(Part 2/2)
III Economy and Business Congress Barcelona, April 2018
Full Article published in: Digital Transformation and Artificial Intelligence
If you want to read part 1 click here
Part 2/2…
3-Imbalances of the Digital Ecosystem. (Strong, medium or weak digitization)
Based on the digital ecosystem model that incorporates a set of indices beyond the purely technological and the equation of the exposed digital ecosystem, we proceed to calibrate the level of the indices for each member country to obtain figure 4, and where the size of the the bubbles indicate the value of your GVA CARG (Compound Average Rate) for the years 2010 to 2016 (dark positive / transparent negative).
At a visual level, it can be observed that most of the countries that have positive performances are in the upper right quadrants which indicates that a balanced development of all the indicators (DESI and CEI) lead to a good growth of their GVA, while, in the lower left quadrant, are those countries that, either have all indicators very underdeveloped or well, have significant imbalances and therefore worse performances of their gross added value as a country.
Based on this information, we will proceed to position the performance of each member country with respect to the performance of the European Union average (EU28) in order to classify them according to the level of development of their digital ecosystem, see Table 2.
In it we establish three groupings according to the degree of satisfaction of the “Digital Ecosystem Equation” model. For its preparation we establish a better / worse ranking (better / worse) of each member country with respect to the average values of the total EU28. In this way we can visualize the highest and lowest performances of each country and each indicator. Thus, for example, we find countries such as Sweden (Se) or the United Kingdom (Uk) with performances above the European average in all indicators and therefore classified with the category of digital ecosystem “high” for being positive the two indices at the same time (CIE and DESI) versus the Union average. At the “middle” level of the category, countries that only have one indicator (DESI or CIS) greater than the average are grouped. For the “low” level of the digital ecosystem, we add the countries whose indicators are below the average at the same time.
From table 2, three categories of the Digital Ecosystem are established based on the performance of the indicators worked:
o Strong Digital Ecosystem: It is formed by the countries that exceed the INDI and CEI indexes with respect to the Union averages. Here most of the countries of central and northern Europe are grouped.
o Digital Medium Ecosystem: In this case we can observe the group of countries formed by Latvia, France, the Czech Republic, Spain and Portugal. The case of Spain (Es) in particular stands out for having a better performance in the digitalization index of DESI compared to the Union average, while its CEI and GVA indexes are below. Opening the focus on its CEI index, we see that all the indices that compose it (Competitiveness, Workers’ Commitment and Innovation) are negative compared to the Union average (2015 and 2017).
o Low Digital Ecosystem: This category includes those countries whose both the DESI index and its CEI index are significantly below the growth of the Union. Despite this, it is observed that some of these countries show a good performance of their GVA. This could be explained by the fact that these are countries whose economies are developing and the value of their GVA is strongly dependent on other variables not analyzed in this study. In any case, it is significant to see that these are countries that have recently joined the European Union and that have high volatility in their magnitudes. However, it is surprising to see Italy or Greece in this category.
4-Conclusions and limitations
We have seen that the Digital Momentun concept can shed light on what path and speed each country is taking under the digital magnifying glass. Thus, we find countries such as Spain that is in a “Momentum Outstanding” or outstanding when presenting a DESI index above the European average and at the same time have a digital trajectory with good cruising speed and good growth. In this way and in a first phase, we have classified the countries according to these two variables (value of the DESI index and speed of the digital trajectory) to configure a “finish” photo of each country that allows us to know in which situation find the countries of the Union. We could say that if we wanted to know when the race or digital competition is, this magnitude would be very useful.
However, knowing the digital performance of a country would not be enough because it does not inform us about possible imbalances that may occur in parallel and on which this vector has an impact. It would be a data of the part and not of the parts of a greater whole. We could ask ourselves if this Digital Momentum is prioritizing in addition the “digitization” of companies, industries, institutions, or is following the path of digitalization. The fact is that taking one or the other direction will prove to be a determining factor in the advancement of the economy of the country in question. Moreover, taking a wrong path can undermine the future growth of a country in terms of its growth in gross value added or create a favorable but short-term illusion without substance.
To try to see what kind of digital tilt each country takes, we have made use of the concept of ecosystem considering that the digital impact does not act in isolation and that digitalization plans and adheres to something else, on fundamentals that go beyond what properly technological. In this case, we have tried to include under the equation of the digital ecosystem, factors such as competitiveness, innovation and the commitment of the workers of a country through the preparation of an aggregate index CIE, to later cross it with the index itself DESI in order to discover if there is a balanced growth between them. Our intention has been to see if a better or worse performance of both indices affects the performance of the GVA of a country (not in the part of the quantity if not of sign) and the model has allowed us to confirm the two hypotheses of departure when verifying that The majority of countries with the best performance of CEI and DESI indices in a given period also have a better GVA index compared to the average. Therefore, if your country favors its indexes of innovation, competitiveness and the level of commitment of its workers and adds the digital factor to them, its effects on the GVA will have a high probability of being favorable. Nevertheless. the countries with greater imbalances between their DESI value and the rest of the indices, have lower values in the performance of their country gross added value, presenting the case of positive values of DESI and negative of CEI translating into a negative value in GVA (Spanish case) . Therefore, and according to what has been said, we have classified the countries into three types of stadiums on their digital ecosystem (strong, medium and weak).
Analyzing the countries’ own transformation, doing so from the perspective of momentum would be short-sighted. Take for example the case of Spain. We have seen that its digital trajectory in recent years has led it to position itself at a DESI value (53.5 out of 100) above the EU28 average (52.4) and at a speed of its frankly enviable trajectory (outstanding) . However, when we analyze the growth of its gross added value of the last six years with respect to the EU average, we see that its performance has been not a little but, substantially lower (-2pp B / W) for the period 2010- 2016 It is true that the result of such a macroeconomic magnitude as the gross added value is the result of multiple factors that go beyond the present study. Despite this, what we can affirm is that even with these good results in the digitization index, when we focus on what kind of practical digitization, it is revealed that their values (better / worse average EU28) in the indexes of innovation (-1.05), competitiveness (-1.55) and level of commitment of workers (-9.41) are far from the average of the member countries and a gap of those with better results. This shows that the digital transformation model practiced in Spain is very skewed towards “digitization”, ie a medium or weak digitization focused on processes, cost control, the increase in the network of people and things, forgetting the importance of necessary innovation, the creation of more competitive environments or the importance of the commitment of employees in companies or institutions, for and through digitalization to achieve a strong digital environment. So, here we have a country with a high DESI index, with a good digital speed, but with low levels in other pillars fundamental for the development of the country and as the model shows with an average digital ecosystem. Taking into account the starting hypothesis and concluding that at a better level than the European average of the indicators DESI and CEI in unison corresponds a greater probability of a GVA of higher growth, it will be very risky to focus exclusively on improving a single indicator.
It is also true that the model includes countries such as Romania (Ro), Poland (Po) or Bulgaria (Bg), among others, which present good indicators in their growth composed of gross added value despite having also strong imbalances between their indices DESI and CEI. The analysis of these exceptions is outside the scope of this study and could be due to growth models corresponding to developing countries recently incorporated into the EU28 and whose volatility in the delivery of their magnitudes is very high. We can also observe countries with good equilibria between their indexes and in a high digital ecosystem stage with scarcely lower values of the growth of their GVA (Holland, Finland and Denmark). This may be due to the fact that the variables that impact the performance of the added value of an economy are multiple, even sometimes singular, of each country and, as we have already said, this study in no case aims to find correlations or causality among the set of variables analyzed.
And it is not that digitization is not important, of course and a lot, but it would seem that it is not enough to grow. It has been wanted to emphasize that rather it is about building a strong digital ecosystem, of unfolding the digitalization maintaining a proportion and not losing sight of the rest of high impact factors to try to stimulate its growth in unison mode. Therefore, public (and / or private) policy should ensure a good balance in its actions to boost the variables of digitization, innovation, competitiveness and labor “engagement” in a joint and not isolated way, as it stimulates, As we have seen, a greater probability of the growth of your GVA as a country.
As a final conclusion we can say that the digitalization of a country and what all this implies, requires a peripheral vision that contemplates the very ecosystem that the digital nerve affects because the advance in the digital index exclusively, does not guarantee growth and less when magnitudes As important as innovation, competitiveness or the level of commitment of workers with their companies in the country, among many others, are stagnant or far from the European average. Digital transformation requires a solid and growing foundation — a strong digital ecosystem — to deploy its full potential beyond incorporating technology that is so necessary, but not sufficient.
Regarding the limitations of this analysis, we can mention firstly that this study does not analyze the factors of causality and their relationships, leaving it for later analysis. On the other hand, digitization is investigated in its aspect related to a specific set of official indicators (DESI, GCI, GII) or own elaboration (Employees Engagement) not taking into account other factors, indexes or data of very high draft in the digital and economic environment of a country. In the third place, there is no mention of the business processes or models of the companies / industries or other very important variables such as the education system, the level of poverty, the endowment of natural resources, the rate of trade opening and many more. In addition, the model used does not include the level of sectoral specialization of each country, its “ad hoc” competitive advantages or other factors such as monetary, fiscal, employment or inflation policy, although it has been avoided, as far as possible. possible, the effects of fiscal policy when working with the GVA instead of GDP (Gross Domestic Product). Another fifth notable limitation is that the indices have been weighted at the same level both for the construction of the CIE aggregate index and in the part corresponding to the digital ecosystem equation. All this is due to the fact that this analysis does not pretend to find the causality relationships nor any type of correlations between the variables used.
Finally, the study does not include other countries outside the EU, which would give it an additional value by containing more information and having a wider spectrum of contrast for the confirmation of the starting hypotheses.
Potential areas of study could include: adding other variables to the ecosystem, applying quantitative methods or other methodologies or models, and even the possibility of researching the values of the DESI, CEI or other indices multipliers and even carrying out this exercise with other countries outside the European Union.
