING shows how to think a step ahead about the meaning of quality standards in the digital world. Quality and trust are the most important values for this traditional company, and Industry 4.0 and the digital transformation have already been important focus areas for them since 2011. Even though it was hard to accept at first, HARTING has meanwhile realized that errors are inevitable. For that reason, its development switched to agile methods. It also uses the “minimum-viable-product” approach and relies on microservices for its software. Working this way, HARTING can discard things and create new things more easily. All in all, HARTING has become faster.

That can be seen with HARTING MICA, an edge computing solution that enables older machines and plants to get a digital retrofit. The body and hardware still reflect HARTING’s standard of perfection. But for the software, the goal is “good enough”, because a microservice is neither ever finished nor perfect. As a result, wrong decisions and mistakes can be corrected very quickly and systems can mature faster, approaching the state of antifragility. If the requirements change or better software technologies become available, each microservice can be thrown out and a new one created. That’s how you gain speed and quickly digitize old machines and connect them to the cloud within a manageable cost framework.

Taking the dread out of mistakes

If you want to become anti-fragile, more than robust, like HARTING and other companies, you need to proactively look for the weak spots in a system as you experiment. In a system that should evolve, all sorts of errors will happen that you weren’t able to predict, especially when systems need to scale into unknown territories. So subject your system to continuous failures and make subsystems artificially fail using tools like Netflix’s Chaos Monkey.

If you do all of this, you will start to objectify errors at your company and make dealing with errors a matter of normality. And when errors become ‘business as usual’, no one will be afraid of taking a risk, trying out a new idea, a new product or a new service and seeing what happens when customers interact with it. That’s how you quickly find solutions that really work in the future.

At Amazon, our approach for systematically and constructively dealing with errors is called the “cause of error” method. It refrains from seeking “culprits”. Instead it documents learning experiences and derives actions that ultimately improve the availability of our systems.

From root cause to innovation

The method first calls for fixing an error by analyzing its immediate root cause and taking steps to mitigate the damage and restore the initial running state as quickly as possible.But we are not content with that result. We go further, trying to extract the maximum amount of insight from the incident. And this process begins as soon everything is working again for the client.

A key element of our cause-of-error method is asking 5 ‘Why?’ questions (a technique that originated in quality control in manufacturing). This is important because it determines the fundamental root of the problem.

Take the case of a website: Why was it down last Friday? The web servers reported timeouts. Why were there timeouts? Because our web services are overloaded and couldn’t cope with the high traffic. Why were the web servers overloaded? Because we don’t have enough web servers to handle all requests at peak times. Why don’t we have enough web servers? Because we didn’t consider possible peaks in demand in our planning. Why didn’t we take peaks in demand into account in our planning? By the end of this process, we know exactly what happened and which clients were affected. Then we’re in a position to distill an action plan that ensures that specific error doesn’t happen again.

Quite often, applying this cause-of-error approach allows us to find breakthrough innovations, in the spirit of Nassim Taleb. That’s how the solution Auto Scaling was created, after a certain client segment was fighting with strongly fluctuating hits on their website. When the load increases for a website, Auto Scaling automatically spins up an additional web server to service the rising number of requests. Conversely, when the load subsides, Auto Scaling turns off web servers that are not needed in order to save cost.

What it reveals is: Organizations need to look beyond superficial success. This is true for the development of systems as well as business models. If you want to remain agile in a complex environment, you must follow this path, even if it means leaving the comfort zone. If we transfer these ideas into an organizational context, three aspects might be worth considering:

1. Embrace error as a matter of fact

Jeff Bezos once said about Amazon: “I believe we are the best place in the world to fail.” That inspires a lot of our people to experiment, find errors and turn them into something innovative. A statement like this encourages your people to actively look for errors, and to turn them into pieces of innovation. And: reward employees when they find errors. What we have learned from our development work at Amazon is that you need to always look beyond the surface of an error. Some of our best products have been born from errors.

2. Make due with incomplete information

German companies have a tradition of being thorough and perfectionist. In the digital world, however, you need to loosen those principles a bit. Technology is changing so fast; you need to be fast too. Make decisions even if the information you have is not as complete as you would like.Jeff Bezos put his finger on that when he wrote in his most recent letter to shareholders that “most decisions should probably be made with somewhere around 70% of the information you wish you had. If you wait for 90%, in most cases, you’re probably being slow. Plus, either way, you need to be good at quickly recognizing and correcting bad decisions. If you’re good at course correcting, being wrong may be less costly than you think, whereas being slow is going to be expensive for sure.”

3. Praise the value of learning

I’ve stressed the need for companies to have a systematic approach to how they deal with errors. But your approach will only work if it’s part of your overall culture. Make sure you understand your DNAandknow what people are thinking and talking about on the work floor. Openly praising experimentation in product development and encouraging people to find errors will come across as empty rhetoric if your employees really do have reason to fear repercussions for themselves personally if they make mistakes.

It is a matter of leadership to foster and shape a culture of experimentation that is practiced day in, day out.

Whatever companies come up with in order to systematically learn from mistakes, it will make them better in competing in the digital world. And it will give them the freedom and courage to take their systems, solutions and business models to a higher level.

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VoD cuts the cord in SA

Some 20% of South Africans who sign up for a subscription video on demand (SVOD) service such as Netflix or Showmax do so with the intention of cancelling their pay television subscription.

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That’s according to GfK’s international ViewScape survey*, which this year covers Africa (South Africa, Kenya and Nigeria) for the first time.

The study—which surveyed 1,250 people representative of urban South African adults with Internet access—shows that 90% of the country’s online adults today use at least one online video service and that just over half are paying to view digital online content. The average user spends around 7 hours and two minutes a day consuming video content, with broadcast television accounting for just 42% of the time South Africans spend in front of a screen.

Consumers in South Africa spend nearly as much of their daily viewing time – 39% of the total – watching free digital video sources such as YouTube and Facebook as they do on linear television. People aged 18 to 24 years spend more than eight hours a day watching video content as they tend to spend more time with free digital video than people above their age.

Says Benjamin Ballensiefen, managing director for Sub Sahara Africa at GfK: “The media industry is experiencing a revolution as digital platforms transform viewers’ video consumption behaviour. The GfK ViewScape study is one of the first to not only examine broadcast television consumption in Kenya, Nigeria and South Africa, but also to quantify how linear and online forms of content distribution fit together in the dynamic world of video consumption.”

The study finds that just over a third of South African adults are using streaming video on demand (SVOD) services, with only 16% of SVOD users subscribing to multiple services. Around 23% use per-pay-view platforms such as DSTV Box Office, while about 10% download pirated content from the Internet. Around 82% still sometimes watch content on disc-based media.

“Linear and non-linear television both play significant roles in South Africa’s video landscape, though disruption from digital players poses a growing threat to the incumbents,” says Molemo Moahloli, general manager for media research & regional business development at GfK Sub Sahara Africa. “Among most demographics, usage of paid online content is incremental to consumption of linear television, but there are signs that younger consumers are beginning to substitute SVOD for pay-television subscriptions.”

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New data rules raise business trust challenges

When the General Data Protection Regulation comes into effect on May 25th, financial services firms will face a new potential threat to their on-going challenges with building strong customer relationships, writes DARREL ORSMOND, Financial Services Industry Head at SAP Africa.

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The regulation – dubbed GDPR for short – is aimed at giving European citizens control back over their personal data. Any firm that creates, stores, manages or transfers personal information of an EU citizen can be held liable under the new regulation. Non-compliance is not an option: the fines are steep, with a maximum penalty of €20-million – or nearly R300-million – for transgressors.

GDPR marks a step toward improved individual rights over large corporates and states that prevents the latter from using and abusing personal information at their discretion. Considering the prevailing trust deficit – one global EY survey found that 60% of global consumers worry about hacking of bank accounts or bank cards, and 58% worry about the amount of personal and private data organisations have about them – the new regulation comes at an opportune time. But it is almost certain to cause disruption to normal business practices when implemented, and therein lies both a threat and an opportunity.

The fundamentals of trust

GDPR is set to tamper with two fundamental factors that can have a detrimental effect on the implicit trust between financial services providers and their customers: firstly, customers will suddenly be challenged to validate that what they thought companies were already doing – storing and managing their personal data in a manner that is respectful of their privacy – is actually happening. Secondly, the outbreak of stories relating to companies mistreating customer data or exposing customers due to security breaches will increase the chances that customers now seek tangible reassurance from their providers that their data is stored correctly.

The recent news of Facebook’s indiscriminate sharing of 50 million of its members’ personal data to an outside firm has not only led to public outcry but could cost the company $2-trillion in fines should the Federal Trade Commission choose to pursue the matter to its fullest extent. The matter of trust also extends beyond personal data: in EY’s 2016 Global Consumer Banking Survey, less than a third of respondents had complete trust that their banks were being transparent about fees and charges.

This is forcing companies to reconsider their role in building and maintaining trust with its customers. In any customer relationship, much is done based on implicit trust. A personal banking customer will enjoy a measure of familiarity that often provides them with some latitude – for example when applying for access to a new service or an overdraft facility – that can save them a lot of time and energy. Under GDPR and South Africa’s POPI act, this process is drastically complicated: banks may now be obliged to obtain permission to share customer data between different business units (for example because they are part of different legal entities and have not expressly received permission). A customer may now allow banks to use their personal data in risk scoring models, but prevent them from determining whether they qualify for private banking services.

What used to happen naturally within standard banking processes may be suddenly constrained by regulation, directly affecting the bank’s relationship with its customers, as well as its ability to upsell to existing customers.

The risk of compliance

Are we moving to an overly bureaucratic world where even the simplest action is subject to a string of onerous processes? Compliance officers are already embedded within every function in a typical financial services institution, as well as at management level. Often the reporting of risk processes sits outside formal line functions and end up going straight to the board. This can have a stifling effect on innovation, with potentially negative consequences for customer service.

A typical banking environment is already creaking under the weight of close to 100 acts, which makes it difficult to take the calculated risks needed to develop and launch innovative new banking products. Entire new industries could now emerge, focusing purely on the matter of compliance and associated litigation. GDPR already requires the services of Data Protection Officers, but the growing complexity of regulatory compliance could add a swathe of new job functions and disciplines. None of this points to the type of innovation that the modern titans of business are renowned for.

A three-step plan of action

So how must banks and other financial services firms respond? I would argue there are three main elements to successfully navigating the immediate impact of the new regulations:

Firstly, ensuring that the technologies you use to secure, manage and store personal data is sufficiently robust. Modern financial services providers have a wealth of customer data at their disposal, including unstructured data from non-traditional sources such as social media. The tools they use to process and safeguard this data needs to be able to withstand the threats posed by potential data breaches and malicious attacks.

Secondly, rethinking the core organisational processes governing their interactions with customers. This includes the internal measures for setting terms and conditions, how customers are informed of their intention to use their data, and how risk is assessed. A customer applying for medical insurance will disclose deeply personal information about themselves to the insurance provider: it is imperative the insurer provides reassurance that the customer’s data will be treated respectfully and with discretion and with their express permission.

Thirdly, financial services firms need to define a core set of principles for how they treat customers and what constitutes fair treatment. This should be an extension of a broader organisational focus on treating customers fairly, and can go some way to repairing the trust deficit between the financial services industry and the customers they serve.

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