Sebastian Jakubiak

The most fundamental advantage of data – besides they carry information – that the data are finitely copyable. As they so easy to replicate, with no marginal cost, data can be used by all the people. It’s often claimed that data is like water. On the other hand, it is quite easy to make the data to be restricted by sophisticated algorithms of encryption, so no-one will be able to get an access to. In fact, this kind of the data you have to “refine” before transferring into asset. So, the data by dint of oil metaphor could be “refined” like oil. Online advertisement sector is probably the biggest marketplace for personal data. “Refined” clicks there are bought and sold instantly. As you see there is no one single data economy, but at least few. Blockchain layers of data (like BTC) are among others financial data economy with its own ideology. So, if you think it’s feasible to build competitive advantage based not on the free data – you’re absolutely right. It’s high time to dive deeply into the question: How to “refine” them?

The data economy is in progress. If you consider the wealth which comes from the data economy and the distribution of the wealth it shows us the data economy – which we’re actually generated – is very unequal. In the most recent quarter Amazon, Apple, Alphabet, Microsoft and Facebook made a combined profit of $55bn, which is bigger than the next most profitable US companies during last 12 months. During the Coronavirus downturn it will definitely increase their revenue as the e-commerce is blooming and home-office communication tools are new standard for conferencing. But there are also findings that every single statistic dollar which flow through this companies generates additional 6 to 9 dollars in surrounding partnering business across the digital value chain. How to take a piece of that cake? That’s not easy answer, but we will try to do so during this meeting.

Among mind-blowing things about AI you know already are Reading (OCR), Seeing (camera detection) or Speaking & Listening (Siri, Alexa). But when you broaden your imagination further you could ask yourself. What else AI can do? Could it recognize you on the street? Could it detect when you’re lying or Could AI read your mind? In this speech we will also ask ourselves what AI can do in really mind-blowing things we’ve reserved only for humans. We will also dig deeper with the question: Why AI do it better than humankind?

Among mind-blowing things about AI you know already are Reading (OCR), Seeing (camera detection) or Speaking & Listening (Siri, Alexa). But when you broaden your imagination further you could ask yourself. What else AI can do? Could it recognize you on the street? Could it detect when you’re lying or Could AI read your mind? In this speech we will also ask ourselves what AI can do in really mind-blowing things we’ve reserved only for humans. We will also dig deeper with the question: Why AI do it better than humankind? Artificial intelligence is in fact very sophisticated statistical algorithm of machine learning process which in general terms using neural network idea started during mid ‘60 of the last century. During last eighty years it has developed in so advanced form it recommends you the way to travel from A to B. Even if during this process it can calculates thousands of possible variants it can pick the only one best solution. But finding digital truth is not an easy task to complete. From the business perspective it became even more difficult and more important. More difficult because data sources are constantly evolving and multiplying. More important because i.e. decisive support from AI could ruin or grow your business. Are you ready to take a grip on the throttle with AI name on it and accelerate your business? Ladies and Gentleman. Please fasten your seatbelt.

There are four V’s of the data: velocity, variety, volume and veracity. Each of the data your company collects enters into one of that categories. As an example of velocity is data which are transferred continuously from sensors measuring i.e. speed or acceleration of your car. Variable data are so unstructured and change so frequently that is impossible to recognize the pattern. There are also huge volume data lakes like picture database or you-tube which are storing unimaginable amount of data in volumes exceeding rate of review them during the same amount of time they are generated. The last category of the veracity data is untrusted or uncleaned data. There is no-brainer Artificial Intelligence can refine the data from all of that categories. I make a bet your company is in statistical 95% which don’t care enough for their data or do not generate good return on that most promising asset. Let’s take a chat if I’m right or just a little wrong.

There are around 2 million of different artefacts (like items, things, objects) which goes through once hands during statistical lifecycle of a single person. For the next 20 years this amount will grow at least twofold. It’s estimated that next generation will touch 4-6 million of different artefacts from the moment of birth till the very end. But at the same time the intelligence in the objects will flow as easily in them as the electricity in the past, so in the future there will be only intelligent objects (smart things). They will “talk” to one another in their own language and perform interactions we as humans will be not aware. Let me tell you how this three basic laws of IoT: the Moore’s Law, the Metcalfe’s Law and the Koomey’s Law will reshape the landscape of smart things in this next generation and what consequences it’ll cause for the business.

The sensor name is partly borrowed from Latin sensus which stands for: to sense, to feel, to mean, to perceive. Initially they reflected human senses as seeing, hearing, smelling, so you can find as simple sensors: cameras, microphones or smog detectors. But as technology develops this kind of sensors became even more sophisticated. Modern cameras can recognize your face or (after Wuhan case when the people started to wear masks) can perfectly identify person based on the unique style of walking. But there also very cheap sensors which are already almost everywhere, like temperature sensors, accelerometers, gyroscopes, pH, infrared, light, proximity, and so on. Quite often this kind of things are parts of the very sophisticated networks responsible for detecting incoming failure in machines like jet engines. Associated with the sensors are also new forms of servicing as i.e. preemptive service when the fixation or replacement of the part become just a little earlier than the failure itself. If you want to know how to setup a new business model for industrial IoT let’s talk.

If we could personify the bits, we’d say that bits want to move, bits want to be linked with other bits, bits want to be reckoned in real time, bits want to be duplicated, replicated, copied and bits want to be meta. If you skip all this hardware part and i.e. focus purely on metadata responsible for tracking, we can find it brings totally new value to the general tracking solution (for insurance, for travel, for other market players). There are also many metadata which could support your business as well (either from operation or innovation side). From my personal experience I know that every business is not aware what it could bring to the table. If you want to analyze the flow of the bits your business generates today into metadata of your business in the future – let’s take a look together.

Exponential organizations (ExO) are unicorns of the future. Performance of how you organize can be the key to growth. ExOs are organized in very specified structure. It’s based on Massive Transformative Purpose focused on scalability of a great idea. So to create the scale every ExO needs staff on demand, community, algorithms, assets and engagement. If you want to know what are the other components of ExO let’s join the speech.

In every ExO there is constant flow of data. Quite often ExO operate at marginal cost close to zero, and at a first glance they deliver value for free. The structure of the single ExO organization and as well process and resources will differ from one to another, but they have one thing in common: the monetization process. It’s the most critical and difficult piece of business model. Good monetization process in the right place of the data flow could skyrocket your profit, as well as bad one could close the shop. Do you mind?

Do you remember big chess competition between Gary Kasparov and computer called Deep Blue played in 1997? The case was symptomatic because Deep Blue won and proven that machines are better in logic games then humans. But you might not be aware that almost 10 years later another computer system called AlphaGo beat again human master Lee Sedol in much more abstractive game Go. It was even more surprising as Go has not structured algorithm behind and number of combinations in this game is even bigger than atoms in the universe. From that moment of time humanity recognized that it might be not reasonable to fight against the machines, but rather we should setup a teaming with them. The idea of robots working together with humans become obvious and one of the first step to bring this idea into life is called RPA (Robotic Process Automation). Nowadays there are a lot of computer systems working together with humans on call lines, chatting with customers or even recommends specific scenarios in forensics intelligence or medical treatment, to execute together with humans. If you’d like to know how to team-up with your bot and use it in benefit of your business we should talk.

I’m sure you’re aware there is in digital world thousands of apps which are addressing very different needs starting from renting a car or flat (like Uber or AirB&B), and ending on matching your date mate (like Tinder). Let me assure you that every day the new one is born. But if you analyze business models of this geosocial networking online platforms you will find there are certain business and technological pattern which keeps them spinning like crazy. The biggest challenge is not how to build another one because it is quite easy. The biggest question is how to make them profitable and sustaining? If you want to answer above and to analyze David Sack’s famous napkin sketch to understand what to focus on – just join to my speech.

What does it mean to be a leader of the future? Do you know how in structured way transform our abilities from manager to leader and finally into leader of the future? What are the values of the future? How much control over your team is exactly enough to not kill their initiative? How to create sustaining teamwork? What kind of soft skills do you have to master? Is it rather ethics, emotional intelligence or trust? Do you have to structure your hierarchy or setup a network organization? Should you have to use in sales process advanced techniques of psychological behavioral manipulation only because they are very effective? Or should you implement Artificial Intelligence into your business which clearly take job from your most loyal but obsolete employees? What are the core values for leadership of the future? What about gender disparity, diversity or climate changes? What could bring value to the table is space for open discussion. Leaders of the future are surely among us. Would you like to be one? 

Since early days of industrial revolution business leaders find it out it’s more important than ever to verify how efficient and effective is this new model of working. As the machines takes from humans all simple, repeatable tasks it was obvious it has to be measured. In result we have started to measure almost everything. Starting from units produced per employee/unit or per hour and on the other end – on financial results. Financials are like blood flow of the organism in capitalism. During IT revolution it was even more attended, as quantitative analysis started to solve business problems. Since then we have multiplied numbers of critical business factors to be focused on. In result nowadays we’re drowning in constant stream of data lived in a different cloud services which can measure almost everything. Finally, quantum computing will definitely solve all human problems. But as we can measure everything the good question is if we really know anything about our business. Where is it heading to? What are our assets? The real assets. During this speech I will try to explain why we have to focus only on few indicators of core part of our business and what are meaning of the indicators for digital business of the future. 

Adam Smith has been considered as one of the fathers of capitalism. He has also tried to prove that capitalism is guilty of promoting greed. Since then there are divided opinions. From the other perspective – regarding to Yuval Noah Harari – capitalism was considered as one of the imagined orders existing only in human brains. Analysis of these two contradictive views could easily leads into the dilemma either ethics is more important than greed or not. Nowadays more than ever, during recovery time after Corona crisis, when our safety need has been exposed on risk, humanity has to found good answers for tough problems standing in front of us. In this motivational speech I would like to share different perspectives on ethical profitability. I will show also why delivery vaccination for Coronavirus for the entire world in freemium model could lead to extraordinary benefit of the pharmaceutical company. We will discuss as well why trust beats control in digital world and what the business can take as a lesson learned from ethical social responsibility approach.

Related to famous organizational theorist Rusell Ackoff – there are three kinds of thing that can be done about a problem. They can be resolved, solved and dissolved. You can solve a simple problem like how to travel from A to B. There are only quantitative factors, so you have to measure and optimize the weighted outcome, as in fact exists only one way to solve that challenge. Resolving a problem is far more complex. There are as well quantitative and qualitative factors to be taken into consideration, so there might be more than one possible solution, and there is a question of selecting the best one. Finally, there is a mess called sometimes chaos. This is a kind of a problem where there is no existing logical solution to be applied or there is indefinite number of ways how to solve (chaos theory). In my speech I will present how in actual digital world any X-year strategy plan has to be considered as mess and why it is better to dissolve this in broader perspective.