innovation delivery

Define it, Nail it, Scale it – Moving from Innovation to Delivery

How to get that digital product offering out to the market before the competition? How to do innovation and scale at the same time? How to get those digital architects, data scientists and design professionals all into the same room – when the agile devops team is already taking all the seats?

The good news is that there is already a set of useful tools and approaches around that match and mix well together. There’s no magic needed but it does not hurt if you consider the steps you take from innovation to delivery as an end-to-end process.
At Symbio, we have a long history in product development and software engineering. A lot of the stuff we’ve learned the hard way – and even more by working together with others, with our customers, our partners, our whole ecosystem and the wider developer community.

We want to give back also. Please find below our contribution on how to get things done in the digital age.

Define it!

So maybe your great idea is in square one. You have an opportunity or a challenge but no solution yet.
It would be nice to come up with an innovative and validated solution concept. How to do this with minimal risk, in days rather than months?

To get started you will need a solid set of methods and tools that can help you find the best ideas and to test them quickly. We have benefitted to no end from applying Design Thinking concepts and approaches to our work.

Just expecting that people will magically come up with ground-breaking ideas usually does not work. However, when you have the right tools and methods, you can ideate, create prototypes and run tests within a week.

Validating the idea as soon as possible gives you more confidence to build it further. And if it wasn’t the ground-breaking one, you didn’t lose that much time and money developing it.

This is where companies often stumble: when presented with an idea our first natural reaction is to think about the solution. Continue on this path and maybe you end up taking a month or two to come up with a technical prototype.

However, what you should really be thinking about is how to get more and even better ideas to the table, and how to test them right away. This is the part where you should fail fast, throw those things away that will not work and keep only the best ideas.

We believe in innovation by design, not by accident. Good design is not aesthetics, an event, a product or an experience. Rather it is a process – and you should approach it as one.

By injecting insight and a right set of skills into that process, you get the winning formula. The team needs to understand both what is technologically feasible and what is viable from business perspective.

Most importantly, you need empathy for the user. Build the user understanding and find out whether your ideas are usable and desirable. You should keep empathy in the center – it is amazing how easy this is to forget if you do not pay attention to it.

Nail it!

Now let us assume you already have an initial solution concept in place. You have tested it and got initial validation for it. People will want it, it is technically feasible and it will create business value.

What you are looking for now is a real solution, a Minimum Viable Product you could go to market with.

Once again, there is a set of tools and approaches available for you. Lean Start-up methodology offers a good starting point. If you already got validation for your concept, you are not looking to fail anymore. You will still want to learn fast.
Build a first version, launch it with a target group, measure how it resonates, learn from the findings and build a new version. Repeat this as long as needed. You will want to nail that MVP!

You will need to make hard decisions based on the input you generated. You might want to stand firm and sweat it out. Perhaps you should pivot and course-correct using a new fundamental idea. With every new customer, you get to learn more about the needs and expectations of your future customer base.

It is not only about the customer experience though. You also need to consider what kind of technologies and business models make sense, how the competition will be behaving and what are the customer-side activities required before the benefits materialize.

A lightweight tool such as Business Model Canvas will help you create common understanding on your product’s value proposition, on your customers’ expectations, on business realities and perhaps the infrastructure you will end up relying on.

In particular this allows you to prioritize and to make difficult choices by making it easier to illustrate the trade-offs in the process of defining your MVP.

Common understanding is helpful here. Yes, someone needs to make those hard decisions and it will be easier for the team to follow if the rationale is clear for all.

You will also need the right mix of skills in the team to make sure you stay on track. Maybe you will need to ideate a bit more or perhaps you should start considering how the product will develop as it matures.

Scale it!

So, let us say you have already managed to attract a solid interest in the market. How do you scale your product for global use?

Moreover, once you enter that global market, how do you stay ahead? How do you make sure that all the effort you put into development is creating customer value as soon as possible?

Continuous Delivery will help to deliver the promises of Agile. Some might still assume that if you want to deploy software more frequently you will necessarily compromise stability and reliability. However, it appears that rather the opposite holds true.

In fact, you will find peer-reviewed research showing that high performance teams consistently deliver services faster and more reliably using Continuous Delivery. We believe this applies to most domains and use cases for which one engineers software.

Yes, you should continue to develop user stories, epics and themes to structure your work to appropriately sized chunks. You should also take time to ensure there is visibility and feedback so that team members can learn about and fix issues as soon as possible. You also need to build in means and coding practices to ensure you can deploy whenever you choose to do so.

Building a culture of collaboration is at the very heart of getting things right. DevOps offers the right mind-set and the right practices for a cross-functional mode of working. If the team members from development, testing and operations are all in, you are already holding keys to success.

When the whole team understands the way of working, it allows you to accelerate time to market while increasing reliability. It also helps you to gain end-user feedback quicker and earlier, helping you to make sure you are still building the right product.

Wherever you can, you should automate. Some might consider cost-efficiency as the main driver in this. However, it might be that the flexibility you gain turns out to be much more valuable. You might also deliver quality benefits that are difficult to reach without automation.

How about all the new technologies? Artificial intelligence and machine learning are all the hype today. Should you also use Continuous Delivery when approaching such technologies? The short answer is yes.

The industry is still young but there is a lot to gain and you should embrace Continuous Delivery also with your AI enabled offering. For example, you might use smart automation to figure out when to re-train your models instead of going for a scheduled approach. Better user experience, less compute.

It is going to be data driven …

The tried and tested adage says that you should start from the business need. Even when delivering new innovative solutions. At times, it might be the advances in technology are so fundamental that they inspire new business.

Whether you are producing industrial equipment or consumer services, your offering is going to be data driven. You are going to do artificial intelligence or intelligent automation, and there is going to be software and analytics in your offering.
You will need to build in capabilities for data science and machine learning, for data engineering and automation. We believe that these capabilities will be central for new product offerings in most industries.

You might be creating new digital customer experiences with conversational platforms. Perhaps you are working with your new data driven industrial product, making use of your install base and differentiating where others cannot.

If your core offering is a pure commodity, you will perhaps focus on using these approaches for internal efficacy and efficiency. Or maybe you will find a way to convert your service function to a sales channel.

This is to say that in addition to the designers and engineers working on the other aspects of your offering, you will also have teams building machine learning models and laying down data pipelines.

You will fare better if you do not think about Artificial Intelligence as a single field of research or one specific approach. Instead, think of it as a toolbox that is in fact generic rather than specific.

You can use these tools and some raw materials (yes, data) to build intelligent value add into your offering. This might even turn out to be the core of your next product or service.

We believe you will need this AI & Robotics toolbox and the relevant skillsets around whether you are just starting to ideate or you are already far delivering your product.

One day the focus might be in exploratory data analysis. On the other, it will be about making sure your data pipelines are feeding your models with quality data.

… enabled by digital architectures

To build leading digital products you will need a solid set of architecture and technology skills. It might about the architecture for processing all that data or it might be about architecting for Continuous Delivery.

Whether it is about enterprise architecture or software architecture, it is the architect’s role to match technology with requirements.

To match and to go beyond requirements, you will need to perform many smart choices. There is no shortcut – you need a trusted architect with in-depth expertise on picking the right methods and practices, able to choose the right platforms and tools.

A solid solution architecture looks at the whole – people, processes, data and technology. You need a core that runs solid, and you need to leave room for and embrace experimentation.

Maybe your concerns are more oriented towards enterprise architecture. How to align the landscape with business strategy and goals. Industry knowhow is key here, understanding the business context and the appropriate technologies.

It might be you are composing a complex solution out of commercial off-the-self components. Understanding role and purpose of each component is key. Perhaps you are building a complex bespoke system. You will need a proper software architect to look after it.

Besides the cloud, maybe you need to worry about the edge also. Maybe you also need someone to pick the right hardware components, to get them running and interacting. To enable your intelligent device and to make sure the user experience gets better over time, instead of degrading.

Whether its enterprise or software architecture you are looking for, you need to make sure the architect is not only an expert in technology but also understands deeply what you are trying to achieve.

It is the architect’s job to question both the requirements and the technologies employed. The architect should be worrying both whether you really know what you are looking for and whether your future house will stand the test of time. If your architect is not worrying about these things then it is a question of good fortune.

It might be you are just starting to ideate or perhaps you are already out there deploying new products every month. Either way it is difficult to come by if that comprehensive view on requirements, technology and architecture is not present in your team.

The combination creates the value!

We have structured some of our key teams around the thinking described in this article. We believe this allows us to move from innovation to delivery with ease and to get digital products out to the market faster than ever.

Our Innovation team focuses on getting the best ideas defined. Our Solutions team can build on those ideas and nail that minimum viable product. The Products team can scale it up whether it is a mission critical industrial solution or a consumer grade product for the global market.

The Artificial Intelligence and Robotics team will not shy away from machine learning models or complex mathematics. The Architects and Technology specialists will guide you towards the goal whether you need data pipelines in the cloud or embedded software on your device.

We believe it is a good idea to avoid drawing strict borders to divide those capabilities and skillsets. If there is overlap, there is no gap. Your ideation will be easier if the architect is deeply familiar with design thinking. It also helps if the data scientist knows how to do agile software development.

Build your teams to work together – not in silos. In the end, the real key to success is the right team of people working together. And having a good time while doing it.