The role of organisations has been under heavy discussion over the last years. Recently more and more organisations tend to choose a new approach regarding their management control; self-management. This blog post looks at how one local Finnish service company has developed its way of finding a balance between employees’ autonomy and accountability.
Hello networked organisation
Organisations are designed to be stable and predictable environments. They have been very good at processing information, optimising processes and producing outputs. But over time, things change: customers want different services, new competitors and business models arrive, and the organisation might scale rapidly. This greater overall complexity forces organisations to fundamentally rethink their whole organisation model.
In the networked organisation model, the organisation operates as a network of small, self-directed pods that are connected by a common purpose and supported by a platform. A platform is a structure that increases the effectiveness of a community. The networked organisation cannot fit on a traditional organisation chart and is optimised by information speed and people pods.
The networked organisation enables a whole a level of flexibility and adaptiveness, that would never be possible in a divisional organisation. It can respond dynamically to change and can learn and adapt to the environment continuously. This will help the organisation to faster identify and capitalise on opportunities.
Networked organisations are also very resilient. It distributes the workload across a wider area by allowing each pod to focus on goals rather than on steps or stages. If one connection breaks, pods can still continue to work.
Networked organisation in action
Gofore plc. has around 600 employees and provides consultancy services in the fields of software development, design, management consulting and cloud. Gofore wanted to keep its organisation as simple as possible even though the growth has been rapid. The next chapters explain briefly how the networked organisation model functions at Gofore.
Gofore’s business model is consulting, so the company is eager to find new customers and deals. In this typical example, a sales person discovers an interesting invitation for tender. He contacts another sales person to discuss the details. After discussion they decide to create a bid.

The invitation to tender requires proof of concept and a team of three developers. Sales person A discusses with the sales person B and uses Gofore’s internal services to find a suitable UX-designer and a software developer for the project. Sales person B leaves the pod.

The UX-designer and software developer A start designing proof of concept. Software developer A invites two more developers B and C who would be right for the project. Sales person A also invites a legal advisor to help prepare the bid.

Software developers A, B and C fill needed resumes and help the UX-designer to finish proof of concept. The legal advisor advises software developer B on details of her resume. Sales person A and the legal advisor finalise the bid. Sales person A sends the bid to the client. Finally, the pod disappears, and people return to other pods.

A notable thing in this example is that people might not have met before. There were also no managers or a standard process of how to proceed. The pod shares the common goal to “finish the bid”. In other words, the whole pod is accountable for doing all the needed actions in order to reach the goal.
Most of the communication happens in one Slack channel and the pod might be active for only a couple of weeks. The pod goal can be everything from a small marketing event to a large strategic acquisition and it can contain employees, partners and customers. Size and activeness of the pod also varies over time. Sometimes the pod has one facilitator and sometimes multiple members are the driving forces. Occasionally, a pod fails to reach its target. Then people from the pod sometimes gather to reflect on what went wrong.
Theoretically, people can jump into different pods and take different roles at any time. On the practical level, people have varying expertise and responsibilities that restrict mobility. People who have more sales or recruitment responsibilities for example tend be more active than a single customer project focusing expert. There are also more static structures at Gofore, such as the executive management team and human resources function. Despite this, most “goforeans” are members of multiple pods simultaneously.
Side effects
Every model has side effects and the networked system is no exception. Gofore has numerous pods active every day. This might cause a situation where two pods are working on the same topic without knowing the others’ plans. Thus, a pod might be operating on an activity that has previously been done, or is already planned to be done. In my experience, this sub-optimisation risk hasn’t been a major challenge at Gofore so far.
If an employee belongs to too many pods at the same time, context switching might generate overhead and frustration. The other challenge is that people become bottlenecks – people struggle to say no for new pods and activities, even when their schedules are fully booked. For these reasons, employees need to know how a self-organising organisation works. Gofore has created internal “People Person” and “Coach” services that support employees in their self-management and personal development skills.
Some people might also miss long-term teamwork and traditional supervisors, where decision making is slower and more predictable. Gofore’s customer projects are typically long lasting which helps to create a more stable environment. Some pods such as “Guilds” and “Capabilities“ are also more durable by their nature at Gofore.
Control your own fate
This blog post offers a glimpse into Gofore’s operational level. It is important to understand that when the organisation is adaptive and learning, structures and culture also evolves continuously. Hopefully organisations understand this paradigm change and let go of the legacy of Taylorism.

References
The Connected Company by Dave Gray
https://hbr.org/2015/06/what-makes-an-organization-networked
https://blogs.oracle.com/content/who-is-dave-gray-and-what-is-a-connected-company
http://blog.idonethis.com/cells-pods-squads-structure/
Graphic Design
Miia Ylinen

Juhana Huotarinen

Juhana Huotarinen is a lead consultant of software development at Gofore. Juhana’s background is in software engineering and lately, he has taken part in some of the biggest digitalisation endeavours in Finland. His blogs focus on current topics, involving agile transformation, software megatrends, and work culture. Juhana follows the ‘every business is a software business’ motto.

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A business model is known as a plan of how to execute an organization’s strategy. It can also be a summary of an organization’s business logic. Understanding the target domain is often required in order to model a business, for example, to gain a common understanding where the participants are a cross-functional team. To model these plans or summaries there are many tools, templates or frameworks available. In many cases, they use graphics to create a more understandable way to ensure that different perspectives are considered.
One of these templates which is easy to access is called the Business Model Canvas (BMC). An objective of the BMC is to create a commonly known way to clearly picture the ontology around the target domain. The BMC offers you pre-defined building blocks to divide your business domain or a single product/service – it works in a very scalable way because it fits both small and larger target domains. The BMC consists of nine building blocks which contain points of view from a value proposition, customer thinking, business infrastructure and economics.

icon The Value proposition building block is in the middle of the canvas. The value proposition defines the value or benefits customers get from using the organization’s products or services. For example, the service’s value proposition is to provide a faster and reliable connection between users.
iconThe Customer segments building block defines the customer groups for whom value will be produced. Customer segments can be sorted with different criteria, for example, according to age, county or industry.
icon Customer relationships answers questions such as: what kind of relationships the organization has with different customer segments and how are they maintained. For example, how to create relationships with new customers, how to maintain existing customer-relationship or how to develop relationships with potential customers in the future.
icon  The Channels building block represents all the defined ways to reach customers or how the value propositions are distributed for customers. For example, an item bought from an online shop will be delivered via the post office, but a local store can sell the item locally.
icon  The Key resources building block defines all the resources required to produce and provide a value proposition. Resources can be divided for example according to the material (human, IT-infrastructure) and immaterial (patents, brand) resources.
icon  The Key activities building block answers the question: what are the main tasks or functions to deliver the value proposition. For example, activities can be divided according to manufacturing lines, services, or problems to be solved.
icon The Key partners building block defines the most important stakeholders to complete all the necessary key activities.
icon  The Revenue streams building block defines the price for the value proposition. Different types of prices can be defined according to the customer segment.
icon The Cost structure defines all the costs of the activities to produce and achieve the value proposition. For example, these can be costs of marketing, distributing and manufacturing. Cost structures can be sorted with fixed and variable costs.
One developed version of the BMC is called Service Logic Business Model Canvas, that especially points out customer thinking in these building blocks. For example, the value proposition considers what are the problems that customers are about to solve with a product or a service. Or what are the specific features that specific customer segments are looking for from the value proposition.

Towards a common understanding

Designing with graphical tools helps to understand the target domain from a different starting point. For instance, project members from different sectors might see the result in a very different way. The BMC-template offers a fast and effective way to begin brainstorming and especially to collect and compare ideas. All you need is a printed BMC-template and lots of Post-it notes. Collecting something concrete on a wall makes it possible to begin discussions with each other and promote the business model to the next level.
Finally, a couple of tips for effective teamwork with the BMC:

  • By using different sizes and different colours of post-it notes you can highlight or easily split ideas into groups
  • You may use multiple notes to write down words or paint pictures: tell a story while placing them onto the canvas (good stories are remembered for a long time)
  • Be open-minded while having conversations about ideas – it’s dangerous to fall in love with your own ideas.
  • It might be necessary to go through multiple rounds before getting a satisfying solution. It’s important to evaluate iteratively which ideas work better and which ones do not.
  • It might be a good idea to split a larger group of participants into smaller groups and compare their outputs – finally collect the best ideas together.

post-its

Downloadable BMC-template:
http://www.businessmodelgeneration.com/downloads/business_model_canvas_poster.pdf
Example of using Service Logic Business Model Canvas:
https://pdfs.semanticscholar.org/8be1/75561b64ad8172cc7d5a0859da9c9460bda8.pdf
Sources:
Business Model Generation: A Handbook For Visionaries, Game Changers, And Challengers (2010) http://businessmodelgeneration.com/book?_ga=1.248258951.1869965398.1467892617
Osterwalder, Alexander et al. “The business model ontology: A proposition in a design science approach.” (2004). http://www.hec.unil.ch/aosterwa/PhD/Osterwalder_PhD_BM_Ontology.pdf

Antti Luoma

Antti Luoma works as a service architect at Gofore. He has a Master's degree in Philosophy from the University of Eastern Finland, studying computer science. Antti is an expert in the comprehensive use of architectural descriptions in business model design and project management.

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In the business of digital services, the customer is the boss, and the value the customer sees, feels, and perceives is the only metric that matters. But what does it take for a traditional product business to turn into a customer value-driven service provider?
Service Business
Bad services come into the bargain with products. Great services replace the need to buy them – or make them obsolete altogether.
 

When products no longer satisfy

Traditional B2B product companies are struggling to stay relevant. Research & Development pushes out new technology faster than ever, and every step of the manufacturing process to logistics has been fine-tuned to perfection to offer the best quality-price ratio to customers.
The products have never been better, yet the sales forecasts are looking grim: traditional businesses are losing more deals every year while those businesses that manage to listen and react on their customers’ needs the quickest, flourish. What’s going on?
traditional product business
Traditional product business relies on technical excellence. The customers are passive consumers of the product.

The day the customers changed their minds

Meet Maria, the plant manager at Industry Inc., a mid-sized manufacturing company.
On an average Monday, Maria continues working on the newest tender for the plant. With the help of her team, she’s already narrowed the options down to two. It’s time to make the final call.
Option 1 is a trusted, familiar dealer, offering an excellent product. History has shown that it’s a good choice, and the price is the same as always.
In Option 2, the provider is offering a partnership focusing on improving the plant’s process performance. The product itself is one component of the service and is included in the monthly invoice. With the service, the provider promises to remove a few of the manager’s, engineers’ and the operators’ manual tasks. “These sure are tedious and time-consuming tasks,” she notes. “I wouldn’t lose anything important and could focus my efforts into more strategic questions.” “Actually, with these key figures, we’d be able to plan our budgets six months in advance. That’d make our jobs a lot easier.”
Option 2 sounds like a better choice, but also more expensive. But after adding up the benefits, Maria comes to the conclusion that the true potential is in the long game.
“Maybe we should give it a try. If everything fails, we can always go back to the good old Option 1,” she decides.
And they never go back to Option 1.

Hard numbers drive the discussion, but perceived value tips the scales

In B2B, direct cost is always a major criterion in decision-making, but certainly not the only one. The technical excellence of the products is already taken for granted by the customers – in the end, what really makes the difference is the total value the customer feels like they are getting.
How much do you value removing the mundane tasks you dislike? What about being able to consult experts in decision-making when needed? Sharing the risks with someone? Or making you feel like a better professional at your job?
We all choose the best option for ourselves, and for the context in which we live. People value things differently, and these values are rarely visible to the naked eye.

Knowing the people behind the billing address

No business can afford to create something their customers don’t accept. But who exactly do we mean when we say ‘the customers’?
In the digital service business, customers are not passive entities that consume what the business offers – they are people with different roles, needs, and motivations of their own.
Find out who your customers are, and what they need and value. Focus your efforts on doing the most important bits for them. (it’s worth mentioning that customer needs and wants are two different things – customer-centricity doesn’t mean you have to say ‘yes’ to every customer wish!)
When true customer insight starts driving decision-making, customers become the new objective setters for your business. Those objectives start driving the technical excellence of your business. The whole current changes direction.
Digital service business
The digital service business relies on customer insight. Answering to the needs of the customers drives the objectives of the whole organization.

Getting out of the black box

Creating something new never comes without risk, but you can avoid flying blind.
You need to learn how to collaborate with your customers’ key people. You need to be able to test your assumptions and ideas with them before they’re built.
It takes courage to challenge your own assumptions and approach customers with hypothetical scenarios and prototypes. Nobody likes having their ideas shot down, but it’s always better to fail with a two-month-old concept than with a launched service that’s been developed over years.
“But can we do that? What will our customers think?”
You’ll be surprised how eagerly people reserve an hour of their time to help create something that will, in the end, make their own lives easier. They’ll appreciate the opportunity to get their voices heard and make a difference. If you’re well prepared and have the right professionals to do it, people will want to pitch in. Or, at the very least they’ll appreciate that they were asked.
With the resulting, rich insight, you’ll notice that it’s much easier to make decisions on where to head next, what to change, and what to keep.
 

Playing the long game

Services are never ready. The service provider’s responsibility does not end when the first version is out and the first deal is won. That’s where the real acid test begins.
With services, the strength of the customer relationship is put to a test every single day. Even the best customer insight stales with time: customer needs and priorities change, and the service needs to be able to evolve with them.
Meeting and exceeding customer expectations demands resources, commitment, and, most importantly, continuous development. But the work pays off with strong and honest relationships that last. Such relationships create long-term value for both parties.

Fortune favours those who are driven by customer value

In the game of customer experience, fortune favours those who truly know and collaborate with the people behind the customer accounts, anticipate and react quickly to changes in the environment, and keep delivering their promises day after day.
Find out who your customers are and figure out what they find meaningful. Be prepared to challenge your own assumptions. Find the courage to test concepts with your customers’ key roles before they are built.
It takes courage, a change of mindset, and realignment in the way the business operates internally. But at the turn of the tide, that’s the price of staying afloat.
 

Janne Palovuori

Janne designs services that bring genuine value to people and business. As a service designer, he observes services through a holistic focusing lens. Heavily on understanding the 'right why' to design for, Janne works for people, with people, meaning the bedrock of his line of work is qualitative research, facilitation and co-creative methods. Janne's superpower is creating visualizations that conceptualize ideas and make information comprehensible, engaging and worthwhile to target audiences, across different project phases.

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Open source is everywhere in today’s software business. Open source is found in programming languages, operating systems, frameworks, databases, standards and even machine learning models. However, structures behind open source projects have changed.
Open source is an asset

Rise of free sharing

Open source software is software that anyone can inspect, modify and enhance. The concept of free sharing of technological information existed long before computers. However, the concrete open source movement took the place in the ’80s, when the GNU project started and the Free Software Foundation was founded.
At the beginning of the 21st century, open source technologies gained popularity in enterprise software development. Open source-based Java and JavaScript became mainstream programming languages and open source databases such as MySQL and PostgreSQL also achieved success. Frameworks and libraries such as Spring, Ruby on Rails and JQuery likewise mirrored that feat by eating away at more complicated commercial rivals. The most widely used open source project Linux even become a symbol of universal freedom and independence.
Almost all of the early years open source components were invented by individuals, communities or small or non-profit corporations. In that time big players such as IBM, Oracle and Microsoft were focusing on their own proprietary ecosystems. Early in the millennium, former Microsoft’s CEO Steve Ballmer even famously described the Linux open-source operating system as ‘communism’ and ‘a cancer’.

Clear benefits

Traditionally in the software business, the strategy has been to build and license technologies and sell them. The vendor lock-in approach where a customer is dependent on applications and the source code has been a typical asset for tech companies. However, the technology landscape was ready for contemporary players.
The next generation of tech giants such as Google, Facebook, Amazon and Netflix are closely linked to open-source projects and communities. For tech giants, open-source is a part of their technology strategy, not enemy territory. Here are a few reasons why open source is a smart move in the long term.
Implementing and maintaining numerous technologies is extremely costly. Lowering development costs by building open source components for free could have a huge impact on the company’s profitability. There is, for example, an estimate that Facebook’s Open Compute project has saved them $2 billion in data centre costs.
Hiring a good developer is never an easy task. Open source helps to mitigate this global challenge. First, it promotes company branding. A good company culture is a mechanism for attracting the right people and retaining its workers. Working closely with open source communities gives the impression of a transparent, generous and people-friendly company.
Secondly, developing relationships with an open source community results in a pipeline of developers who are familiar with the open source technology and are excited to help work on it. The community engages experts around the world who are interested in solving similar problems and developing exciting technologies. The more well-known the open source technology is, the more candidates are available for the company.
The best way to make sure the kitchen is clean is to keep it open. The same analogy works with software development. According to many researchers, open source code tends to be of better quality (i.e. fewer defects) than propriety code. A bigger number of contributing developers, peer pressure and larger variety are just a few reasons why. In the best case scenario, the open source component becomes an industry standard.

Side effects

Old tech giants changed their strategy as well. Oracle acquired Sun Microsystems which was the company behind Java. IBM followed the approach in 2018 when it took over the largest open source company Red Hat.
The biggest transformation happened to Microsoft. The company decided to open source the .NET platform and released Visual Studio IDE for free. In addition to this, Microsoft plans to ship a full Linux kernel directly in Windows. Nowadays Microsoft is one of the top corporate contributors to open source projects.
However, tech giants’ active role in open source doesn’t come without a price. A painful example is the popular front-end framework AngularJS, invented by Google. Google decided to re-write the new version of AngularJS and stop support of the older version. This upset a large number of organisations and developers because they needed to completely refactor their applications.

Love of power

The tech giants have realised that company value does not come from technologies, but instead from culture and capabilities. Open source projects fit perfectly with this mindset. In addition to this, open source adds a new tool for the tech giant’s engagement strategy.
The result is that a few tech giants contribute to the largest number of open source projects. The dream era, where open source projects were the way to express, learn and have fun, is over. Open source has turned into a business and its rules are defined by some whose intentions are ambiguous.

Examples of open source projects contributed to by tech giants

Airbnb – JavaScript style guides, Airflow
Amazon –Deep Learning model library DSSTNEC, Amazon Ion Java
Facebook – React, React Native, GraphQL, Open Compute Project, PyTorch
Google – Android, Angular, Kubernetes, Tensorflow, Go
IBM (Red Hat) – Fedora, CentOS, Apache Spark, Ansible
Microsoft – .Net, Visual studio Code, TypeScript, RxJS
Netflix – Chaos Monkey, Hystrix
Oracle – MySQL, JDK
Twitter – Twitter bootstrap, Aurora, Storm
 

Graphic design

Miia Ylinen

References

https://en.wikipedia.org/wiki/History_of_free_and_open-source_software
https://www.forbes.com/sites/paulnoelguely/2018/09/03/open-source-software-from-the-periphery-of-tech-to-the-mainstream-of-finance
https://opensource.com/life/15/12/why-open-source
https://timreview.ca/article/410
https://code.fb.com/data-center-engineering/open-compute-project-u-s-summit-2015-facebook-news-recap/
https://www.geekwire.com/2014/net-visual-studio-microsoft-open-source-cross-platform/
https://www.theverge.com/2019/5/6/18534687/microsoft-windows-10-linux-kernel-feature
https://www.techrepublic.com/article/who-contributes-most-to-open-source-the-answers-will-definitely-surprise-you/
https://www.zdnet.com/article/coverity-finds-open-source-software-quality-better-than-proprietary-code/
https://blog.usejournal.com/a-hypothesis-on-how-react-js-became-so-popular-dc5953c67cf6

Juhana Huotarinen

Juhana Huotarinen is a lead consultant of software development at Gofore. Juhana’s background is in software engineering and lately, he has taken part in some of the biggest digitalisation endeavours in Finland. His blogs focus on current topics, involving agile transformation, software megatrends, and work culture. Juhana follows the ‘every business is a software business’ motto.

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Recently, for about a year and a half, I was working as a developer on a bleeding edge, business changing, disruptive solutions project. I can not say much about the business or the customer itself, but I thought I would share some of my experiences on what and how we did things.

Our team consisted of a Scrum Master, a UI/UX designer and full-stack developers, but the whole project had multiple teams working across the globe towards common goals using a Scaled Agile Framework (SAFe). Our team’s primary focus was to implement the web UI and the higher layers of the backend stack. We also contributed to the overall design and helped with coordination between all the product owners and different teams.

One of the best things in the project was to learn and use a huge amount of different bleeding-edge open source technologies.

Frontend

The key technologies for frontend development were React and Redux, in addition to the obvious HTML5, CSS3 and JavaScript ES6. With Redux, we used redux-saga for asynchronous side-effects and also some other supporting libraries such as redux-actions and reselect. CSS was written as part of the React components using styled-components. Building and bundling of the code was done using Webpack. We also had a great experience with Storybook as a means of supporting rapid development and easy documentation of UI components.

While microservices on the backend are becoming very common, this project also used micro-frontends. This approach is rarer, but the benefits are quite similar: Different teams are able to work on different parts of the frontend independently since they are loosely coupled. New micro-frontends can also be written in different languages and using different technologies. This way switching to anew technology does not require rewriting all the existing functionality. As a technology of choice for combining the micro-frontends, we started with Single-SPA, but later switched to an iframe based approach. Using iframes made development and testing easier and improved our capabilities for continuous deployment.

This second solution turned out to work quite nicely. The only big challenge was related to showing full-screen components, such as modal dialogs. The iframe of a micro-frontend can only render content within itself. So, when it needed to open a modal dialog, it had to send a cross-window message to the top-level window, which then was able to do the actual rendering correctly on top of everything.

For frontend unit tests, we used Jest, Enzyme and Storybook snapshots, while end-to-end testing was done with TestCafe. Once again, it was seen that end-to-end tests are tricky to write – and quite a burden to maintain. Thus, choosing their scope carefully to get the best cost-value ratio is important, no matter what the tool that is used. Nevertheless, we were quite happy with TestCafe compared to available alternatives.

Backend

The backend of the system as a whole was very complex. The dozens of microservices in the lower layers were mostly done with reactive Java and they utilized, for example, event sourcing architecture. On top of those, our team built around 10 microservices with Node.js. The communication between services was mostly based on RESTful APIs, which our services implemented with either Express or Koa. In many cases, also Apache Kafka was used to pass Avro-serialized messages between services in a more asynchronous and robust manner. To provide real-time updates to the UI, we of course also used websocket connections. We learned that in some cases those Kafka messaging based approaches may work very well. Still, there is definitely also a pitfall of over-engineering and over-complexity to be avoided.

In the persistence layer we started with CouchDB as a document database, but later on, preferred using PostgreSQL relational database in most of our cases. With the latter one, we used Knex for database queries and versioned migrations, and Objection for Object-Relational Mapping. For our use cases, we did not really need any of the benefits of a document database, especially since nowadays PostgreSQL also supports json data columns to provide flexibility to the standard relational data model when needed. On the other hand, the benefits of a relational database such as better support for transactions and data migrations were important for us.

Some essential parts of the backend infrastructure were also Kong as the API gateway and Keycloak as the authorization server. Implementing complex authorization flows with OAuth 2.0, OpenID Connect and User Managed Access (UMA 2.0) was one of our major tasks in the project. Another important architectural piece, which took most of our time in the latter stages of the project, was implementing support for Open Service Broker specification.

In the backend, we used Mocha framework for unit testing but usually preferred to write the assertions with Chai. Mocking the other components and API responses were covered with Sinon and Nock. Overall, our backend stack was a success and, at least for me, a pleasure to work with.

DevOps

All the services in the project were containerized with Docker and for local development we used Docker-Compose. In production, the containers were running in OpenStack and orchestrated with Mesos and Marathon. Later on, we also started a journey in moving towards Kubernetes instead. For continuous integration and delivery, we used Gitlab CI/CD pipelines. I also liked our mandatory code reviews of every merge request. In addition to assuring the code quality, it was a very nice way to share knowledge and learn from others.

In a large scale project such as this, carefully implemented monitoring and alerting systems are, of course, essential. Different metrics were gathered to Prometheus from all the services and exposed through Grafana, while all the logs were made available in Kibana. We also used Jaeger as an implementation to OpenTracing API, which allowed us to easily trace how requests flowed between different services and what was the origin of any errors.

The main challenges were related to the fact that running such a huge project completely on a local workstation during development is impossible. We investigated a hybrid solution, where some of the services would run locally and some on a development cloud, but found no easy solution there. As the project and the number of micro-services continued to grow, we were getting close to a point where a better solution would have needed to be discovered. For the time being, we worked around the problem by just mocking some of the heavier low-level services and making sure our workstations had plenty of memory.

In summary, this was a fun and challenging project to work with. I’m sure everyone learned tons of new skills and gained a lot of confidence through this project. I want to send my biggest thanks to everyone involved!

 

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Joosa Kurvinen

Joosa is an experienced fullstack software developer with a very broad skill set. He is always eager to learn and try out new things, regardless of whether that is with backend, frontend, devops or architecture. He has an agile mindset and always strives after clean and testable code. Joosa graduated from the University of Helsinki and wrote his master's thesis on AI and optimization algorithms.

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A book called The Fourth Industrial Revolution by Dr Schwab describes how the fourth revolution is fundamentally different from the previous three. The fourth revolution combines the physical, digital and biological worlds. These new technologies will impact all disciplines, economies and industries.

The Fourth Industrial Revolution demands that CEOs take responsibility for the massive transformation of their businesses and for the extraordinary impact that this transformation will have on wider society.
– Pierre Nanterme, Accenture CEO

Already in 2016 The World Economic Forum at Davos stated that almost half of the jobs in the USA were at risk, because of Industry 4.0. However, Industry 4.0 also has great potential to drastically improve the efficiency of business and organizations and help regenerate the natural environment through better asset management, potentially even undoing all the damage previous industrial revolutions have caused. According to the report issued by Deloitte, over the next decade, the U.S. could be short of 12 million skilled workers. As a result of this, manufacturers are looking for ways to increase manufacturing efficiencies by doing more with less.

What is Industry 4.0


PICTURE 1: Industrial Revolutions
The first industrial revolution brought mechanization through water and steam power. The second revolution was mass production and assembly lines using electricity. The third was the adoption of computers and automation. Now, the Fourth Industrial Revolution is upon us. It is a fusion of fast technological breakthroughs in the physical, digital, and biological spheres. Technology breakthroughs in fields such as 5G, the Internet of Things (IoT), Big Data, Analytics, Artificial Intelligence and Robotics are significant on their own, but when combined we are talking about the enormous benefits of Industry 4.0.

  • IoT. The Internet-of-Things (IoT) are where devices such as industrial sensors connect to the internet and to each other. IoT requires connectivity. 5G helps the evolution of IoT by improving the interaction between different platforms as well as enabling more devices to become connected.
  • 5G. 5G will recode the whole concept of mobile connectivity. 5G brings a new-market disruption, which opens a completely new blue ocean of opportunities. 5G pushes industries to seek entirely new use cases for connectivity. 5G offers a completely different performance. 5G pushes a shift from the hardware business to the software business. 5G will change how people use and communicate with technology. It will change how different technologies communicate with each other. All this will take place faster and more reliably than ever before. Mobile internet will be faster than ever. High bandwidth and low latency will transform whole industries through new ways of connecting production processes and products.
  • Big Data. There is more data available than ever. As the amount of data increases, new innovations and technologies to utilize the promise of this data are constantly created. Big Data can be filtered and turned into Smart Data. Fast Data aims for real-time data processing, where data is processed when it arrives. In the field of Big Data technologies like Artificial Intelligence, Machine Learning and Deep Learning can be used to analyze the data.
  • Software ecosystems. With 5G, IoT, Big Data and Artificial Intelligence, the differentiating factor will be software capabilities. New capabilities are all about thinking outside the box. Ingenuity regarding what can be done with technologies, and how they can be applied to solve tomorrow’s challenges. This is a crucial mindset across every technology-related industry.

Industry 4.0
PICTURE 2: Industry 4.0 is a fusion of fast technological breakthroughs in the physical, digital, and biological spheres. It is not a single innovation, it is all the innovations combined.
The key to achieving the potential of Industry 4.0 is a collaboration between stakeholders from (traditional) industries and technology partners. This requires a new agile mindset and cultural shift. In short, Industry 4.0 will bring a new productivity shift, while smart machines keep getting smarter as they get more data, and factories will become more efficient, productive and less wasteful.

We Are the First Generation that Can End Poverty, the Last that Can End Climate Change.
– UN Secretary-General Ban Ki-moon

Forbes vs Uros

Markus Meukel from McKinsey & Company dropped big numbers regarding the promise of IoT at the annual Nordic IoT 2019 keynote speech. According to Mr Meukel “IoT is the most impactful technology revolution” creating an estimated 10 trillion annual turnover globally by 2025. Sounds insane, doesn’t it. However, just this week a Finnish IoT company Uros presented its growth figures.
2015: $2,7M
2016: $42,7M
2017: $483M
2018: $1309M
And Uros CEO Jerry Raatikainen stated “What we are seeing now is the IoT market growing; the sector will be huge. We will leap into the year 2022 with the same rate of growth”. Mr Raatikainen is saying that a small technology company from Northern Finland will hit 50 Billion turnover in a few years. This underlines the effect the Industry 4.0 phenomenon offers for large companies. Industry 4.0 will change the game big time.

Industry 4.0 Examples

  • Logistics: Optimize the routes of individual parcels and vessels (car, truck, ship) for efficiency and productivity. Automate everything. For example, Kalmar aims to optimize terminal processes. Zalando to use robots to pick packages. DHL is investing big time in Industry 4.0.
  • Manufacturing: Smart manufacturing is a major application of the Internet of Things (IoT). For example, Fastems provides numerous references, where they have automated manufacturing lines around the world. Another interesting case example is the Bosch factory, where implementing radio-frequency identification-based tool management, embedding sensors to machines and analyzing real-time machine data and inventory, the factory renovated its manufacturing infrastructure and is able to understand and eliminate output losses and predict machine interruptions before they occur. Lean manufacturing principles, which form the backbone of smart factories, are being increasingly integrated into everyday operations. Adoption of lean manufacturing and the transition to data-led practices can increase the competitive edge of manufacturing. To improve manufacturing efficiency, one must backtrack from the customer. In today’s rapid cycle of customer demand, the linear design-manufacture-market-sell process does not increase competitive advantage, because demand forecasting is never as effective as ongoing collaboration. When customers are participating continuously in product design and make updates to their orders, they achieve a more productive relationship.
  • Process Industry: The Industrial Internet offering by Valmet combines process technologies, automation and services, which will turn the benefits of the Industrial Internet into reality. Metso is focusing on providing sustainable solutions for the processing and flow of natural resources by means of Industry 4.0 and Digitalization.
  • Food ProductionAutonomous farming is taking agriculture to the next level. Agriculture 4.0 uses artificial intelligence to analyze the data from satellite imagery, weather forecasts, flying drones and IoT sensors on the field for crop modelling and for precision agriculture. For example, John Deere is pushing the boundaries on what can be achieved in the area of autonomous farming machinery.
  • MiningSandvik AutoMine already provides full fleet automation with automatic mission and traffic control capability. Sandvik OptiMine analytics system creates a transparent model of the mining operations improving efficiency and safety.
  • Business DisruptionRolls-Royce has pioneered a pay-by-use approach in its jet-engine business; other manufacturers have followed. Rolls-Royce has turned from an RnD and manufacturing company to a data analytics company. Some say, that Rolls-Royce started the whole subscription economy of today’s Netflix and Spotify culture.
  • IPR Business: Today, many manufacturing companies have deep expertise in their products and processes but lack the expertise to generate value from their data. SAP offers consulting services that build on its software. Qualcomm makes more than half of its profits from intellectual-property royalties. Manufacturers might offer consulting services or other businesses that monetize the value of their expertise.

We Are Creating a Better Future

Adopting Industry 4.0 technologies will help countries and businesses achieve sustainable growth. Industry 4.0 capabilities will enable faster design, novel products, reduced risks, optimized processes and the elimination of waste. New technologies will contribute to companies’ economic success. But they will also fulfil a social purpose, by contributing towards improving people’s lives. New technologies like artificial intelligence and edge computing can make people’s work less error-prone and create more room for creative tasks. These are technologies that will enable us to stay successful.

Jari Hietaniemi

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Fast Data

fast data
The promise of Big Data has finally gained momentum. There is more data available than ever. While the amount of data increases, new innovations and technologies to utilise the data are constantly created. Big Data describes increasing amounts of data, which is constantly collected. Big Data can be filtered and turned into Smart Data. Smart Data can be described as cleansed, filtered, and prepared for the context form of Big Data. Work is about batches and off-line processing, where you capture-store-process data in overnight batch jobs. Fast Data reduces the time between capture and process. Fast Data aims for real-time data processing, where data is processed as soon as it arrives.
Data technologies are evolving. Both the way data is processed and the timeline when data is analyzed are changing. Data is collected from countless systems and analyzed in real-time. Data includes transaction data and business data, IoT metrics, operational information, and application logs.
The Fast Data revolution has been made possible by two underlying revolutions of Big Data and Smart Data. Big Data systems like Hadoop made it possible to store huge constant volumes of unstructured data on commodity hardware. For example, the Cassandra storage technology began from the need of Facebook to store high volumes of data. Currently, on Facebook, 2000 photos per second are uploaded. However, the challenge that Facebook faced, starts to be an every-day challenge for any tech company working with high volumes of transactional data. The practical implications of having access to Fast Data are huge for any organization.

3V’s of Data

  • Volume. Big Data emphasizes the volume of data
  • Velocity. Fast Data emphasizes the velocity of data. Modern enterprise needs to make data-based decisions in real time
  • Variety. Smart data emphasizes the variety of data. Enterprise needs a wide variety of data for making decisions suitable for the context.

While some large enterprises have made efforts to build data warehouses, most organizations still leave the majority of their unstructured data unused. The key big data adoption inhibitor is a knowledge gap. Many companies don’t have an understanding of how to create business value based on fast-data systems and many don’t have the skills to build this type of system.

Data Analysis Before, After and During

Data can be used to analyze past, current and future.
Descriptive, prescriptive, diagnostic and predictive
Analytic options can be categorized into high-level buckets, which complement each other:

  • Descriptive Analytics: Insight into the past. Uses data aggregation and data mining to provide insight into the past and answer: “What has happened?”. Reports for historical insights.
  • Diagnostic Analytics: Similarly to descriptive analytics but with an aim to drill down to isolate all confounding information: “Why did it happen?”. Root cause analysis.
  • Predictive Analytics: Understanding the future. Uses statistical models and forecasts techniques to understand the future and answer: “What could happen?”. Forecasting of demand and output.
  • Prescriptive Analytics: Advice on possible outcomes. Uses optimization and simulation algorithms for advice: “What should we do?”

No matter, what the business is about, data-analytics can be used to understand the past, predict the future and even to suggest the best possible ways forward.

Tech Stack

A modern fast data architecture is based on four cornerstones.
aquire, store, process and present

  • Acquisition: Fast and reliable data acquisition, where data enters the system from numerous sources. The focus must be on performance and dealing with back pressure, where data is generated faster than it is consumed. From a technology perspective, this means using streaming APIs and messaging solutions like Apache Kafka, Akka Streams, Amazon  Kinesis, Oracle Tuxedo  or   ActiveMQ/ RabbitMQ/ SoniqMQ/ JBossAMQ
  • Storage: Flexible storage and querying, where both logical and physical data storage is taken into consideration. There is no single good answer on how to model the data. Textual data falls into RDBM, but not all data is text. The main driver for the increase in the volume of data is the growth of unstructured/non-text data due to the increased availability of storage and the number of complex data sources. Unstructured data currently forms up to 80% of enterprise data. While the unstructured data has no identifiable internal structure, the data models must be based on solving the use cases will be created through experiments. E.g. Redis and Cassandra are one option for running fast-data, where the speed of a Redis combined with the performance of Cassandra makes working with data fast and easy. From a technology standpoint, we are using Apache Cassandra, Apache Hive, Amazon   DynamoDB,   Couchbase,   Redis,   MemSQL,   MariaDB/MongoDB.
  • Processing: Sophisticated processing and analysis are nowadays usually implemented as a hybrid between traditional batch processing and modern stream processing. Traditional ETL processes are run as batches and real-time online processes as streams. The same goes with the location of processing; It is common practice to combine in-memory and on-disk processing to reach the optimal results. In-memory processing can be accomplished via traditional databases or via NoSQL data grids. Data proximity discusses whether data is available locally. The best performance is reached when processing local data. Data locality is the idea of moving computation to the data rather than data to the computation and data gravity mean considering the overall cost associated with data transfer. From the technology aspect, we have solutions like Apache Spark/Flink/Storm/Beam and Tensorflow.
  • Presentation: Presentation combines technology, science, and art. Presentations can be divided, for example, into notebooks, charts, maps and graphics. Common technologies here are Apache Zeppelin, Jupyter, Tableau, D3.js and Gephi.

Moreover, you need a fast data infrastructure with an affordable total cost of ownership. Common management technologies are AWS, Docker, Kubernetes, Spinnaker and Apache Mesos

Examples

Big Data Fast Data
Automakers improve the efficiency and safety of cars using data-analysis during car design Automakers improve the efficiency and safety of cars using connected, autonomous cars to optimize the route and speed based on location, traffic and predictive maintenance information
Health care system suggests for a diagnose based on a historical dataset Health care system predicts a heart attack based on real-time data
Warehouse determines what products to order based on analysis of the previous quarter The online store offers personalized recommendations real-time based on customer behaviour
Credit card company creates risk models based on demographic data Credit card company reacts real-time on potential credit fraud
Aeroplane manufacturer improves the maintenance plan of aeroplane based on data-analysis of historical data Aeroplane manufacturer suggests maintenance activities real-time regarding technical status, location, routes and coming time tables of the plane
Cargo companies optimize parcel routes based on historical data Cargo companies optimize ship and truck routes real-time based on weather, traffic and content of the vessel
Telecom operator adjusts the base-station location and configurations based on earlier collected data. Telcom operator combines fast data and 5G network slicing to split a single physical network into multiple virtual networks and apply different policies to each slice to offer optimal support for different types of services and real-time charging based on usage.

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Jari Hietaniemi

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5G Changes Everything

5G

What is All The Fuss About

5G will change everything. 5G will change how people use and communicate with technology. It will change how different technologies communicate with each other. All this will take place faster and more reliably than ever before. Mobile internet will be faster than ever. High bandwidth and low latency will transform whole industries through new ways of connecting production processes and products. 5G specs are straightforward:

  • Mobile-broadband: Lightning fast, 20Gbps(4G: 500Mbps). Users can play multi-player VR games and 8K video on mobile in the move.
  • Low latency: 1ms (4G: 50ms) latency and ultra reliability. 1ms latency enables the remote precise steering of robots (car, boat, plane, construction robot, emergency robot, war robot)
  • Massive IoT: 1M (4G: 100k devices) device connections per square km, high energy efficiency. A large industrial plant can base IoT on top of 5G. Stadium events can offer enhanced experiences for spectators.

5G Brings a Paradigm Shift

5G will recode the whole concept of mobile connectivity. 5G brings a new-market disruption, which opens a completely new blue ocean of opportunities. 5G pushes industries to seek entirely new use cases for connectivity. 5G offers a completely different performance. Throughput, efficiency, latency, reliability and device density are way beyond what earlier technologies have been able to offer; High speed, low latency, power efficient and cheap.
5G also pushes a shift from hardware business to software business. With 5G, IoT, Big Data and Artificial Intelligence, the differentiating factor will be software capabilities. New capabilities are all about thinking outside the box. Ingenuity regarding what can be done with technologies, and how they can be applied to solve tomorrow’s challenges. This is a crucial mindset, not just within the telecommunications industry, but across every technology-related industry.

Software has a potential to grow the Telecoms business with double digits.
– Bhaskar Gorti, President of Nokia Software

5G Changes also the Operator Business

Currently, operators charge customers a fee for using their pipeline. 5G will enable new ecosystem structures and monetization strategies. From a technology standpoint, 5G impacts virtually every component of the mobile network in some way. Currently, it is hard to define precisely what a 5G network really is, as each network will be different from the next, both in form and function. While one network is used as a low-latency coverage for autonomous transportation, another may be used for an affordable gigabit internet of citizens.

5G goes beyond the regular operator business; it’s a business revolution.
– Borje Ekholm, Ericsson CEO

5G enables operators or network service providers to shape their offering. This will create a completely new ecosystem, while operators are able to offer additional value in the form of innovative use cases. Operators will shift from the current man-in-the-middle to true innovative ecosystem partners. This creates the opportunity and challenge: Operators must be able to develop the underlying payment, partnership, and interoperability systems that will allow a 5G ecosystem to be monetized and to flourish.

Industry 4.0 vs 5G

5G goes beyond the path that 4G/LTE and any generation of cellular technologies went through; It’s more about enabling services. Industry 4.0 refers to the Fourth Industrial Revolution. The Fourth Industrial Revolution is now upon us. It is a fusion of fast technological breakthroughs in physical, digital, and biological spheres. Technology breakthroughs in fields such as 5G, the Internet of Things (IoT), Big Data, Analytics, Artifical Intelligence and Robotics are significant in their own right, but when combined, we are talking about the enormous benefits of Industry 4.0. The key to achieving the potential of Industry 4.0 is a collaboration between stakeholders from (traditional) industries and technology partners. This requires a new agile mindset and cultural shift.

IoT could also mean seamless critical and elderly care.
– Rajeev Suri, Nokia CEO

The Internet-of-Things (IoT) is where devices such as industrial sensors connect to the internet and to each other. This is already happening on existing 4G networks and the technology is being used everything from hospitals to industry. 5G helps the evolution of IoT by improving the interaction between different platforms as well as enabling more devices to become connected. Possible future applications include real-time health monitoring of patients, optimization of street lighting to suit the weather or traffic; environmental monitoring, smart agriculture and industrial automation, autonomous traffic, etc. 5G enables remote-anything. Industry plants, construction robots, mining systems, oil platforms, traffic management all can be run remotely. No need to have high-performance computing power at the target device. A connection is the only thing needed.

5G Critique

Because of the high frequency, 5G does not penetrate building walls well and can also only travel short distances in the air. Therefore, it will most probably only be utilized in really dense population areas. For the same reason, much of the industrial IoT still runs on top of the 2G network because of good penetration, low price and low power consumption. If talking about simple monitoring, you cannot look past LoRa and other similar long-range technologies.

6G is Coming

While we are still wondering what 5G will change, the technology manufacturers are already preparing for 6G.

I want 5G, and even 6G, technology in the United States as soon as possible.
– Donald J. Trump, The President of the United States

 

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Jari Hietaniemi

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Businesses must adapt, learn and transform faster than ever to make the most of the changing digital landscape. Gofore helps take on this challenge: together we harness design principles, strategic thinking and rapid execution to create new value and competitive advantage.

Diagram 1: Gofore works on all levels of the business

Gofore helps with creating 5G 

In the Telecom sector, Gofore has successfully helped clients to enable the infrastructure for 5G and the Internet of Things to transform the human experience – globally. Gofore has enriched software development to support proofs of concept and content creation for delivering services provided by innovative solutions, such as AI, analytics, machine learning and big data.
Alongside strategic thinking and technical expertise, Gofore has brought Agile and Lean coaching to the table. “We have integrated into existing strategy work with our iterative approach. We see that strategy is about fast paced delivery, the ability to scale with the help of standardised practises and building a learning organisation. We continuously analyse change to find useful patterns to apply to software development. Our goal is to focus on what could be as opposed to what is”, comments Juhana Huotarinen, Agile Transformation Advisor at Gofore.

Juhana Huotarinen on stage, walking through the Agile transformation ideology
Feedback from one of our global market leading clients says: “For us, it has been important that Gofore has been fully committed and accountable for what we are aiming to achieve. Our collaboration with Gofore is transparent, committed, accountable and supportive. Specifically, we are very satisfied with the Agile methodology and technical expertise Gofore has brought.
In practice, Gofore planned and coordinated a new multi-disciplinary, multi-team, multi-site high performing transformation program including Agile coaches and software specialists. This was achieved largely by creating a permissible culture which encourages collaboration and self-learning. The core competence of Gofore is to make complex things straightforward. Whether that means complex business, organization or technical challenges.

The First Steps of Transformation

We are now starting to see commercial 5G networks scaling up for transforming business and delivering better customer experience. Previous wireless technologies were about connecting people. The new characteristic of 5G is that it has all the ingredients for automating business processes and it is a great technology for business transformation. There surely are challenges to tackle in how to build the capacity in a dynamic and flexible way, how to address operational inefficiencies by leveraging automation/AI and how to increase revenue growth by means of service differentiation and the ability to leverage partners’ ecosystems. Not only with bleeding edge software, but with enabling agile strategy and culture.

Have you taken the first steps to transformation?

5G

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Petteri Mäkeläinen

Petteri has broad experience in business development, international operations and project management. He has strong interpersonal skills and is skilled to work in a highly collaborative environment. Proactive and professional, Petteri has diverse and strong managerial, collaboration and development skills having worked with a wide matrix of stakeholders. Petteri currently works as a business manager in the Telecom sector

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Creating empowering solutions

This blog post is part of our Recoding Society blog series started by Mikko’s blog ‘Creating a positive impact’. The series highlights the impact our work is having on Society. We have identified several challenges we are helping organizations and citizens to overcome, and in this series, our experts share their thoughts featuring real projects one theme at a time.
One of the challenges identified was a question relating to empowering people and organizations. How can this be done? In this blog I first deliberate about the term “empowering”.  What does this actually mean? Then give some examples of activities which I believe demonstrate developing empowering solutions.

Creating services that are beautiful

Empowering as a term is quite dated however, understanding exactly what empowering entails is still not straightforward. I conducted a small study using a group of my friends. First, I asked, “what does empowering people mean to you”. I got a wide range of answers starting from “nothing really” to “feedback from other people”, “inspiring growth stories”, “a thing that gives me energy”, “seeing confident people” and so on but nothing really what I was expecting as an answer. This made me feel a bit frustrated. Why are we using this word since it is clearly understood in so many ways? To me, empowering people means creating services that are beautiful and easy to use and that deliver on (or exceed) the users’ expectations. So I carried on  and asked next “what kind of services make you excited” and I got answers like “simple, easy to use”, “UI is easily read”, “able to use my information from several different sources”, “a service that makes me feel it has been developed for me and not for the organization”. These answers resonate with me and I can link them to my work. I can also link them to the ever-evolving world of services.
So, I guess it’s fair to say that even after a very small and by every aspect, not scientific study that a definition for empowering is difficult. It has been defined as an activity stating a concrete action where one authorizes, permits or warrants someone to do something, but often it’s more complicated. Empowering sometimes means that one ends up making someone (else) stronger, better in control of their life, more confident, happier, and so on ( source ) And when we start to get terms like these, we get close to personal feelings and experiences, but we also start comparing to a reference group which further complicates the definition. My final point here being that when we design empowering digital solutions, we must be super conscious not to get cocky, not to think that we know, but rather to be very alert of the things that we simply do not and cannot know (on behalf of others).
What do we do then when amongst all the other important requirements we also need to take account of empowering people and organizations when designing digital solutions? This sounds like an almost impossible task. How can you figure out different things that will have a meaningful, positive, sustainable, ethical and legal impact and that are also empowering different aspects of our quality of life? Luckily this is a question that we are not trying to solve alone.

Using AI and data in an ethical way

In Finland, the preliminary study on the Aurora national artificial intelligence program worked on how cross-organizationally by using AI in an ethical way, completely new services which come close to people’s life events can be developed. Empowering people by enabling easier access to more suitable services was at the heart of the pre-study. Experts from Gofore participated in ‘Moving to a place of study’ and ‘The well-being of children and parents in changing family relationships’ projects.
The MyData movement works rigorously “to empower individuals with their personal data, thus helping them and their communities develop knowledge, make informed decisions, and interact more consciously and efficiently with each other as well as with organizations” (source:mydata.org). Gofore is a member of MyData Global as we believe in the same mission to empower individuals by improving their right to self-determination regarding their personal data.
MyData.org
Already up and running in Finland, we have our very own Kanta-services where we as citizens have access to our health and prescription data and the professionals always have up-to-date patient data. Kanta-services are a huge step towards even more empowering services in the welfare sector. Much like AuroraAI, Kanta services are developed by a wide variety of operators including Kela and THL but also users and IT system developers. This demonstrates how the public and private sectors when working towards common goals and including the users, can create something completely new. Gofore is one example of a private sector company involved in Kanta-development.
Recently there was much debate and even heated discussion around the secondary use of health and social data. Despite the discussion, a separate law was approved by the Finnish Parliament on 13.3.2019 making Finland a forerunner in enabling innovative and ethical use of data.  In a nutshell, this law will level up the market for health and social services by making it possible to use data for steering, supervision, research, statistical analysis and development. In other words, this new law simply empowers organizations and companies providing health and social services to develop the market more equally.
Through programs like AuroraAI and movements like MyData plus concrete projects like Kanta, which are pioneering, I believe that significant and sustainable improvements with even deeper and wider impacts than merely empowering individuals or companies will happen. It makes me very happy to be able to say that Gofore is participating in all of the activities described in this blog.
 

Kaija Puranen

Kaija is an ICT professional with a wealth of experience and is passionate about the development of operations and data. She finds the best tools from traditional as well as agile methods for projects and applies them in organizations of all sizes. Currently, Kaija is involved customer-oriented change projects, with a particular interest in the change of leadership culture, the potential for enriched data, and MyData.

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