A reflection on Mobile World Congress topics mobility, digitalisation, IoT, the Fourth Industrial Revolution and sustainability

Commerce has always had a conversational, today it is digital. Organisations are asking how to organise clean effective data for an open digital conversation. 

Digitalization’s aim is to answer customer/consumer-centric demands effectively (with relevant and related data) and in an efficient manner. [for the remainder of the article read consumer and customer interchangeably]

This essentially means Joining the dots between clean data and information and being able to recognise the main and most consumer-valuable use cases, be it common transaction behaviour or negating their most painful user experiences.

This includes treading the fine line between being able to offer “intelligent” information (intelligent in terms of relevance and context)  to the consumer effectively and not seeming to be freaky or stalker-like. The latter is dealt with by forming a digital conversation where the consumer understands the use of their information only being used for their end needs or wants.

While clean, related data from the many various multi-channel customer touch-points forms the basis of an agile digital organisation, it is the combination of significant data analysis insight of user demand & behaviour (clicks, log analysis etc), machine learning and sensible prediction that forms the basis of artificial Intelligence. Artificial intelligence broken down is essentially resultant action based on the inferences of knowing certain information, i.e. the elementary Dr Watson, but done by computers.

This new digital data basis means being able to take data from what were previous data silos and combine it effectively in a meaningful way, for a valuable purpose. While the tag of Big Data becomes weary in a generalised context, key is the picking of data/information to get relevant answers to the mosts valuable questions, or in consumer speak, to get a question answered or a job done effectively.

Digitalisation (and then the following artificial intelligence) relies obviously on computer automation, but it still requires some thoughtful human-related input. Important steps in the move towards digitalization include:

• Content and Data Inventory, to clean data/ the cleansing of data and information;
• Its architecture (information modelling, content analysis, automatic classification and annotation/tagging);
• Data analysis in combination with text analysis (or NLP: natural language processing for the more abundant unstructured data, content), the latter to put flesh on the bone as it were, or adding meaning and context
• Information Governance: the process of being responsible for the collection, proper storage and use of important digital information (now made less ignorable with new citizen-centric data laws (GDPR) and the need for data agility or anonymization of data)
• Data/system Interoperability: which data formats, structures, and standards, are most appropriate for you? What data collections are most Relational databases, Linked/graph data, data lakes etc.?); 
• Language/cultural interoperability: letting people with different perspectives accessing the same information topics using their own terminology.
• Interoperability for the future also means being able to link everything in your business ecosystem for collaboration, in- and outbound conversations, endless innovation and sustainability.
• IoT or the Internet of Things is making the physical world digital and adding further to the interlinked network, soon to be superseded by the AoT (the analysis of things)
• Newer steps of Machine learning (learning about consumer preferences and behaviour etc.) and artificial intelligence (being able to provide seemingly impossible relevant information, clever decision-making and/or seamless user experience).

The fusion of technologies continues further as the lines between the physical, digital, and biological spheres with developments in immersive Internet, as with Augmented Reality (AR) and Virtual Reality (VR).

The next elements are here already: semantic (‘intelligent’) search, virtual assistants, robots, chat bots… with 5G around the corner to move more data, faster.

Progress within mobility paves the way for a more sustainable world for all of us (UN Sustainable Development), with a future based on participation. In emerging markets we are seeing giant leaps in societal change. Rural areas now have access to the vast human resources of knowledge to service innovation e.g. through free-access to Wikipedia on cheap mobile devices and Open Campuses. Gender equality with changed monetary and mobile financial practices and blockchain means to raise to the challenge with interoperability. We have to address the open paradigm (e.g Open Data) and the participation economy, building the next elements. Shared experience and information commons. This also falls back to the intertwingled digital workplace, and practices to move into new cloud based arenas.

Some last remarks on the telecom industry, it is loaded with acronyms and for laymen in the area sometimes a maze to navigate and to build some sensemaking.

So are these steps straightforward, or is the reality still a potential headache for your organisation? 

Contact Findwise now to ease the process, before your competitor does 😉
Fredric Landqvist research blog
Peter Voisey