Automation and digitization should increase the productivity of work. But productivity growth has been flat or declining in most developed countries during the past 20 years. This has been visible in countries where most jobs, and especially new jobs, are not in manufacturing, but in services and information work. So, it would be fair to assume that technology and digitization don’t help improve productivity. Henry Ford, Jeff Bezos and Larry Page didn’t win big because they optimized old operations; it’s because they created totally new operating models. Opportunity lies in developing new ways to do things, not optimizing old ones.

World-famous economists, like Daron Acemoglu, Greg Mankiw and advisors of many governments, try to understand reasons for slower productivity growth. I won’t attempt to understand all the macro-economic factors, but to focus on small practical questions like what could be the bottlenecks with digitization and automation of information work.

I wrote earlier about how we need real digitalization, not consulting projects. The problem of many automation and digitization projects is that they just try to optimize the existing processes and implement them in legacy IT systems. Both those processes and systems were developed before the current opportunities of digital services were readily available. The optimal model would be to build new processes with the latest technology focusing on the company’s real value to its customers. If you automate old processes that are unnecessary to offer customers value, it doesn’t improve productivity. That’s why genuinely digital companies like Amazon, Facebook, Google, Netflix, Alibaba and many startups win business from old companies.

It takes quite a lot of courage from management and investors to disrupt old models instead of just trying to ‘optimize’ them. The reality is that to fine-tune old models with old IT could give you a small percentage improvement in productivity, but if you want to achieve much more, maybe 100 or 1,000 per cent gain, you must create new models to operate with the latest technology.

I also wrote earlier about the trending low-code and citizen-development, and how it can rarely help implement robust well-planned solutions. This is another example, why automation of processes doesn’t always bring significant value when citizen-development is trending in automation. Suppose a company must create new models to operate so that customers can communicate digitally with it, and they digitize all internal and supplier interactions. In that case, it doesn’t work if each employee (i.e. citizen-developer) starts to automate their routines from the pre-digital era.

It’s a sad fact that real automation also makes some work unnecessary. If you just let employees automate something they don’t like, it doesn’t make a company significantly more effective. Of course, by getting rid of boring routines, each individual and department can become more effective. But in reality, significant changes need much more fundamental changes. A record shop doesn’t become a new Spotify simply because employees automate some of their routine work. And a bricks-and-mortar retailer doesn’t become a new Amazon when employees automates their routines. Those companies need a new way to operate with new processes and new roles for their employees. Uncovering existing processes and automating them might bring some savings, but if you create new ways to operate based on new tools, you can create a whole new business.

AI, digitization and automation (including RPA, robotic process automation) are at the heart of these changes. They are hype terms nowadays, and it is easy to make fun of them. Their reputations suffer if those technologies are not appropriately utilized; they become window-dressing, like lipstick on a pig. Suppose you put a little bit of AI and a little bit of automation on top of your old processes and systems. In that case, it is not making them more digital or intelligent, and it’s just adding one more layer of complexity and arguably, technical problems. Some companies would like to use machines to observe people and use AI to create automation to perform the same tasks. It sounds like an exciting tech vision, but it’s a strange idea that the optimal model for machines would be to copy how people have done something traditionally.

Henry Ford didn’t build a car for everyone by asking old-style workshop car builders to automate some of their routines. Jeff Bezos didn’t digitalize retail by asking guys who receive telephone orders and fill paper order forms to use VoIP calls and scan order papers. Google founders didn’t revolutionize the online ad business by making an online copy of the yellow pages. They created new models from scratch, how they could offer the best value to their customers with the latest technology. But many companies still try to develop their operations by adding new tricks to old models.

Automation, AI, and digitization will change most businesses, and they will significantly change the way information works. Improving existing processes is a multibillion-dollar opportunity, but creating new, more effective models to operate in hundreds of billions or trillions. Improvements bring short term wins; new operating and business models create companies that prevail in the future.

All these require courage from management and investors. They must be brave enough to discard old models to operate and old systems. It is nice to promise each employee that nothing will change or promise two per cent stable growth to investors. Still, as we have seen in retail, this model leads to huge collapses, significantly when competitors change the business and market rules. Those leaders who want to create big successes should start to build their operations based on software robots, AI and digital processes, not just hope the old models can be done a little bit better. And they should start today.

The article was first published on Disruptive Asia.

A personal trainer gives you instructions on what to do at the gym. In most cases, she or he asks only basic things from you, like your target, to either lose weight or grow muscles, and maybe how often you have visited the gym before. A growing group of wellbeing consultants tell you, how to sleep, eat and work better. They might ask you to keep a sleep and food diary. These days, people have more and more wearable devices to measure daily activities, heartbeat, sleep, blood glucose and many other things. But there is still a very weak link between data, wellbeing and training services. However, this will change.

I have read about sleep consultants whose primary task is to teach people to repeat some words when they try to sleep. They say it helps you to relax and sleep better. However, people nowadays have several devices that measure their sleep, heart rate when they go to sleep, sleep intervals, even body temperature and how tough their day has been. Wouldn’t it be better if those sleep consultants could utilize your data, and not only teach mantras?

During the COVID lockdown, many fitness centers were closed. They started to offer online services, including virtual personal trainer sessions, online exercise classes and videos on how to train at home. But this is mainly one-way communication. The fitness center doesn’t take your data to create a more personalized plan for you. Why not? Technically it would be quite feasible, but they would have to develop new services for this model. Many customers would be ready to pay more for personal services than standard classes.

The world is full of services to lose weight. People pay for online services to get instructions for daily eating and exercising. Some services help track your calories when you record your daily food entries. Most services are still elementary and don’t use data available from wearable devices. Nowadays, you can even track blood glucose in real-time. It would be quite useful with exercise, heart rate and sleep data for personal weight control services.

The wearable market is increasing. The smartwatch market, in particular, is growing steadily, approximately 20% annually based on market research and is expected to reach almost $100 billion by 2027 from $150 billion this year. Smartwatches take market share from some other early devices that only measured steps and heart rate data, basic things. At the same time, new categories are growing, like smart rings (e.g. Oura) and blood glucose, metabolic health apps (e.g. Levels and Veri). Withingswas part of Nokia for some years, but Nokia sold it back to its founders and wrote it off, just when the market started to grow. It is a company that has a more extensive range of products from watches to digital blood pressure and under-mattress sleep tracking equipment.

So, people are starting to gather a lot of personal data. But many people are still confused, how to utilize this data. Apple Health is a service that helps combine data from several devices if you have an iPhone. But it is probably the most confusing and worst UX product Apple has. As with business data, people need tools to utilize the data, and raw data is hard to understand.

There are also other health data sources. DNA tests offer information on personal genetic profiles. Digital health care records are starting to become available in some countries. This data could also be combined with wearable data.
This sounds like a perfect match. Wellbeing services should start to become more personal and based on real data, not only some standard instructions, because people are, in fact, individuals and different. Wearable devices provide more and more data points that are hard to interpret. Both those parties could improve their businesses if they learned to utilize the other party’s services better.

How can this happen in practice? There are, at least, three ways to do this:

1. Wearable device manufacturers could start to offer more apps and services to utilize data in daily life. They will probably do something in this area, but it is not their core business, and people should be able to combine data from many sources, not only use data from device-specific silos.
2. Wellbeing services could start offering services to collect data from different sources and develop ways to utilize them. But most of these service providers (gyms, personal trainers, or wellbeing consultants) are not data technology experts.
3. There will be players who help collect data from many devices and sources and offer it in an easy format. Third parties can make applications for people and wellbeing service providers to utilize the data. This is the most viable path to work with many data sources, have data technology competence, and work with many wellbeing service providers. This is also the best solution to guarantee the privacy of the data.

Any professional business consultant usually analyzes a company’s numbers and processes before starting to give instructions. It would be bizarre to have a consultant that would try to get a company to better health, without looking at its existing data. But in wellbeing consulting it is still very typical. This will change in the next few years, and we’ll see wellbeing services based on actual personal data. And this market will grow fast; people are ready to pay for better overall health and wellness.

The article first appeared on Disruptive Asia.

When I started my career in the 1990s, I worked as a software developer for a company that produced slot machines and casino systems. One day, a group of consultants popped up to our department. They came to tell us that our software development was not very efficient and that with new visual tools, the same work could be achieved much more effectively. They promised to redesign software for our latest gaming platform in six months with a couple of developers. We had previously taken two years with almost 20 people to do the same thing. Our management bought their story. So, they started to rewrite the software, and from then on, we all had to adapt to drag-and-drop visual state-machine development tools. 

The same is happening again. Low-code and citizen-development are trending again, and companies are actively selling their expensive tools allowing anyone to design software or automate tasks. Why have costly developers when you can teach your employees to manage their daily needs with simple drag-and-drop tools? The whole software industry will be changed again!

Office work automation (e.g. RPA tools) is one fashionable area citizen-developers have taken on. So, too, with data applications. Why have expensive data scientists when you can just offer low-code tools to anyone to get information and insight from raw data? I have even heard of those same low-code tools enabling individuals to make apps using their personal health data. Sounds nice?

Three months later, those consultants came back to us. They told us it didn’t make sense to redevelop the whole gaming platform software, but they could create a smaller piece to prove their case. So, it was agreed they would only develop new software with their model and tool in small components, starting with a device that recognized coins when the players entered them.

But is it so simple? Why are the world’s leading software companies in Silicon Valley paying $250,000 annually for good developers, if they can just take random guys from the streets (or at least offices) and get them to make software with low-code tools? Or why complain about a shortage of data scientists, if you can get any office assistant to find relevance from data with low-code tools.

Two more months (total time now five months) and the consultants came back to us. This time, they told it didn’t make sense so they would rewrite the code we had already done. They could write a manual on designing better quality software, and they could also sell their design tool to us so that we could use it to improve our software planning. 

Some people build their own home, and others use ready-made design drawings. But would you like to go to a skyscraper or a bridge designed by a ‘citizen civil engineer’? Or would you like to take citizen-pilot flight with an automated aircraft? Why is it necessary to have more expensive professional pilots?

I don’t mean we should have official accreditation to be a software developer, but it’s a fact that the most complex systems in the world nowadays are built with software. It is not simple to build complex critical systems. It is much more complicated than designing a skyscraper or a bridge. For construction, you have precise formulas to make calculations, but many structures of software solutions are so complex that you cannot have formulas or simple models to prove that they work. I have personally seen people with no experience or education, trying to understand how to develop software, especially robust software. It doesn’t work correctly; a study shows eleven of twelve citizen-developer projects fail.

There are tasks people can program easily. Some people make Excel macros for their own purposes. People make some simple tools to help them in daily tasks; they know how to use them, with no need to handle wrong data entries or particular situations. At the same time, it is not ideal to leave more complex software development to citizen-developers with these simplified tools.

It is also good to be clear with definitions. Sometimes low-code marketing uses examples, like design tools, that need no code at all. Low-code is a software development approach that requires little or simplified coding to build applications and processes. So, a drag-and-drop graphics design tool for end-users is not a low-code development tool until you want to convince your audience that it as a great example of low-code.

I was just listening to an organization that has invested in citizen-development tools and used hundreds of hours to teach thousands of their employees how to use these tools. But they can still only do basic things. The management admitted, they would not let them make any mission-critical or important solutions and processes or implement more complex software.

Finally, after six months in my early career case, the consultants could implement no software with their visual tool. They came to us with a manual for better coding and organized a half-day workshop. To be honest, after all these years, I don’t remember too much from that session, but one of their claims was that visual tools are better than software code, because people are naturally visual. Our developers disagreed with them because they didn’t feel these visual tools worked for serious programming needs. After the workshop, we never heard from those consultants, and we continued to make machines with professional programming languages.

Those consultants were paid for those six months and their design tool, then they found the next customer (victim). The same is going on again; companies are buying software licenses and training to get all their people to make software. Don’t get me wrong; I believe software development tools and methods are developing, and many tools can help. But it is crucial to understand the difference between personal tools to automate something or make Excel macros and making reliable software that can run many essential systems and processes. The reality is the world needs more professional software developers and more reliable software. We must not mix professional software development and its tools. With some simplified tools, every office worker can make some macros or automate their own simple tasks; they are totally different domains.

The article first appeared on Disruptive Asia.

This is normally the time to make predictions for the coming year. Typically, the focus is on tech and business trends and evaluate which ones could get next year’s timing right. This time it’s different. In 2020 the pandemic was a disruptor of normal trends. It stopped some businesses, changed some and accelerated others. So, what we can expect to see when vaccines hopefully turn the tide of the pandemic?

If we briefly summarize 2020, it accelerated digital businesses by a few years, stopped travel and hospitality businesses, moved many activities from bricks and mortar to online and taught people to use many new tech tools. In 2021 the questions are, which of these trends will continue, which will turn back time to pre-pandemic and which businesses have changed forever.

One or two years won’t change human beings fundamentally. People can learn to use new services and products, but basic needs don’t change. Let’s take, for example, how people have adapted to food delivery services, but they still want to meet other human beings. People also look for easy solutions but usually hesitate to do things they don’t understand or haven’t tested. But home delivery and Zoom meetings, because they had to be adopted, became everyday options, that we quickly learnt to use effectively. 

So, what’s the outlook for 2021? We must think about the things people have learned in 2020 and also what they missed in 2020. Then we must also consider which technologies and services took a leap in 2020. We can also evaluate, which trends started before the pandemic, and those that the pandemic has accelerated. Based on this, we can assess a little more accurately what we can expect to see.

Digital services are helping people in many situations. Virtual meetings help us save time and money. Digital signatures make it easier to handle agreements and use legal services. Home delivery makes grocery shopping more straightforward and faster. Sometimes it is more effective to work from home. These have been obvious changes in 2020, but they are still good examples of trends that will continue after the pandemic.

Airlines, hotels, restaurants and many other hospitality services took quite a beating in 2020. Many people have changed their views on travel and eating out, and are questioning if they need to take so many flights in future. This part is probably much more complicated. People still want to see new places, see other people, and break from daily routines and environment. But at the same time, many businesses are probably having second thoughts on the value of business travel and physical meetings.

People now see the value of physical meetings and hospitality services in a new light, having lived without them for so long. People have also noticed they can work just as effectively from home or remote places. Nevertheless, data indicates that flight bookings for late 2021 are strong and that new business models, like monthly subscription for flights, are emerging.

Retail businesses have suffered most from lockdowns and restrictions. Many retailers, even well-known, long-established department stores and chains, are closing down. But it would be a mistake to think the pandemic has been the only reason for this. Bricks and mortar retail has been in trouble for years, and surprisingly, why it has taken such a long time for some customers to adopt online shopping and use home delivery services.

The COVID situation has not only impacted consumer businesses. B2B business has also changed. We haven’t had trade shows, conferences and meetups to find new products, services and contacts. This has pushed the adoption of ‘self-service’ online sales channels, but at the same time, traditional ’face-to-face’ sales are vital for most B2B businesses. There is no doubt that B2B companies have also suffered, and there will certainly be bankruptcies after the pandemic when companies are forced to take a reality check.

Based on the above, here are some of my predictions for 2021:

1. Travel, hospitality and service businesses will increase when the pandemic restrictions and risks are over. This doesn’t mean all companies in the sector will survive or that the services will be the same as before 2020. Still, it will be an excellent time for new companies to enter the sector, acquire some existing businesses and innovate new business models.
2. More retail business will go online, and high street stores will continue to fail. 
3. More services will go digital and online, but it doesn’t mean that all new digital services will be profitable. Competition will be fierce in many areas, and companies will need to achieve significant volumes to survive. Many will need to go global to achieve this. 
4. A more significant opportunity than digital consumer services will be enabling components that make it easier, safer and more effective for consumers to use services. These will include better utilization of data for consumers, better trust in services and third parties, and solutions to improve customer experiences (e.g. VR/AR for shopping, better platforms for remote education and better solutions to manage home deliveries).
5. Commercial real estate business will go through significant changes. Many retail stores will disappear, office space needs will change, and new requirements will emerge. For example, companies will need new office space types to accommodate people that work from home, occasionally coming to the office, something more akin to ‘hot desks’ than cubicles.
6. E-commerce operations may need to enhance customer experience and marketing by utilising showroom type places, where customers can physically see the products and make orders, and where companies can promote their brands. Coffee shops and restaurants will also need more space to accommodate social distancing.
7. People will become more aware of health and wellbeing issues, and wearable devices to give them more data. This will create many new digital services to improve wellbeing and monitor health and get remote healthcare services when needed.

These are just some examples of what we are expecting, but they illustrate the changes and trends we are going to see after the pandemic. Of course, the biggest question is whether mass vaccination will speed the return to some normality or are we going to encounter some new surprises. Anyway, we must always prepare for the next phase in business and be ready when it comes.

The article first appeared on Disruptive Asia.

TikTok is a big success story but also a big political issue. A lesser-known part is how TikTok is disrupting the social network model in its virality. It reminds me of the old debate, which is more important, personal interests or social networks.
Is it possible that the traditional social network concept has reached its limits? Is the TikTok model changing the whole social platform landscape?

Over 15 years ago, a small team and I started what was probably the first social network data analytics company in the world (Xtract). This was well before the success of Facebook, LinkedIn or Twitter. We started to work with different kinds of companies that had some social connection data, including telco and online services. We made tools to analyze the data with the intent of targeting marketing activities.

Our software analyzed billions, even trillions of data points, and we did research, too, on how influence in social networks works. Why would people be influenced by other people to buy something, churn or become active users? The outcome was that it was not only the influencer or social network that mattered. It depended also on the context, for example, which product was in question. It is quite natural to understand how one person can influence you on which car to buy, and another person which books you read, and sometimes your own opinion might matter more than that of your social network.

There are many ways to analyze consumer behavior to understand preferences and how best to profile them. Profiling can be based on all kinds of available data, but we can divide it into four main categories:

1. Demographics (e.g. age, gender, living area, education)
2. Behavior (products you use and buy, newspapers you read, music and movies you like, hobbies, etc.)
3. Social network (whom you are connected to and how strongly)
4. Psychometrics (e.g. personality types).

Social network services have been a big success story during the last 15 years because they have been able to capture user’s time and also advertisers. Social graphs play a vital role in those services, i.e. people share content with their contacts and its how things spread among the users.

Now we come back to TikTok’s model. It has snowballed, with over 500 million users globally. But TikTok is not really a social network service, even though virality is at its core. People are sharing videos, not primarily to their social network, but instead based on categories and hashtags. Users have excellent tools to make their videos, and they can utilize existing ideas and materials, e.g. duets with other videos, and then share them. They can also see how different categories and hashtags get views and also target their videos based on this and in that way to utilize ‘trends’.

This model also gives much more opportunities to new users to attract lots of viewers. In the traditional social network, it takes a time to get contacts and followers. And in the conventional video services (like YouTube) the algorithms favor those who have published for a long time and amassed a large number of views. It is sometimes said the Chinese business model with less respect to IPRs and copyrights allows everyone, every day to take the latest ideas and products and try to make them better for tomorrow. TikTok, in a way, follows that principle, everyone can see the trending content and utilize it to build his or her own success.

This is not only relevant for TikTok and videos. In a recent discussion with the chief scientists of our earlier data analytics company, we came back to the old theories on how personal interests and social networks drive behavior and could we see TikTok phenomena in some other services too.

We concluded that actually, we see limits in social networks in having discussions about interesting topics. For example, on Facebook, your discussions have been limited mainly to people who are your contacts. If you have a special interest area, after a few years with the same friends, it is not so fruitful to discuss there anymore. Hashtags don’t work on Facebook. It is the same issue in many social networking services, including LinkedIn. On Twitter, you can better follow specific topics. Still, it has so many messages that also there you must typically focus on the most popular messages from those who have a lot of followers.

Then we come to another problem of social networks. They have a lot of fake profiles, and people’s networks have been diluted when they have accepted too many friends. So, social network services have a dual problem: they limit your discussions and available content, and they don’t actually represent your real network. For example, if asked by each of your LinkedIn contacts if you would make an introduction to a close contact for each of them? I couldn’t do it because my network is so extensive, and I don’t know all my contacts well enough. When we can only have one network in a service, it includes too many connections for multiple purposes, like building real trust, but too few contacts for special interest area topics.

Could this mean that TikTok is not the only video platform that is a problem for many politicians, but the first sign of a new type of internet service to come? Could we start seeing more services that can combine people’s different interests better, help to get attention to interesting content without a huge follower base and enable us to create social networks around different interest areas and purposes? We would also need services where you can build trust networks for various purposes. Who are people you can recommend, who you trust to get business introductions, who you want to network with for your work, and what is your real personal trust network?

Maybe we will soon step into a post-social-network time that tries to better combine natural behavior with personal interests and different networks for different purposes. This can mean, we see two types of networks: 1) those that enable you to focus on your interests whether music, literature, science, special hobby or whatever; 2) real trust networks for different purposes, for business, personal life, hobbies and personal interests. The current social networks are now too much of everything and too little of anything.

The article first appeared on Disruptive Asia.

The dictionary defines trust as “to believe that someone is good and honest and will not harm you, or that something is safe and reliable.” Trust can be a difficult thing for people to grasp, but in the digital environment, it can be even more complex. We need trust in most daily situations, but with digital, virtual and cyber services such important parts of our lives, we need to better think, what digital trust really is.

The Covid-19 situation has accelerated the use of many virtual and digital services. In early March I was told that I must travel physically to sign an estate inventory for a meeting with other heirs. In April I was told I must not come physically and I must sign documents online. For me, this is a good example, how rapidly things can change, when otherwise it could take 10 years to approve this kind of change for laws and rules.

Even basic things, how to sign documents online is quite a mess today. DocuSign has a good position globally to sign documents, but it is not ‘official’ in all countries or situations. It has great usability, but it includes compromises between usability and security. In some countries authorities, banks or other service providers offer more secure signing solutions, e.g. based on e-ID cards or mobile identity tokens, but they are more difficult to use.

Maybe the strangest document signing was one official service in the USA, where signing was to type my name between slash symbols (seriously, this was the instruction: “The appropriate person must electronically sign the form by personally typing in any combination of alphanumeric characters preceded and followed by the forward-slash symbol (/); e.g., /mike miller/, /efr/, or /374/). This electronic signature should not be typed in by someone else on behalf of the proper signatory.”). Another extreme is my Hong Kong-based bank that compares documents I send to a sample of my signature and every second time I fail to write my signature in the same way.

Signing is just one very simple example of trust, but we have more complex things. Is the person I meet really who they claim to be? Are they going to keep their promise? If I talk confidentially, are they going to keep this information to themselves? If they buy something from me, are they going to pay, or do they have money to pay? These and many other questions in business and personal life crop up.

In physical life, we have solutions to handle several trust questions. People have ID cards to prove their identity. There are systems like credit scores, payslips and financial statements to prove the capability and history to pay. Human beings have also learned all kinds of signs (how people behave, facial expressions, personal history, and many other things) to make estimates, who and what they trust or don’t trust. Often the trust is also transferable. If I trust someone and he recommends that I trust someone he trusts, I will probably trust them.

In the online and digital world, we have more components and variables to evaluate and it makes it more complex to evaluate trust. Maybe we don’t see the other person at all, only his telephone number or email address. If we see someone online, how do you know the person is really who they claim to be. When we physically meet, people build trust with each other over time, but how can this work in the digital environment. If I share some documents and information online with a person, how can I ever know if and how the other person uses and shares them?

We also have solutions to handle these things virtually. For example, we need security devices and apps to get to our bank accounts; companies have access controls to their services and networks to use their virtual tools. For many of these services you still need to do something physically, e.g. visit somewhere or send some documents by mail. But doing something physically first is really a usability challenge for many online services, and COVID-19 has now put us in many situations where it is not even possible.

This is exactly the reason we have lower security in services where usability is better and it is not too difficult to start to use them. DocuSign is enough for many signatures; Zoom is secure enough to handle meetings; WhatsApp is the easy solution for daily chatting and email is the easiest way to send many documents. But we have seen enough cases that these solutions have also their risks, sometimes significant. We know they are enough for most needs, but many needs also go beyond the trust level they can offer.

This has demonstrated, in a very practical way, that we need new solutions to handle digital trust in daily situations. Those solutions need to have good usability and offer the right level of trust for each need. The cybersecurity discussion is easily very polarized. We have cybersecurity freaks that claim no system is secure enough and that no system with ordinary level usability can be secure. Then we have those ignorant people who are ready to use any system that is just an easy solution. We have many kinds of solutions for digital identity and security, but as a whole this area is still quite messy.

One reason is that the thought process to develop them is often very technical and focuses on one specific aspect of security. Maybe we should think more about what trust really means in different situations, and how people have handled it for thousands of years. A simple example is transferable trust or how your personal trust network could help you in digital services. Maybe in that way, we can find concepts and technologies to create real digital trust between people and devices.

The article first appeared on Disruptive Asia.

People networks shape the world. Niall Ferguson’s book The Square and the Tower gives an excellent introduction to their history. Networks have played an important role in politics, business and daily life. They can be very public and transparent networks, or secret societies, or even fictional like parts of the Illuminati network. 

Official organizations can be very different from real networks. We all know companies where the organization chart tells one story about who makes decisions and the actual network of people that make decisions are very different. Networks can also be more dynamic than official organizations, and they can survive changes.

Companies try to become more dynamic and agile. Often organizational structures create friction to be dynamic, react rapidly or to be proactive in business. Organizations themselves could be more dynamic but then comes IT. Processes are applied to complex IT systems, but it is tough to change tools and IT solutions quickly. We have heard stories on how a CEO can use his or her network inside the organization at different levels when some quick changes or new activities are needed, and the organization is too slow to implement them.

Many organization structures and management practices have their history in military organizations. Nowadays, many people hesitate with military management styles in business, because they are seen as old-fashioned, command-and-control models. But it is important to remember that military and security environments can still also offer examples and lessons to very modern organizations.

For example, military organizations have traditionally operated with very formal models. When armies fight against each other, they have front lines, concentrate troops at points where they can make breakthroughs and defend borders. This is no longer the reality. Guerrillas, terrorists, activist cells, unofficial troops (like in the Ukraine) and dynamic networks are a more significant risk to many countries than traditional forces. Fundamental new models are now required to operate and manage military and security organizations. 

Wars in Afghanistan, Iraq, Ukraine and Syria have not been about fighting between official armies, and many countries have seen attacks from local terrorists, and independent cells or individuals that have are often associated with global networks. This has forced military and security organizations to find new models for fighting against these enemies. It also means their own organizations need to be more dynamic. 

Military organizations have traditionally had very hierarchical structures. Their operations and technologies were built to support those models; command chains, rights based on organizational position and limited communications between parallel organizations. Now they have been forced to rethink their existing models. At the same time, consumerization is coming to armies too; people are using mobile phones, social networks and messaging apps during operations. Military organizations can either ignore or ban these tools or start to utilize them. Some have already taken the latter route. It also changes, how organizations operate, and especially how they can become more dynamic networks based on the situations, needs and resources.

Many companies have similar needs to find more dynamic models to operate, adjust processes based on needs and use resources rapidly where needed. This is easily in conflict with the organization charts, fixed procedures and IT systems that support processes, information sharing and communications. These needs are not only inside organizations but also with customers, partners, suppliers and other parties. It is more challenging to create and maintain dynamic networks within traditional organizations and their contact points. Networks can sometimes be different, some more hierarchical, some based on other trust artifacts. 

All this creates new needs with ICT technology to support these networks. In practice, they use informal ways of working, like video phone calls, group emails, and WhatsApp groups. But those unofficial methods don’t really include ways to manage networks, security or the systematic use of different tools. They are used to handle specific needs, not to manage networks. Most business tools have been designed to work in traditional organizations, with hierarchies, formal structures and stability.

Networks are a traditional model for people to cooperate. Digital technology offers more tools to work globally and create all kinds of networks for general or specific needs. But we don’t yet have the tools to operate these digital networks the same way people have learned to manage networks in physical life. They are based on trust that you earn and lose, and they are adjusted to daily needs. We will see new solutions emerging in this area and how the military, businesses and individuals can better create and manage digital networks.

The article first appeared on Disruptive.Asia. 

Picture courtesy Avexer - local trust networks in crisis management.

Wouldn’t it be nice if a web store could propose the exact products you want? Or your online newspaper had news and TV series you are actually interested in? Or a user interface adjusted automatically to your requirements? These have been ideas I have heard many times during my 18 years in the data and analytics business. The problem is that those terms are mainly used by people who don’t know what they are talking about when talking with other people who won’t admit they don’t know what they are talking about.

To simplify, personalization is typically based on one, or a combination of three things:

1. what preferences you indicate (e.g. tick boxes);
2. what you typically buy and how you typically use a service; and
3. what other similar people buy and how they use the service.

But none of these are as simple to realise as one would think.

When you ask preferences from people, most tick all boxes or no boxes, they either don’t concentrate or know what they really want. And if they indicate their preferences today, there is no guarantee they will match tomorrow’s preferences. 

Models can learn from yours and other similar user’s preferences. The system then starts to offer specific offers to you, that you may or may not use to buy those specific things. This in turn reinforces the system believing that you are interested only in those things. It narrows the options and offerings to you and in turn misses many things. The same happens in services like Facebook, and how it selects which people and posts to show in your daily feed.

Another angle is that the system doesn’t even try to serve or help you better. It just tries to maximize sales or keep you engaged in the service. It offers you products and content that you are likely to buy or click. It focuses on maximum, short-term monetization. 

These issues are not new. People who work with personalization, machine learning and analytics have talked about them for over ten years. But it doesn’t stop many people dreaming about personalization, putting it in their business plans and presenting it as a key use case for ML and AI.

It is not impossible that personalization could be more useful and one day we will have really valuable personalization that actually helps users. But it needs much more than what many solutions and business plans offer today. A fundamental starting point is to really understand, what people want to do and achieve in each use case. It is much harder than optimizing some clicks or processes.

Let’s take some simple examples:

• People still like to browse printed papers and online publications, and not simply focus on articles selected for them – a significant part of the browsing experience is to find things you were not specifically looking for or expected.
• Customers also like to walk around in physical stores and browse many products on the Internet, just to see different choices, get new ideas and pass time. Then there are other situations when they just want to make an immediate and specific purchase.
• Your earlier purchases or actions don’t necessarily mean you want to do the same things again.
• Movies and TV series that are recommended to you based on earlier watching behavior may not really be what you want to see, especially when based on a simple categorization of the content that doesn’t really understand your preferences. People can experience similar content in many different ways, which is completely beyond a simple ‘tags’ choice tree. 

These are simple examples, but they illustrate how personalizing an experience is not a simple algorithm achieved by optimizing a few variables. The system should know your preferences now, your state of mind, the real reasons why you have done something earlier, and it should be there to help you, not just to sell you products and services.

Personalization and AI are terms that have been diluted with stupid use and marketing of the terms. Both of them will be very important in the future. But many existing solutions and especially business plans are crap. They are crap produced by people who don’t really understand people’s needs and technology, but love to give the impression that they understand both things.

There is no simple solution to change the situation for the better, but there are certain things that would help, for example:

1. AI and personalization services that work for people that help to make the experience better based on personal data, not just to sell you more or hook you to a service.
2. Models and analytics should be based on richer use of data, not only analyzing actions in one service, but putting them properly in context and anchoring them to your characteristics.
3. Use proper terms for things, e.g. sometimes optimization of the buying process is a more honest and correct term than a fancy AI-based personalization,
4. When people market AI personalization, try to dig deeper into what their system can really do with difficult and concrete questions. Don’t accept statements like, “it is amazing, how great algorithms developed by very smart guys can automatically find you the best options,”
5. And, at least, try to analyze your own behavior in different situations, and see, what kinds of personalization could really help you in daily situations.

​Of course, there are smarter and smarter systems all the time. People are getting worried that AI knows everything about them and can utilize all that data. A system can have too much of your sensitive data, but often systems are more stupid than people expect. Real development happens with solutions that offer specific solutions for specific needs, not with those big plans that claim to solve all needs with big data and general personalization algorithms. And if it is your data in a system you can manage and that works for you, then at least you are represented and know the incentives the ‘intelligence’ works toward.

​

At Prifina we are grateful to be able to work in collaboration with leading software developers in different companies and in open collaboration. We’re also fortunate to have the chance to work with amazing new technologies like GraphQL, that unlocks much more flexibility and permeability than their predecessors like the Restful API setup. 

Every once in a while we notice there that something new doesn’t have full support available for something we want to do, where we have to solve what looks like a common problem for ourselves. As we’re building our own solution to what seems like a common problem, our solution is to release it to the public domain. 

This post is about a GraphQL Data Model Editor we've built together with Startup Commons and Grow VC Group and are now releasing, so we can develop it together in collaboration with others that see value in using it.

What we’ve built: The GraphQL Data Model Editor

​Here you can see the clickable prototype. Feel free to add comments, questions or suggestions.

A complete application to create, document (for the business user and the technical user), edit, manage, publish, populate, test, verify and deploy data models in SLS to AWS, and use this model to spin up AWS infrastructure. 

Building and documenting the data model

Publishing and connecting the data model to AWS

In our internal setup, this published SLS data model can be deployed directly into AWS and used to spin up the needed backend setup. It can also be used to make amendments into the existing infrastructure, which naturally requires clear versioning, deployment protocols and access controls. 

Further development

We see the need for further development in at least the following areas:

1. Versioning (think Google docs)
2. User and access management 
3. Setup to spin up fake data en masse to populate and test data model (using e.. Faker https://github.com/marak/Faker.js/)

​

How many times have you heard that the current pandemic crisis is also an opportunity? People are repeating the old John F. Kennedy quote about the Chinese word that meant both danger and opportunity. I have now seen dozens of business plans for mobile apps to get COVID-19 under control, a new tool to work remotely, enabling e-healthcare and many other similar ones. They are probably important things, but if you want to build a longer-term sustainable business during a crisis, you must go beyond the ‘obvious’.

It is important to have a concrete need, when you want to build a new product or business but, in reality, it is not so simple. When you read that people want to buy a lot of toilet paper and cans of tuna during a crisis, it can be a good business to go to sell them immediately – if you happen to have them. But it doesn’t mean that you should start building a long-term toilet paper and tuna business from scratch. Furthermore, it may also be a brand and credibility risk to jump on a bandwagon and chase a short-term trend linked to COVID-19, unless you actually have a valuable contribution that isn’t a repurposed afterthought. But an innovation could be, how to make the logistics for these and other products better, or how to guarantee the availability of basic items in all situations or help people to manage their needs better so that they don’t panic.

When the Internet became mainstream in the late 1990’s, many people wanted to start a dotcom business. When 3G came, many parties started developing mobile Internet services. When Apple opened the App Store, people started to make mobile apps. And when blockchain became well-known with bitcoin, people wanted to be bitcoin investors and build blockchain services.

But how many were actually successful? Very few it seems, but at the same time, those were important turning points for many new products and businesses. It is also highlighted that the winners are not necessarily those who go digging for gold in a new area, but who facilitate something new for these areas and people. Think of what Levi Strauss, Wells Fargo and Domingo Ghirardelli did during the California gold rush.

This is a very difficult time for many businesses and entrepreneurs. We will see in the future how high a price we will have paid for the effect of lockdowns in the economy and businesses, as well as indirectly in the lives of people, their health and long-term wellbeing. This is also the time to plan new things and start to implement them, but you must go beyond the daily demand to build something sustainable.

This lockdown period has changed the behavior of people. People have learned to work remotely, order online, use e-health services, study online, handle online meetings, sign and confirm things digitally, agree on a mortgage and home buying digitally, host social after-work sessions and many other things. And there are a lot of much less obvious changes in the market and behavior of people. When you now want to build a longer-term successful business, focus on the projected changes in the market and people, not today’s short-term demands.

It is important to remember that it‘s not just about building new services you believe will have demand in the future. But it might be that you can facilitate a platform, enable development or offer some fundamental components for those services. For example, consumer business is always hard to predict, let alone who is able to make a version that is a big success. But if you can build a component that all those new consumer services like to use, it might be a better bet. It is said, you should first focus to be #1 in your own potential market, no matter how small that market may be, if you have any hope of becoming #1 globally.

Doing things digitally online is now the first layer of most new services. What could be the next step? Data is becoming more important and now governments also want to track your location and health data. This probably raises more fundamental questions about data management and ownership models, when the crisis is over. Or if office work is now done more remotely and with online tools, could we at the same time automate them more? Or if we teach people online, can we also have AI solutions to handle more personal teaching, when a teacher cannot handle all one-to-one questions. Or if people start to make more virtual communities, how to handle trust and ‘hidden-hierarchies’ that exist in all important communities and clubs. Just to highlight some potential trends.

This is a difficult time for many people. Planning and building something new is important not only to create for a future lifestyle or business but also for mental stimulation. It is fundamental to focus on hope and the future. In many businesses and professions, it is also mandatory to focus on new things, if the old models have collapsed. But please, go beyond the obvious. If you see dozens or thousands of other people trying to promote a new idea or business, forget it. Take your time, and try to see and analyze, what is fundamentally behind those obvious phenomena and what value you can create for the long term.

The article first appeared on Disruptive.Asia.