Thinking

Digital imperatives: Succeeding in the digital age

Starting your digital transformation can be tough and take a lot of effort. An inherited factor of the digital age is complexity – a complexity that can cloud the prioritizations of even the most clear-sighted executive. We have distilled this complexity down to seven areas which all organizations and executives should consider, if they want to thrive in the digital age.

To be successful in the digital age, we believe you need to understand and consider seven areas.

  1. Understand the impact of technologies and trends – now and tomorrow
  2. Be customer–centric and understand your customer experience – the full 360 degrees
  3. Adapt to a data–driven workflow and understand the impact of AI technology
  4. Iterate your business models – and sometimes make tough choices
  5. Build long-term capabilities for change – not just run individual initiatives
  6. Harness the power of partners and ecosystems – you can’t succeed on your own
  7. Understand how digital tools and automation impact your processes and organization

You need to understand the impact of technologies and trends – now and tomorrow


Development, progress, and change is continuous, they never take a break. If you want to succeed in the digital age, you need to understand how this impacts your company, and when to start planning for that impact.

Many changes are technology-driven, but the most change does not occur in the technology itself – but rather in the people, their habits, and their culture. Take Facebook for example. Social media had been around for at least a decade. However, Facebook managed to crack the code on how social media should be designed – and therefore changed how we interact with friends and family.

But what is hype and what is real? If you try to read up on what new technologies and trends are out there, you might be tempted to buy trend reports, read tech news sources, etc. However, many of these sources are often sensational (because they have an incentive to be), and it might be difficult for you to understand what will actually have an impact for you. To mitigate this, you can try the following:

  • Talk to industry and technology experts. Make sure you find people who have little bias and have aligned incentives to your own. For example, industry experts who aren’t benefiting from being sensational. Talk to them, don’t just read the reports.
  • Listen to the Innovators and the Early Adopters. This in reference to Geoffrey Moore’s book Crossing the Chasm. These are the people that adapt new technologies and cultures, years before the masses do.
  • Talk to your customers. Knowing your customers is always important. Even more important is knowing the percentage of your customers who lead the way for others, and have great feedback on your company, products and services.
  • Listen to the start-ups. Most startups are great at understanding where the wind is turning, as they are small, agile, fast-moving and customer-centric. Invite a number of startups for a discussion on industry trends, and learn from them.
  • Make prioritizations. Distill all the input and make sure you, and your organization, have a real discussion together on what you should prioritize, and when/how you believe this will impact your business.

As a final note we encourage you to consider the impact of Moore’s Law, when doing these exercises. What’s Moore’s Law? It’s the observation that the number of transistors in a dense integrated circuit doubles about every two years. This is (very roughly) true for the price and the performance of other technologies, products, and services in general. Simply put: Things get better and cheaper, quickly. Therefore, when you research technologies and such, ask yourself: What if this technology was 10 times better and/or 10 times cheaper?

Where to start? Research the top five technologies and trends that will have an impact on your business within the next 5 years. Try to understand what the impact will be, when it will happen, and how you should get on top of it. Have these discussions throughout your organization and make this a recurring work, with explicit responsibilities.

You need to be customer-centric and understand your customers’ experience – the full 360 degrees


In the digital age, customers and users have zero tolerance for poor user interfaces, product disruptions, lacking functionality, poor customer service, and generally unsmooth experiences. Competition is fierce and they simply have to many options to choose from. By understanding the actual experience of your customer, you can improve it. Furthermore, by being truly customer-centric, you can solve new problems, build new solutions and make new business.

Optimizing the customer experience is something that most companies work actively with. However, we find that many companies forget about the very basics, such as providing correct information to customers, having correct invoices, working payment options, communicating with customers in a relevant way, etc. This is often related to your internal organization, your systems, your data quality – three things that your customers will never care about.

When you’ve considered the basics, you can move on to actually trying to provide new digital interfaces and products for your customers. What this means will vary depending on your industry. For industries with physical products/services a good start is a modern “user portal” (though you should call it something else), where your customers can buy, modify, and understand the services you deliver. It’s not rocket science, but it can still produce real results. For other industries a user portal is not enough, and you must look at digitizing the entire value-chain and the end-product instead.

To actually be customer-centric and user-driven is something altogether different. This means putting your customers in the very center of everything you do. It means interacting so frequently and deeply with your customers that you understand their most pressing issues and begin to find new solutions for them. For most companies this is a leap to large, and we encourage small moves to progress forward. Take inspiration from what the leaders in customer-centricity are doing – such as Amazon.

Where to start? Go and talk to your customers – yes you, don’t send your minions. Understand them and what they need, what they love and what they hate about your product. Make sure that your entire organization do the same and ingrain this process in your day-to-day workflow. And when you are done with that, go talk to your non-customers to understand why they aren’t your customers.

You need to understand how data can drive your business and the impact of artificial intelligence technology


In the digital world everything can – and should – be measured. This is fantastic news for executives who wants to build a data-driven, fact-based business. Theoretically, the data-driven workflow is a straight-forward cycle of three simple steps – which can be applied to your entire organization, or any given part of it:

  1. Measure and understand. Decide which indicators that makes sense to measure, and make sure that they are measured consistently over time. Understand why the numbers look like they do, and what root-factors that make them go up or down.
  2. Target and improve. Understand what you can do to improve the numbers, and set bold targets for doing so. Identify a set of hypotheses and priorities, which is your best guess for how to improve your numbers in line with your targets.
  3. Iterate and repeat. Make iteration into a continuous practice, where you constantly evaluate your actions against the numbers, always looking for root-causes and new facts. Set even bolder targets to improve and do it all again.

This process might seem straight-forward in theory, but to do it at scale in real-life is often more challenging. In practice you often need to build new support systems and enabling foundations, to allow you organization to work with a data-driven workflow.

Competency and resources are important factors. You might need to update your systems, and look over the roles you have in your organization. Many organizations find themselves needing data scientist roles, to enable the data-driven workflow. If properly organized, this type of role can be a very powerful addition to any company.

Transparency and broad understanding of data are other key factors. To align an organization everyone should have access to the same data points, understand them equally well, and understand how they personally can affect them in a positive way. This can for example be done by putting up digital dashboards, showing real-time updates of the most important indicators. This also helps when you want to have cross-functional discussions on how to improve the numbers.

Note that transparency can be intimidating and lead to conflict. When organizations start measuring things they have not measured before, the spotlight usually moves into places it has not ventured before. This is a good thing, a way of turning every stone in order to improve, but it might also put some people in your organization on the spot – especially if they are not performing very well. In these cases, it’s important to act as a team and have productive discussions on how the organization as a whole can improve to succeed with its mission.

Apart from the performance management aspect detailed above, you should also understand how your data can drive product and business development. Data is a key asset in the digital age, and if you leverage it properly you can use it to expand your business. In practice you can do this by performing a business discovery process based on your data. In short, you should take inventory of the data you have available and detail what opportunities it presents.

How will the continued development of AI impact your business? Even though we are decades (?) from the development of a general artificial intelligence, we already now see how AI technologies and algorithms, can have a profound impact on businesses. Some examples on areas affected by AI are image recognition, natural language processing, and optimization – which in turn have led to advancements in everything from cancer screening to autonomous vehicles. You should analyze and understand how AI technologies will affect your organization and business – now and in the future.

Where to start? Follow the outlined process for building a data-driven workflow, and remember to start small and expand when you have a good practice that works for your organization. Make an inventory of your data and analyze new opportunities for business and product development. Make sure you stay on top of how AI technologies can affect your business.

You need to iterate your business models – and sometimes new models will compete with your existing ones


A large part of digital transformation is about business model change and innovation. The most successful companies manage to produce new, and constantly innovate their business models, and therefore thrive in the digital age.

Business model is a broad term, referring to the logic of how an organization “creates, delivers, and captures value” (referencing Business Model Generation, Alexander Osterwalder). What does this mean in practice? To us it means that you have to constantly innovate the way you do business.

Depending on your context this can mean very different things, but here are a few examples of business model innovation:

  1. Process: Innovate on how you create and deliver you products of services. Example: Uber. Uber were able to quickly build a huge network of drivers. By doing so they were able to serve customers quickly and with low prices.
  2. Product. Innovate your products and services and the value they create. Example: Tesla is a great example of product innovation, where they built and popularized an entirely new car segment.
  3. Pricing: Innovate on how you capture value and charge for your products. Example: Spotify managed to provide a flat-rate model for unlimited music, when their competitors sold albums or songs.

Trying to innovate your business model can lead to competition between “the old and the new”, both externally towards customers, and internally in your own organization. Often, disputes or unclarities can be managed by simply testing what works and what doesn’t. Stop talking and start testing with real customers, and let them decide which model is preferred. This might require bold decisions, such as starting up a new side-business, somewhat separated from the ordinary business to test a new business model. As always, make sure it’s a team effort and avoid ending up in “old versus new” or “legacy versus innovation”.

Where to start? Map down your current business model(s), for example by using the Business Model Canvas, or our favorite, the Lean Model Canvas. Have a discussion on where you believe there are opportunities for change. Try in small scale and expand – if successful.

You need to build long-term capabilities for change – not just run individual initiatives


Speed, complexity and scale are three inherited factors in the digital age. Because of these factors, it’s impossible to be successful in the long-term by simply launching a “digital project”. You need to structure your organization in such a way that you own the needed capabilities for change. By having these capabilities, you can manage and navigate the uncertainty of the digital age more successfully – and be ready for what the future might hold.

New roles and functions. To manage these long-term capabilities, you might need to look over which roles and functions you have within your organization – especially related to the area of “management support”. This can be functions who are responsible for strategy process, portfolio management, business transformation, and similar.

More fluidity, less hierarchy. When market and technology move quickly, then upper management can sometimes have a hard time in following – which can result in they becoming a blocker. Many new types of organizations reduce their management levels and make sure that decision-making is moved to the front-line, where people actually knows what’s going on.

To plan or not to plan. If the future is tougher to predict, then long-term planning becomes more difficult, but arguably also more important. We believe that the key here is balance. Try to plan, but understand that the plan will change – even within the year. Most organizations should avoid detailed long-term planning altogether, as it only wastes time. Excessive long-term planning is sometimes used as a way for middle/senior management to justify their own position, which should be avoided.

Where to start? Have a discussion on what roles and functions you think can be needed to be more future-proof in your organization. Discuss your management system and organizational hierarchy, to understand if more decisions should be moved “to the front”. Discuss how you plan for the future, and what level of planning is right for you.

You need to harness the power of partners and ecosystems – you can’t succeed on your own


In the digital age, more value is created in the form of ecosystems than before. This means that all organizations must look to what they themselves do best, and what value they can bring to each ecosystem. When another part in the ecosystem does something better, then use them instead of doing it poorly yourself.

Know your value. When starting new discussions on collaboration or the use of ecosystems and partners, you often end up asking yourself: “What value do we actually bring to the table?”. This is an important question which require a clear answer, and alignment within your management team. Typically, this question should be answered by your business strategy, and that work should therefore proceed any significant discussions on collaborations.

Talk to the startups. Startups are good at knowing the customers and their needs. They are also good at moving quickly to cater to these needs with new solutions and products. If you represent a larger corporation, then perhaps there are opportunities for collaboration – which can be mutually beneficial. Usually large corporations can bring three things to such a discussion: Brand recognition and trust, scale and reach, and resources.

Collaborate with customers. The relationship between companies and their customers is often more complex and intricate in the digital age, than before. Customers don’t simply just buy things anymore. Instead, they interact with brands and organizations in a way which can be very beneficial for all parts, if used correctly. One example of this is the way that many technology companies solely use their customer-base for decisions on which features to add.

Where to start? Make sure that your organization is aligned on your business strategy, and that you know the value you bring to the table. Discuss how you can use ecosystems and partners to build new products and services, or to reach new markets. Understand how you can collaborate with your existing customers, to provide even more value to them.

You need to understand how digital tools and automation will have an impact on your processes and organization


Digitalization presents great opportunities to build new business, but also many ways of achieving internal efficiency through new tools and by automating processes. Most organizations can benefit drastically from using modern software for their processes.

Investigate outsourcing. Outsourcing is always an interesting option for non-core processes. What is core and what is non-core is an age-old discussion in most organizations, that will probably never have a distinct answer. For example, most organizations argue that accounting is not a core process, yet they have large departments doing only this. This is often due to legacy, and perhaps trust-issues. We would recommend to ask yourself: “if we built this company from scratch today, would our accounting department be this large?”. Most often the answer is no, and then you can look for new solutions and how you should transform.

Discover new modern tools. Keeping with the accounting example from above, there are some fantastic new digital solutions out there who have automated most accounting processes in full, where you can trade large parts of you accounting organization for a monthly fixed SaaS fee instead. This is true for many standard processes, and we advise you to stay up to date on current possibilities. Another area where many companies can improve is collaboration. Far too many emails are sent each day, which perhaps should have been a quick video call or a Slack message instead.

RPA might be right for you. A current popular notion within automation of processes is RPA – or Robotic Process Automation. This basically means having “software robots” or “AI workers” take over some tasks previously performed by humans. We believe that this is a double-edged sword, and that organizations should approach RPA with sensible caution. While RPA can reap benefits, it can also become a stopper for long-term digital transformation. It can act as a sort of glue (or “virtual duct tape” as some call it, see references), which helps you in the short-term, but which doesn’t really fix the underlying challenges.

Where to start? Make a simple map/chart of your processes and internal workflows. Have a discussion on where you believe there is room for improvement. Search for new tools and software which you believe can increase your efficiency.

We believe that excelling in these seven areas will give you a head start in your digital transformation or perhaps get it back on track again. Do you want to know more or need help with a project related to this topic? Talk to us on hello@avrio.se to see how we can help. We always welcome your queries and feedback.

References, material and further reading


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