What does a Data-driven Economy mission mean? In short: better service, mega-shift in productivity, sustainability through less waste and CO2, fact-based decisions, true single European market, global transparency and the end of grey economy.
What does a Data-driven Economy need? In short:
1. Data - eventually most of it structured, standardized, verified and delivered in Real Time - at its birth. Controlled by me (MyData.org) or me in my enterprise. Financial and administrative data have deep traditions here and will show
the path to all sectors. PSD2 was a true Pandora's box.
The Real Time Economy (RTE) program (public-private - established by Tieto in 2006 and now also adopted in REFIT by EU) aimed at improving productivity - especially in SME and public sectors. The first focus area was e-Invoicing, then upstream to procurement,
then downstream to automated accounting and now on e-receipt and automated real-time VAT reporting. An important achievement was the national income register (real-time tax reporting and taxation).
It soon became evident that all this also means much better service - for and by SMEs, for and by the public sectors. Naturally aiming at the end-user or employee - the citizen - Mr Same Guy - at home and at work.
The next phase is to make much more use of the massive amounts of real-time data (in every purchase line, every salary, pension or social support payment line - not only the money but all the e-s - only CO2 missing? .. but all the data global regulation
has already brought to product packages..). For that we need more:
2. Algorithms. Nothing new as we know. They have already for ages been used to define the process for decision making - from simple business rules to highly complex decision engines that require greater involvement of data scientists in
tuning, maintenance and re-calibration. Typical for situations where the cost of slow decisions is not high, cost of wrong decisions is high, data size is small, or at least not too big, explainability is critical and industry environment is highly regulated
But now there is so much new verified and standardized data on offer that the scale and scope rise to new levels - and the speed can be increased. All supported by PSD2 thinking.
3. Artificial intelligence uses training data to make the decisions that algorithms prepare for. Typical for situations where cost of slow decisions is high (i.e. decision-making scenarios where speed is critical), cost of wrong decisions
is low, data size is too big for manual analysis or traditional algorithms, prediction accuracy is more important than explainability and regulatory requirements are less (2-3 as outlined by Dr. Mir Emad Mousavi).
Time will tell how much more machine-decisioning will grow when all sorts of data become available. The road forward is very much based on how much trust can be built. GDPR and MyData are central here. Then we can move from real-time to prescient.
4. Life-event driven service design. In today's world of information overflow, citizens have the right to expect delivery of data as GDPR promises - but not en masse - but access when needed and to their specific life events. All services
should aim at not serving the customer - but their life events. Some do it in their own specific area - others will be more general data service providers.
5. Progressive banks understanding customer value delivered by the economy of repetition, reuse, trust, scope, and scale. Banks have it all: the widest customer base, regulation, trust, global payment and trade finance network, PSD2, GDPR,
blockchain skills, ready services (e-id, e-invoicing, e-salary, e-payments, e-receipts..). They have the responsibility to use this pole position for society at large, customers (life-event driven services also for those not using the internet) and of course
It is their responsibility to step forward - using their role as ID-service providers towards Self-Sovereing Identity - and for politicians to ask them to do so. No other sector can make this all happen fast enough.
6. Politicians who understand the big picture and make bold decisions.
We need less nitty-gritty regulation and much more open data, standardization, and ambitious deadlines. Crucial importance for western economies - no space left for selfish suboptimization. Progressive enterprises see the picture - also by driving
new -much needed - and better regulation.