Digital Sundai Conversations – Raymond Alves

For Digital Sundai Conversations we interviewed Raymond Alves, former director of the Rockstart AI program. No video interview this time, since Raymond was driving his car while providing us with the coolest insights. We summarized our key findings for you:

Problem first, application second
Raymond: ‘Many AI startups use their technical knowledge and methodology to think of developing a certain application first, without clearly having in mind a real-world problem to which this idea can be applied. Successful startups think the other way around – identify a real-world problem or a market gap first, then start thinking of how AI can be part of the solution. Is the issue big enough to build an entire business around it? Is there any scaling potential? Explore the problem, then explore your options.

Gain experience to see the complete package
Establishing a startup without some years of working in the field is possible, but chances are you lack important knowledge on how to identify a specific market gap, business need or how to build a business anyway. Besides, gaining work experience first can also provide you with the needed insights on both operational, financial or legal procedures. Knowing all ins and outs of the problem on a detailed level ensures you have a complete overview, so you start building on an application with an exact goal in mind.’

Algorithms don’t determine success – mentality does
‘An impressive algorithm is nice, but the team’s entrepreneurial mentality really makes the difference. How well do you handle setbacks? How easily can you identify whether core capabilities can be applied in different contexts as well? In other words: how resilient and flexible are you? Make sure you have the right people on board or business partners close to you to handle every challenge your team might be facing.

Besides, paying attention to the wrong criteria for predicting success can be a pitfall. A promising revenue model and a well thought through marketing campaign are good assets to have in place, but they are often overrated. The most important criteria: growth. How can you continuously grow the amount of end users, and how often do they come back? That determines whether your startup has what it takes to be successful in the long term.’

And, last, but not least:

Want to work with AI? Check out China
‘It wasn’t until my visit to China at the end of 2018 that I witnessed how extremely fast China’s AI economy is developing. With technology and innovation being on top of mind of Chinese leaders, companies and individuals, neglecting the developments happening over there would be a naive thing to do. I am especially curious to see how China’s development in the telecommunication networks and their different approach of privacy and data will most likely influence the Western ways of doing business.’  

Want to find out more about China as an AI superpower? This book was the main motivator for Digital Sundai’s founder Robin Zondag to pay China a visit in early 2020!

AI superpowers book

Digital Sundai joins Google Cloud Partner Advantage Program

When Digital Sundai was founded in October 2019, joining the Google Cloud Partner Advantage program was something we planned to realise in our business journey. We are proud to announce that we have been able to reach this milestone within such a short period of time!

Digital Sundai is acknowledged to be a official Google Cloud Partner now, underlining our capability to help customers solve complex AI & Analytics topics to improve their business performance. The partnership provides us with even more tools, technical knowledge and access to the Google Cloud ecosystem to do so.

Bootstrapped digital transformation

Tomorrow delivered today is the tagline of Digital Sundai. At Digital Sundai we deeply believe that applying digital and AI technologies enables a far better performance of organizations. And we mean today’s digital technology, no need to wait on the even better technology of tomorrow. We also think few organizations and industries have already truly leveraged these benefits. 

At the moment the disruption of Covid-19 is accelerating the adoption of digital technology at unprecedented speed. Whether it is online shopping, remote digital education, call centres with all agents working from home, AI to detect Covid-19 from CT scans or apps to support governments to control the spread of the virus. Habits are changing and will not return fully to pre-Covid 19 days. At the same time the upcoming recession will make cost reduction a key theme for almost all organizations. This will severely limit the ability of organizations to invest in digital change. 

So here we have our dilemma. Society and markets will reward the digitally mature organizations more than ever, yet organizations will have less means to invest to become digitally mature. The answer in our view….bootstrapped digital transformation. 

Sounds good bootstrapped digital transformation but is it possible to realize digital change at low cost in existing organizations? Most research on why digital and AI are difficult to scale in organizations list several topics like strategic focus, lack of skilled resources, legacy technology, which will not change a lot in the coming period. The opportunity however lies in what most research list as key blockers;

  • Organizations are not bold enough when pursuing digital transformation
  • The way they are organized and their culture do not fit the digital age. 

Recently Covid-19 has forced organizations to be bold and to change ways-of-working to digital overnight, and in most cases successfully. The focus on the job to be done was clear, and the lack of resources nor legacy technology did stop organizations from realizing the changes. Also, compared to making these kinds of digital changes under normal business circumstances the costs were multiple times lower. 

Bootstrapped digital transformation keeps this momentum going, without the disruption that originally enabled it. Key for bootstrapped digital transformation:

    1. Top management has a clear focus for what areas to digitize. This directs the efforts of the organization.
    2. A little more action, a little less conversation please. Probably the most important and the hardest bit, especially without a disruptive event to drive it. Successful traditional organizations are in control at almost all times by a command-control way of organizing. Disadvantage is that this often requires a tremendous amount of alignment (i.e. conversation) between different silos to be able to make even small changes. A strong will to transform and the distribution of decision making authority to multi-disciplined agile digital teams will deliver digital change fast enough, good enough and cheap enough. 
    3. Use cloud technology unless. The only place where operations can be scaled fast without large CAPEX investments, access to all company data can be established, and innovative features are readily available. Probably more secure than homegrown solutions too.
    4. Mix own resources with external digital experts. When budgets are tight one cannot hire large external teams to do the job. This might be a blessing in disguise as digital requires a new way of working at organizations, which can only be sustained by its own employees. Gaps in expertise and methodology can be overcome by bringing in the right external digital experts and partners.      

Most organizations will have to accelerate their digital transformation capabilities, and most organizations will have less means to achieve this. Bootstrapped digital transformation might be a way out. This demanding fix combines a strong will to transform, distributed leadership, digital & AI technology, and the right team and right approach.


Podcast on AI for business

How about killing two birds with one stone?
Sit back, relax, listen to an episode of leadership insights by Future Processing and gain valuable insights on AI for business
Michal Grela interviewed our Robin Zondag. They covered:
➡️ Why would you bother doing AI in the first place?
➡️ How to approach an AI project?
➡️ What skills should your team possess?
➡️ How to align business, IT and Data?
You can find the links here ⬇️

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