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.

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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/)

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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.

Cash flow management one of the most important management tools for any startup or SME. Especially, it is important in special situations, like the current COVID-19 crisis. There is no miracles, how you get enough money, but at least you must know all the time, how much money you have and how much you will have in the next few weeks or months. it gives to control on the business and time to find solutions.

Grow VC Group together with Startup Commons (its portfolio company) organized a webinar to learn basics about the cash flow management. Jouko Ahvenainen, a serial-entrepreneur, who has seen several external or internal crisis in growth companies talked about tools and practices to predict and manage the company cash flow. The session has many practical tips and models to manage cash flow and also handle cash flow problems. It also reminds, the management team must work with the cash flow, it is not something finance team only does.

​You can watch the whole webinar on this YouTube Link. You can also download the presentation below.

You can also find more about Startup Commons' material that is now free for entrepreneurs here.

A friend recommended that I read an article, how McKinsey Destroyed the Middle Class. It basically summarizes how management consultants and elite business school MBAs had taken a bigger role in many companies, making middle management less important and placing ordinary people to execute simple tasks. The article also emphasizes the political aspect, and why liberals are skeptical about former McKinsey consultant and ex-Presidential candidate, Pete Buttigieg. 

But I think the story is more complex and we can already see transitions in other directions. Management consultants have often created puritanical processes and focus in many companies. But those companies have also become very vulnerable to any changes occurring inside or outside the company. More and more startups challenge them by changing the rules of business, but changes in software and the more important role of developers is also changing this top-down thinking.

We can see how consumerization has spread to companies. Employees use their own tools and software to do work more effectively than the top-down processes and legacy IT systems would do. Some innovative companies, like Supercell, have created models of more independent teams where this is possible. And in Silicon Valley, companies have already become frustrated with the traditional top down model in B2B sales where you can easily spend months or years and millions of dollars to get a corporate deal.

Open source and cloud companies offer software components and services for free or for a very low price and employees can start to use them almost independently. They can sometimes submit those small costs with their normal business expenses and no formal decisions are needed. Software developers, in particular, have felt it very difficult working with legacy IT systems and slow-moving processes when better and more effective solutions are coming to market all the time.

There is a link between elite management consulting principles and people who just start to use tools independently, or developers that make better solutions independently from open source components. The latter group are challenging the power and top down thinking of top management and inflexible models to create things. They feel, they want to make things better and use their own brains to make them better. Some could say this is part of a counterattack of the middle class.

Of course, things are not always so simple. Some visionary people in top management are happy to see this. They can even encourage lower level people to use their own brains and make things more effective and better. But there are also people in the management teams that don’t like this kind of development. They can see it challenges their position, or even worse, they cannot use projects in the traditional way to promote their own career paths inside the organization by taking credit.

I was able to participate in an interesting project of a military organization where they looked for new and more dynamic models to operate, especially in the gray area between a war and peace; Ukraine’s crisis was an example of this. The project included models where local members of the military can organize things bottom up, when something unexpected happens rapidly, and to use their daily tools like mobile phones and messaging services to organize things, yet still keep them in control. It was a very good example, how the use of everyday devices and software have empowered many more people to do things independently. The biggest challenge for the project was that the traditional big-dollar military suppliers and career officers didn’t feel they get much value from it themselves.

I see more examples of this in my daily businesses, for example,

• Prifina is developing solutions where people can manage and use their personal data to challenge the dominance of big data giants. Prifina alone has more than 11,000 developers interested in the project and also make open source components from volunteer work to enable this. There are also other communities and activities in the same field.
• Robocorp enables the use of open source software and cloud services to make RPA solutions. They have created a new job category called Software Robot Developers, basically any talented software developer can start to implement and offer software robots to handle all kinds of daily tasks. This is very different from top down models where consultants identify processes and then hire IT consultants to implement RPA solutions with expensive software licenses.
• Many distributed models, like distributed ledger or distributed AI, are looking for models where independent people and smaller companies can work as an equal partner inside a network, not where a big company makes the rules that impact subcontractors, too.

​We are seeing the dominance of the management and process consultants getting weaker. Of course, things don’t happen overnight, but we have seen the turning point. The political impact can be more complex to predict. And then there are also more complex cases like Uber in the Atlantic article, where there is literally no corporate hierarchy through which drivers can rise up to join management. One can argue it is really an example for top down control, but at the same time it offers more independent work for many people to drive and make money as they wish. In business we see many nuances of these models, politicians today prefer to see things as black or white.

The article first appeared on Distruptive.Asia.

Once upon a time, in a small and dark country, there was a small bank. Well, actually, it was not such a small bank for this country. It was also an important bank for many people, especially in the countryside, because this bank was also near its customers and the local staff really knew those customers personally and had forged meaningful relationships. 

The leader of the bank had a vision. He saw that banking business would change and that it would be better to act before that change happened. He wanted to drive the change, but he was leading the change from the castle in the heart of the capital, and well away from his customers.

They decided to innovate at the bank. They thought that very basic saving accounts and offering loans with heavy paperwork were not the businesses of the future. They thought it would be a great idea to offer people new services they would really want to use and integrate finance options to those services. People, they thought, weren’t normally looking to them for a finance service so why not to offer them together. They could combine their old strength of knowing customers personally and utilizing modern technology and new services.

They hired many new people. People who had technology competence to build new modern services, people who had created new businesses from scratch, and people who had seen elsewhere that it is better to act before disruption destroys a business.

These people were excited about new opportunities to build a totally new business. They got freedom to develop new ideas and implement them. The bank was to have a new and more important role in its customers’ lives.

However, there was also a group of traditional banking folk inside the bank and in the finance sector. They didn’t really like that the bank was starting to do something that was not ‘traditional’. They felt the bank had broken the rules and it became difficult for them to tolerate this rebellion any longer.

Other people inside the bank also felt they were not in their comfort zone, with all kinds of new things happening. They complained, that it was confusing. From this an ‘empire strikes back’ plan was hatched.

When it came time to get a new leader for the bank, it became an opportunity for the old banking gang to get control back. They started their work to ensure the next leader would take a step, no, many steps, backwards.

Their plan worked. They managed to get a traditional finance wizard to lead the bank. He had the track record of doing things the traditional way. He had also read more traditional business management best sellers than most airport bookshops stock. He was an excellent leader to implement the ‘empire strikes back’ plan.

It didn’t take long time for the plan to start working. The bank decided to stop new activities, and focus on traditional banking. People who came to the bank to do new things, decided to leave. And those who decided to stay, started to repeat the mantra “it is great to have a clear focus, it was so confusing earlier,” although earlier they had been excited about new things. But they were also smart people and they wanted to protect their positions under the new leader.

The new leader wanted to make it clear, that this was another new era in the bank. He wanted to take the bank back to the local social clubs of the bankers in the country. They didn’t want to use modern digital technology, instead keeping their old IT model and developing it further.

By adopting a puritan management and process consultant attitude the bank not only killed off the innovate trial and learn model, but it also managed to get rid of the traditional strengths of the company – the local presence and personnel that really knew their customers personally. They wanted to take the HSBC, Chase, or you name it model and adopt it to this small bank without realizing even the big banks were struggling with fintech and other disruptions that were emerging.

It was a successful ‘revenge’ by the old banking gang and process consultants. The new innovations and businesses were killed off within a couple of years, and not only that, but the personal touch went too. No one can say they were ineffective because peace did come back to the bank and the local finance community. People in HQ were happy in their comfort zones and continued their old activities as if nothing had happened.

They are now living happily ever after, or at least they will be, until the day the disruption wave really comes and changes everything. In some markets, it might have arrived already!

The article first appeared on Disruptive.Asia.

Photo: Sleeping Beauty Castle, Wikipedia.