Welcome everyone. And we will be talking today about um interesting phenomenon when Scrum meets robotics and there will be a lot of no magic here. Um However, I hope it will be and valuable for you. So um to start with, who am I?Well, I'm a robot's lover and uh it's not an accident. Um I have um um technical and educational background in robotics. So my journey started some time ago during my university times. Um I've been working mainly in it industry for several years already. And now I have a great opportunity to come back to, to what I love to, to come back to see the robots working, helping people doing great things. Um And during my career, I learned a lot about Scrum about agility, about switching our mindset into more welcoming change. Um This is why I, I also became a professional Scrum trainer at scrum.org. Um And I had also opportunity to, to teach currently about Scrum and I will talk a bit about robots during my presentation, but let's stop spoiling it. Let's go with the next um slide. So today, um I want to uh convince you that no matter what is your product, even if it's not like a software one, it's not the only application, it's not only um something that um that is artificial if you have different um challenges. For example, you work in marketing, you work in sales, uh you work with a tangible physical product.

Well, the scrum may support you uh to, to on your path, to create this, this valuable product, this valuable service, whatever you do, what is more sometimes agility might be the, the best, the best way, the best path for you. So why it happens? Well, there's a lot of complexity in the world. Um I don't know if you're aware of it, but this is like a short uh short brief description of so called ce framework. I hope I uh I pronounced it correctly, which was created by Dave Snowden and it's used in uh aiding decision making. Oh, thank you very much. So, um do you know the model? I agree. I agree, Simon, it's a brilliant um for those who do not know it. Well, um we have here a few domains, our, our world, let's say our problem uh problem um space is, is divided into different domains. Some of the things we we face are simple. Um So we have, I would even say not good because I think it's quite old picture here. We have best practices that if we follow them, if we are working in production line. Uh we are working in pharmacy. There is a clear and the best algorithm how to create good medicine, how to create great car. Sometimes our work is complicated, like for example, building a bridge or building a house.

So there are some known and knows we will we know that during this process, some of the things will pop up. Uh but we are quite well prepared for them. That the case is like many, many things belong to complex domain. What does it mean? We often do not know what we do not know. And the issue is getting really complicated. There are no best practice. There are no good practice. Uh There are emergent practices which are good to your context. Um So let's imagine that we are put into the dark forest. We do not know the place and we want to go out from this forest. This forest may be a symbol of our complex world. If it's really dark and we do not see a lot. What do we do? Well, just staying and standing in the place, it's a bit risky. Why? Because for example, different people, different creature may appear but they might be good or bad. There might be a problem with the wet weather if you, if little red riding hood, you know, like wolves might be not the best companions when staying at, at the forest. Many, many different things may pop up. You do not know when you do not know how, but you can assume that something will happen.

Also staying in place might be not the best solution for you because basically people around you animals and the weather, everything is changing and um doing chaotic uh moves may end up with you um falling down or smashing your hand head because of the trees. So even if you succeed with going through this forest, this is our complex world. No one is promising that this is the end of your journey. There might be more complexities like for example, lake and now, oh my God, how do I get to this island? Should I swim? But I do not know what kind of animals, what kind of fish is in the lake? Should I use this boat? I don't know if this boat is good enough or not? Oh Sounds like a continuous challenge. A lot of effort. A lot of tough work. So if we choose to act, not to just stay and wait for the others to act for ourselves, maybe we should let the danger come closer. Let's do something well, great. But at this point, the first lesson I want you to remember from my talk. Why don't we think about adventure? Huh. So instead of thinking that this forest, this lake, well, spoiler alert, this island might not appear as your final point. So instead of thinking this path as uh something like a terrible exhausting work, thinking a bit different changing your perception, um helping others change their perception into. Hey, this is the adventure we can go together on that might be helpful.

And I believe it's an important and uh nice part of agility. Now, in description of my talk, I mentioned that in some places people claim, hey Scrum, and that G is only for software. And I would say stop for a while. Of course, if you look for a giant manifesto that I think this is one of the ugliest pages now in the world. This is very old and not very sophisticated. But again, it still exists. And it's in the same way, if you look at it, you will see like working software, agile software development. I agree. But let's forget about this word and I have a proposal today for you. Let's change it into product into service. Maybe different words come to your mind. If we just do those small changes now we are thinking about development of something that can be software can be part of the software, but it can be something totally different. So the next lesson, look at a giant Manifesto because maybe if you forget about software work, there might be some clues for you how to change your mindset. So individuals and interactions work product service, valuable things that you create collaboration with your customer and responding to change.

So Scrum there also the Scrum in the title, Scrum is uh one of the way one of the paths that you can choose on your, on on your journey and adventurous journey towards agility. So to make it short, you um you plan something small based on requirements based on tasks based on things that you want to achieve. You try to deliver it with uh within small, not too big, not too small, rather small team around 10 people or less and making an increment. What is an increment? Well, this is something uh valuable and of good quality that you potentially can give to your stakeholders, to your client, to whoever is interested in. And what do you do? You do in this process, you keep uh making short iterations up to one month in some of the cases, it might be even one day, but usually it's a few days a week or two. And you gradually show your stakeholders, your customers something of value and continuously learn. You learn on daily basis and plan your actions during daily Scrum, which is basically a very short meeting of the Scrum team. Uh You, you inspect your increment and assess, hey, is it what we should do? What our customer thinks, what numbers say about it?

We will talk about numbers and metrics soon and what we should and could do to make our process better. And what happened next repeat? Does it sound um understandable for you? Great. Thank you. So, the next um lesson, the next idea you have small iterations focused on creating something of value, which means that you have to be uh convinced enough that it in its shape, it can be delivered, it can be used even if it's really small feature or something small, really, really tiny, it can be used and it potentially brings value.

So in every such iteration you, you are looking for two opportunities. And this is this is something I want to emphasize, opportunity for experimentation and opportunity for learning. Why is it so important? Well, due to um due to different factors, one of the obvious I hope for you now is that hey, complexity, we are in this forest. So this is just a metaphor. But in fact, sometimes we we even if we have plenty of ideas, it's it's like going through this dark forest, we do not know what to do. So empiricism says that, you know, uh you know the results of the past actions when you have data, when you see them, but what will bring the future? You will never know reality check. Ah Sorry. So um I believe that experimental and data driven approach is something that many of you can benefit from. What does it mean? Well, it's quite I would say scientific and mathematical approach uh which can be taken into any problem that you are facing the cases. As I mentioned previously, we are changing the mindset and how we are going to make our decisions, what factors we are going to take into account. So we can be chaotic and doing random moves in this forest.

But we can make some experiments gather data and based on them, choose what to do. So in, in many, many, in many cases, it basically means that you create a hypothesis. So um this is this is the sentence, this is the statement about well, if I change something in my process, for example, if I change the gripper in the robot, uh the robot will pick uh pick items better. Well, sounds like an idea. But hey, this is, this is like just like a hypothesis, you have to verify it. So you create a frame for your experiment, you have already a hypothesis, you decide how experiment will be conducted most probably you will be conducted it several times to gather data, use the power of math and statistics to look at the data. Hey, definitely the robot is moving better. It's it's picking the item better. So it's worth investing in this solution. And also what is important here, try to make your experiments cheap. So look for prototypes, look for ideas how to um mimic some of the things. Maybe you do not sorry, maybe you do not need to buy fi final sophisticated equipment, simple prototype uh done by your team internally might be just enough. And another another important factor is data driven.

It does not mean that you gather any kind of data because it's quite unreasonable to make your decision in the forest based on the number of foxes, it might be not enough and this factor maybe is less important. What might be more important is to, to gather. Um What is, what is uh the terrain, how it changes? Um If it's safe to, to go to to forward or maybe you should go back. So measure right data and also with right cadence. What is also the hidden power of experimental approach and data driven approach? There is no failure unless you fail to learn. So if your hypothesis became um false, great, you learn that this approach is not for you. Now choose a different approach, choose a different experiment and go forward how all those things are possible. I mean the agility, the scrum thing, uh those small iteration focusing on making small valuable things. It's a matter of culture, it's a matter of, of culture, of courage, focus, commitment, respect and openness. You can take this, those are five scrum values that support you, but you can based on them, create your own values, create your own extension. Remembering that what Scrum values give you just look at the example, better be wrong than I do so. Come on. Make an experiment, try to learn just this is like a clear signal for us to to go to go with it and embrace the challenge and embrace the adventure. This optimistic pos positive attitude towards difficult things that will happen.

And by the way, those are values of the company I currently work in. So what happens when, when all those things put together were great? Well, no magic, no magic happens. Robots starts to read books. OK. This is just a joke. In fact, the robots that we currently work with um are trying to do some reputable boring tasks in warehouses so that people can focus more on developing their skills in more sophisticated areas, taking more ambitious tasks. If you want to watch the video and ask more questions, there will be also also an occasion for that. So to sum up my today's talk, there is such a law which is called third clerk's law that any sufficiently advanced technology is indistinguishable from magic. I hope that now you in no magic trust. So there's no magic in Scrum. Scrum supports you on your empirical process control. So based on empiricism, based on what we've learned from the past, we make decision. There's also in thinking in Scrum. So we are looking to reduce waste. This is also another tip for you what you can change to reduce waste of time of um of resources. And also there is no magic in robotics. Although the this is their nice and sophisticated clerk's law, it's a mixture, mixture of knowledge, science, artificial intelligence culture, wonderful and committed. People just look at them how they are smiling, they work together and they work, they work with robots. How cool is that?

So we are no magic. This is the actual name of the company I work with. You can find us on Expo today. You can also find us uh at our page and our linkedin profile. And if you have any questions related to culture Scrum or anything I mentioned today, feel free to connect with me on linkedin. Thank you.