Data Portability as a Network Model
What it takes, and the benefits that emerge
My post last week on the need to think differently about data portability got a lot of interest and good feedback; so let’s dig down a level or two.
There are multiple important points being made in that prior post; but for me the thing that most enables the new possibilities around data portability emerge when strong data management capabilities are built and run by data intermediaries on the side of the individual - on a fiduciary basis. So to be clear, that means the intermediary has a duty of loyalty to, and acts on behalf of, the individual.
In that mode, the ‘port’ is akin to ‘I’d just like a copy of my data please, for many purposes; or in fact just because I’d like to have a digital copy for my own records anyway’. And… ‘I want it in a useful format, rather an email, PDF or access to files in your portal or app all of which limit what I can do with my data’. In other words, it is not the same as ‘I consent for my open xxx data to be shared with this other party so that they can do something for me and others that my data enables’. That’s a valid model, but a small sub-set of the level of data portability i’m talking about.
Radical as that may seem, it in fact just returns people to the norm that existed pre the commercial Internet when we all kept a copy of our own records. Those records just showed up just as part of the normal transactions, usually in paper format, and were kept in a filing cabinet or similar.
In other words, commercial Internet has surreptitiously moved the digital records of a relationship between an individual or household and an organisation under the control of that organisation. How did that happen? And why was that allowed, by regulators, to become the norm? Very naive on reflection as they now try to fix that current very broken model that was created in plain view. Or it would have been if anyone actually read terms of service and privacy policies…
Anyway, let’s make that assumption that an individual could use something akin to their own supplier management system. So just as a CRM/ e-commerce enables organisations to run ‘one to many’ relationships from the same system and database, an individual/ household could run their own ‘one to many’ supplier relationship management tool. Nothing particularly complex about that really; CRM technology has been around since 1995 or so. It amounts to a database of identifiers for customers, prospects and maybe partners; user interfaces, processes and workflow support, communication tools, analytics and reporting. And now an overlay of AI and agents.
The tooling for ‘My Data’ management, or whatever the best term becomes, would have the same scope, in reverse. Individuals or households will have - a database of the organisations that they engage with, a dashboard, tools that support workflow and processes to get jobs done, the ability to communicate to and from; and analyses and reports. And then a sprinkling of AI and agents.
The key point that emerges when those tools exist on the side of the individual is that it makes them peers of organisations in the technical sense. In turn this ‘peer to peer’/ ‘many to many’ connectivity enables the collective migration to a network approach to managing these data connections rather than many silo-ed client server ones. So an any to any network, just like banking, telecommunications, credit cards and many others. Critically people do not need to know and understand the inner workings of a banking, credit or telecoms network to make a payment or a phone call. They just need to know how to join the network, connect to people and organisations, and send (data) communications.
In the technical sense this means that data portability becomes an access control model rather than a ‘move the data’ model.
The visual below shows multiple relevant data sources flowing into such a data intermediary - using Home Energy as just one use case of many. The same principles apply to the other smart data sectors, and then many more. In that model, data portability will be very straightforward; and nothing like as scary as it is now.
The best analogy that I’ve found so far for setting up these data connections is that they are a bit like setting up a direct debit in your bank account. In fact in many ways this data intermediary model is akin to treating data like we treat money in a current bank account. There is an overall ‘trust framework’ that we all understand even if we don’t need to know the details. Our chosen provider (data intermediary) manages data exchanges on behalf of people on that fiduciary basis. They keep an audit log (statement) of what came in, what went out, and the net position. And some regular exchanges can be semi-automated (those direct debits).
That data coming in from the various sources (including the individual entering for themselves) is blended, augmented and made available for onward sharing. The choice of data to be co-managed, comes from a deep ‘human-centric schema’; 7,000 or so attributes, all under the control of the individual. In effect the parties select from a menu of data templates to co-manage. Each template references commonly used data standards where relevant to aid inter-operability. Each of those many attributes has a logical ‘master source’.
Let’s dive into that Home Energy scenario as the means to illustrate what happens in practice; how that sector works at present is familiar to many of us.
Here is my own record of my Home Energy Supply. Ideally British Gas (my incumbent provider), or the comparison site I used to put that supply relationship in place, would push that data into my data intermediary. But they don’t as yet so I just fill in that template myself.
Going forward, to optimise my position around home energy supply, a number of anchor level ‘smart’ data connections and flows (pipelines) should be put in place:
The incumbent home energy provider should share usage data by fuel, tariff / contract details, standing charge, variable charges, billing amounts and annual forecast use in Kw/h by fuel. Reference data associated includes a unique property reference number and the associated full postal address. Interestingly, unlike the current model, the customer retains their prior home energy data when they change provider so they have a continuous flow of useful data irrespective of provider. And, they also have the option to pass that to future owners/ tenants of the property so that they can better understand the home energy context of the property prior to their own use. Neither is possible in the current model.
The associated Energy Meter Operator provides some key reference data; the meter numbers (the electricity meter number (MPAN) and the gas meter number (MPRN) and the detail on the meters that keep track of gas and electricity use.
Current account banking to reflect actual payments, direct debits and any credits. Ultimately these tools can help address the problematic debit and credit scenarios that seem to to be the norm in home energy. In these, there can be very large time and data gaps between usage, cost calculation and payment, making energy use and optimisation more difficult still to understand and optimise. Lot’s of innovation possible in this space.
Smart meter data, smart home (e.g. Hive) and further third party applications can be used to augment and drive fuel use data to more granular levels.
Automated comparison services should be in place to regularly check incumbent supplier/ tariff/ terms versus market availability and offers. I call that ‘Always on the Best Deal’; critically ‘best’ (i.e. optimisation) is defined by the individual/ household and goes well beyond just price comparison.
The screenshot below shows all of the above connection in a fiduciary data intermediary mobile app.
From the supply side perspective, that all might seem pretty scary. But once the shock subsides, the fastest movers who understand the depth of the change and react accordingly will do well. Critically they will find that these data pipes go two-way and not just one. So contact detail updates, ratings, customer service queries and many more data types can flow this way through trusted connections. Smart data channels will be the lowest cost for customer acquisition and retention. Feedback loops on product-customer fit the best available and most actionable. Customer and related data quality and utility will improve considerably, and compliance with privacy and data protection legislation will be much better and less costly than before. And they won’t have ‘big tech’ inserting themselves into these relationships.
This is more akin to ‘first party data’ and ‘retail media networks’ in that this model sees brands and their customers collaborating around the needs, wants and the product/ service provision that brought them together in the first place. Indeed it may well be the case that brands that already have a good level of trust amongt their customer bases could be deployers of the data intermediary model. They could not take the fiduciary role, but could do very well to much improve the flow of data within their particular business. This split reminds me of the distinction made by the Retail Distribution Review in UK Financial Services a decade or so back. In that regulation, financial advisers had to choose between being genuinely independent (and paid by the customer); or ‘tied’ to a large financial services provider and thus promoting only their product lines.
In either model data portability is vastly improved on the current model.
Next up…. smartreceipts as an enabler of data portability.