Industry Research

Nakono produces industry research focused on the digital economy

We explain in words and numbers how the various segments comprising the digital economy work, what is driving their development and how they will evolve in the future.

Nakono is actively building what we envision will become the world's largest and most respected source of industry data, forecasts, analysis, news and deep insights on all aspects of the digital economy.

We plan to combine a large volume of expertly-curated industry data, company financial data, forecasts, news and other types of information with our own deep-level industry analysis and insights and then use the latest software and artificial intelligence technologies to allow our users to extract the precise information they need – literally in seconds, not hours or days.

Our online research service, Nakono Fusion, already offers a range of genuinely unique features such as instant search, advanced custom charting and document referencing – which allows user to click on a datapoint on a chart and have the source PDF open at the exact page where that data came from.

Nakono Fusion is a next generation industry research service that has been designed by professionals, for professionals.

The Digital Economy

The focus of our research is the business of the digital economy

This digital economy refers to the part of the overall economy that is being enabled by a range of hardware and software technologies that allow raw data and content to be collected, analysed and transmitted over the Internet either directly or as part of a digital service.

The digital economy includes the following main economic sectors:

Connected Devices
Digital Media & Advertising
Social & Web Services
Internet Evolution
Upcoming Disruption

The digital economy currently accounts for around 6% of global GDP. However, definitional and methodological limitations mean that GDP grossly underestimates the true size and importance of the digital economy.

If we use a more appropriate measure, such as 'productive activity', then the digital economy already represents around 20% of the total economy.

Today, it is plain that major technological actors like media digitisation, mobile device deployment and broadband Internet are aggressively terraforming completely new all-digital, global industries in sectors like retail, advertising, television, news and music.

But this just the beginning.

New waves of digital disruption are coming and mega industries like automotive, healthcare and finance will be the next to feel the effects of digital disruption.

Meanwhile, rapid developments in the field of artificial intelligence will soon mean that certain aspects of human intelligence will be commoditised and offered online as a service to developers worldwide, for a nominal fee.

The long term implications of these powerful forces of change are profound.

The only industries that will escape are those where the product offering cannot be digitised or where the harvesting and analysis of relevant data cannot be used to increase value delivery. This means that most industries either already are feeling the effects of digital disruption, or they soon will.

It is clear to us that the digital economy will not just become a major part of the economy, it will become the driver of the whole economy.

The digital economy is Nakono's domain of expertise.


We are building a powerful analytical model of the whole digital economy

Nakono has been deeply analysing digital disruption since 2003.

The industries and markets we analyse are non linear: products and services are often unproven, industry structures are not defined, the competitive environment is highly fluid, business models are often sketchy, consumer understanding of new products prior to launch is minimal and the wider economic context is not properly understood.

Nevertheless, our mission is to deeply understand how the various constituent segments of the digital economy works, why they work as they do and how they will evolve in the future.

Our experience is that most conventional market research methodologies consistently fail to provide the sort of information, data and insight we need, which is why:

Nakono does not conduct primary research

We have found that conventional research approaches - especially opinion surveys - can convey an impression of accuracy and methodological reliability, when none exists.

In particular, our experience is that surveys that use opinion to inform about what will happen in the future are invariably of minimal value.

For instance, if a company wants to gauge likely demand for a new product then it might hire a research company to survey the target audience.

But, ironically, the higher the potential of the product the less relevant such an approach will be: if the product offers features that are unfamiliar to the survey respondents and delivers value in ways that respondents cannot calibrate with what other products offer then the conclusions are likely to be erroneous.

As another example, we do not conduct executive surveys, which is where a few hundred senior executives are invited to complete an online survey form or are interviewed via telephone – usually by people who have minimal domain knowledge.

If conducted well, an executive survey will accurately capture the prevailing consensus – which is moderately interesting – but there are now too many examples where the consensus view of what will happen is very different what actually happens.

This is the first reason why Nakono does not conduct any primary market research.

The second reason why we do not conduct any primary research is that there is a vast trove of critical data already in the public domain which, if properly harvested, can obviate the need for most primary research, which is why:

Nakono is actively harvesting a rich seam of relevant public-domain data

Through our Industry Data and Financial Data data harvesting programmes, and others to be announced, Nakono is seeking out and curating the best possible data which defines in numbers how the various segments of the digital economy are evolving, and how that evolution process has developed over time.

Importantly, we are not using a scatter gun approach to capture random datapoints.

Instead, we are thinking very carefully about the sort of data we need and then exhaustively seeking out trusted sources that have a history of publishing data over a prior of years or decades and where source documentation and methodological information is available.

The data we are looking for is being published on a regular basis by industry associations, trade groups, NGOs, companies, consulting firms, other research companies, plus others.

And we aim to collect it all - and then make it available to you, via Nakono Fusion.

Nakono is developing a research approach that is optimum for the digital economy

When it comes to producing penetrating analysis, directionally-correct market forecasts and powerful insights in a field as complex as the digital economy we have found that conventional research approaches do not work, and cannot work.

We have instead developed a research methodology that comprises four main themes:

  • Heavy use of hard market data: The starting point for any analysis activity or forecasting exercise is to scrutinize historic and current data in order to understand how related markets have evolved in the past and how they are developing today.

    The disruption we have seen in the recent years and even past decades happened for good reasons and it is the identification of these reasons that allows us to glean insights on which historic drivers are relevant in a particular disruptive market situation, and which are not.
  • Sensitive use of confidentially-provided insights: We are constantly talking to senior-level executives working at the coal face in order to gather evidence which we use to optimise our constantly evolving understanding how the digital economy works and how it will evolve in the future.

    This provided on a strictly ‘off the record’ basis by leading industry practitioners – many of whom are working in listed companies. We do not participate in industry analyst programmes and we do not work with PR functions because we have found that doing so means that the information we need is.
  • Null hypothesis testing: When we are predicting how a given market will develop our approach is to imagine a plausible market outcome - the ‘null hypothesis’ - and then narrate what that outcome implies in terms of aspects like related markets, company growth, penetration levels, total spending, and market share.

    We will also look for hard evidence in the market to support the hypothesis – such as product announcements, R&D programmes, regulatory developments and more. Another important consideration is the long-term saturation level of the market we are analysing and how the various enabling technologies will evolve.

    If we feel that the hypothesis can be supported by taking a holistic perspective then we consider it to be ‘directionally correct’ and will then use it to develop a forecasts which will be based on both bottom-up and top-down approaches.

    On the other hand, if the null hypothesis is not supported by the facts, leads to logical conflicts of is challenged when new information comes to light then will modify the hypothesis, or reject it and start again.

    This iterative approach, played out over 13 years, has led to a deep level of understanding that we have of the digital economy.
  • Axiomatic- based prediction model: Our repeated use of the null hypothesis approach in our forecasting has led naturally to a growing set of core principles that we believe define how the digital economy works and powerful predictions about and what will happen in the future.

    Based on strong evidence and argument, we believe these foundation statements are things that we believe to be true, but they cannot be proved to be true. As with science, it is only the discovery of new evidenced – market developments or new insights in our case that will cause the axiomatic foundation upon which out entire research output is based to be adjusted.

    In an axiomatic system – like mathematics - a small number of core axioms can be used to logically derive a rich body of knowledge that, in our case, allows us to narrate our predictions and extract new, valuable insights.

    We are in the early stages of developing our axiomatic prediction model but we are confident that this will be inform about the future direction of the digital economy to a level of detail and directional correctness that is unprecedented. in the field of technology industry research.