Information Answers

The Fox is Guarding The Personal Data Hen House (and he has weapons)

This week I watched the excellent documentary The Great Hack. A horrifying story, very well told; congratulations to all those involved in making that and bringing that story to the general public.

I’d recommend it to everyone, but most especially those in large private or public sector organisations sitting on large troves of personal data. The essence of the story is that:

the personal data asset class is now ‘more valuable than oil’
the vast majority of it is controlled by a small number of ‘for profit’, supra-national organisations
un-scrupulous actors can insert themselves into that eco-system and weaponise the personal data assets
the effects from them doing so are gigantic and world-changing
what they have done is only the tip of the iceberg

That’s pretty scary stuff. The key points made, in my view anyway, are that the products/ services that enable organisations to access and manipulate personal to achieve specific objectives are seen as weapons grade; and that we will see this kind of thing happen time and again unless something is done to change that.

So what can be done to change that? Not easily, not overnight; but it can be done.

Firstly, what won’t work, is regulating to stop it happening; that’s been tried already with GDPR. While regulating may slow down and lessen the effect, it does not address the underlying problem which is that huge volumes of the now weaponisable asset that is personal data sit with large, supra-national, for profit entities. For profits have to maximise the use of their own assets, so are not the right entities to build and guard that personal data hen house. The alignment of incentives is wrong in that model.

So we need to find a model where the alignment of incentives is strong and sustainable. I would contend that this is where the MyData model comes into its own. In that model:

The capability (for data management and selective, informed sharing) is built on the side to the individual. That is the game changer
Genuine propositions that seek to use personal data can still flourish; but dubious ones unable to persuade the individual of their merits in an open, transparent way will fail
The various incentives are aligned with the needs and wants of the individual

Looking beyond that immediate fox and hen house problem (which is big enough anyway); the MyData model is the only way that individuals will gain general control over their personal data, and not the faux control enabled by GDPR.

Lot’s to discuss then at the upcoming MyData conference in Helsinki, 25th, 26th, 27th September 19. See you there.

When will Privacy regulators tackle data access and data portability?

Just looking at the German Competition Authorities decision around Facebook and their interpretation of the use of Consent. That will have a big impact.

Whilst I’m no big fan of GDPR (overhype and under delivery so far versus what could have been), it does seem that by the time of the first anniversary of it going live that the regulation will be starting to show its teeth and have some real impact.

The problem with that is it will probably take a decade to deliver real improvement, and even that will only be on the ‘defence’ side of personal data capabilities. That is to say, a ten year to eliminate the bad stuff which just should not be happening.

So far the regulators seem to be ignoring the more enabling the ‘offence’, ie the more enabling aspects such as data access and data portability.

Of course one could argue that it is not the regulators job to build out positive capability on the side of the individual. I would argue otherwise; if more bandwidth was put on the positive side of what individuals could do with proper access to their data then a lot of the bad things would go away more quickly. Nodding towards data access and data portability and then doing nothing about clear failure to deliver helps no one;

Next Steps for Information Answers

I’ve not really known what to do with this site/ blog since the untimely death of my good friend and colleague John Butler. Until I do i’m going to use the blog/ twitter just as a place for my personal thoughts and sometimes rants about the personal data sector/ industry/ mess.

Opinions and rants will be entirely mine, nothing to do with my employers.

Thanks

Iain

Quantifying the ROI of Customer Engagement Planning

The internet of things (IoT) is generating Big Data and driving the need for business-ready analytics. But the explosion of marketing channels in which organizations are hoping to engage customers is expanding exponentially through mobile apps, social media and the emerging VRM Personal Cloud. CMOs and marketing departments are stretched thinner than ever to ensure enough perceived reach to drive sufficient customer engagement to sustain and grow their business.

The question becomes how to turn this exploding personal data eco-system to the advantage of the organization. With the customer “in charge” in so many real and virtual locations, how can an organization measure the return on its investment in the various channels so as to maximize marketing effectiveness and minimize wasted cost and effort?

Information Answers has been answering that question for major corporations for more than a decade using a sophisticated ROI mechanism that incorporates all the interdependencies, accounts for all costs across departments and tailors its output to the individual organization’s strategy and planning assumptions. Of course, there is a bit of work to input the necessary organizational information – such as planning assumptions – but it’s straightforward and the toolkit hides the complexity, allowing you to press a button and refine your plans or change course with ease.

With our updated proposition, we can work with firms to quantifiably derive the best case, worst case and most likely scenarios for ROI of customer engagement programs based on planned investments, progress and timing of each component and the anticipated progress of key milestones.

Too often, we find organizations suffering from too much information and subsequently double counting expected returns. Through the discipline and application of our updated Customer Engagement ROI Model – we can link marketing plans with finance’s budget, sales projections with current average revenue per customer and so forth.
Even more importantly, the toolset enables CMOs and CIOs to not only navigate the wealth of information but to safely conduct what-if scenarios so that they can:

• Preflight and refine existing propositions

• Identify, test and cost new proposition opportunities

• Assess the projected return on investment in sufficient detail

• And produce a project plan or product roadmap for deployment.

So, if you are serious – we mean really serious – about customer engagement that is, reaching and interacting with prospects, advocates and customers where they research, shop and buy – this toolset and our global expertise enables you to run test flight simulations before launching or scrambling to keep up in every channel. The outcome for you is informed planning, reduced risk, improved margins and growth by leveraging the huge amount of personal data in this new, customer-centric eco-system.

Don’t drown in the data, contact John Butler today for a free consultation and demonstration of how we can help you!

John Butler

Information Answers

john@informationanswers.com

+1 (201) 600-8962

Imagine a World Where Opportunity Knocks and Your Door is Open

By John Butler —

Marketing has long yearned for a step change from being limited to a sales support function such as generating leads for sales and providing distilled research as analytics to improve reach and drive customer engagement.

And rightly so. Marketing yearns to serve the role it was designed for – and that is to be the pivotal strategic guide for the organization. Other departments can improve the bottom line by ensuring revenue exceeds cost, but it is Marketing’s purpose to increase profitability by focusing the organization – including sales – on the most profitable prospects and retaining the most profitable customers. Marketing knows that the only real boss is a paying customer.

So, how can Marketing focus an organization when it is anchored by its legacy role? How can Marketing focus an organization when it is drowning in so many new digital channels – channels that change over time like Myspace to Facebook? It’s juggling Internet ads, email campaigns, more and more mobile apps, and an explosion in social media, all the while weaning off traditional media – which is really about weaning off the model of broadcast approaches in favor of more direct methods simply because digital is more direct than print or airwaves. It was a CMO that told me candidly, at best it’s “spray and pray.”

But again, how can Marketing focus an organization in the Age of the Customer – where customer feedback is more telling than a compelling campaign? How can Marketing focus an organization when the Internet of Things is driving Big Data – giving everyone either data indigestion or slick doughnut charts about aggregate groups far, far away from 1:1 customer intimacy. How many organizations do you know that hope to gain more customer intimacy by hiring a data scientist?

How can Marketing focus an organization when the tools available from the major enterprise software companies are a patchwork quilt of acquisitions by its vendors – a confusing collections of tools – neatly connected in architectural slides and designed to automate a current state, that is, apps that help do everything faster and cheaper but without clear sight of effectiveness.

Imagine a world where Marketing could automatically reach, engage, acquire and retain buyers. Imagine a world where Marketing was directly linked – directly connected – to customers and their needs and wants. Imagine a world where Marketing could focus an organization on acquiring the most profitable prospects and retaining the most profitable customers.

In a world of shiny objects, it is easy to be seduced by the promise of the future. Drones ready to deliver packages that contain items that Amazon anticipates you’ll purchase – a statistical gamble that may well be financially worth the cost, time will tell. Cloud apps that let you run your business on your phone with a swipe of the finger. Marketing Automation that connects everything in the enterprise, ahem, to give you the 360 degree, single view of the customer so that you can cross-sell, upsell and survey – better, faster and cheaper.

Thanks to Apple individuals can now pay with a phone, but imagine a world where active buyers could use their smartphones to handshake with company systems to obtain the best deals and through seamless interactions over time become loyal advocates because the organization is systemically attuned to their needs and wants. Imagine a world where active buyers – “smart-enabled” buyers – were more than just a voice, as in Voice of the Customer, but were actually helping Marketing steer the organization, focusing it on acquiring the most profitable prospects and retaining the most profitable customers.

In that new world – where Marketing is strategically positioned and leveraged – new tools and models are required, some yet to be invented. The good news is that the foundation has been laid and the visionaries have shown the way (just search YouTube for Doc Searls or Drummond Reed or read Customer’s New Voice by John McKean). Smartphones have given individuals the equivalent computing power of an employee using a CRM system. The rapid adoption of Public and Private Clouds has given rise to the Personal Cloud – a structured and secure lockbox of personal information. And we all know about the data breaches suffered by retailers and celebrities so, there are engineers hard at work at securing the network – our beloved Internet needs a security patch (see XDI).

So, the individual has the computing power, the data and the secure connection. What can they do with it? Where is their equivalent of CRM? Why do individuals have to be hassled by unsolicited emails, spooky ads in web pages simply derived from their ad hoc browser history, unwanted advertising interruptions to their online experiences, freemium trial apps loaded with annoying ads that eventually require some attention and evaluation before deciding to purchase the premium, ad-free app? You get the idea, after all, we are all living it and can all cite bountiful examples.

Imagine a way to leverage that data and power in the hands of 2 billion smartphone and tablet users in a win-win scenario – a win for the organization and a win for the individual. Imagine an individual dashboard that provided summaries of buying history with drill down to the receipts, warranties and terms and conditions – you can almost hear the savings in customer support costs.

Now, imagine that dashboard also showed activity conducted automatically based on an individual’s intent to purchase that identified the best deals on insurance, cars, homes, etc. Imagine the individual – through their intent cast – gaining sight of the optimal deal with a supplier that they didn’t even know existed and then selecting that supplier based on a respected connection and a trust contract. Customers need a home or car but what they really want is: Save me money, give me more precious time back, avoid hassles and exceed my expectations when using or maintaining your product or service.

That world is unfolding rapidly. Through Personal Cloud, customers are gaining VRM power. VRM or vendor relationship management gives individuals the equivalent power of an enterprise CRM user. Organizations that enable customer VRM connections to their CRM system through trusted handshake protocols (APIs) are able to compete in a way that the hamster in the social media wheel could never achieve no matter how fast they can make that wheel spin.

We’re not talking science fiction. Not at all. In fact, we’re offering to walk you through real-world examples and help you envision ways to leapfrog the competition using your existing instance of Salesforce.com or other Marketing Cloud to connect directly to Personal Clouds – directly to active buyers ready to spend money. If you want to understand the implications of this new personal data eco-system or you want to know how much it will cost to assess the ROI, we have the tools, experience, expertise and thought leaders to show you and help you lead the way in your organization. Beyond that, we can build prototypes of your CRM connecting to Personal Cloud apps or devices – and transfer that know-how to within your organization.

Contact John Butler, U.S. lead for Information Answers that connects VRM personal clouds to CRM as a Salesforce.com consulting partner and Respect Network integration partner.

Why Personal Clouds and Midata are Good for Business

I’ve long been an advocate of Craig Burton’s thesis that ‘VRM’ and the inevitable shift towards ‘personal clouds’ will be good for the organisations. His excellent overview here includes some real gems, not least ‘Baking core competency in an API-set is an economic imperative’.

And i’ve also noted the slow pace of the UK.gov Midata programme aimed at helping individuals gain access to the data held on them by their suppliers in a form that they can re-use. It is clear that the majority of organisations are not exactly rushing to deliver on that, one assumes because they perceive much more threat than opportunity in doing so. I don’t see that changing in the immediate future, and note that many are now focused on how they can deliver Midata, still within their own context. The back-stop legislation being proposed is unlikely to change that stance. Similar initiatives elsewhere will probably run on similar lines, although USA probably has a strong approach in working with semi-public sector data managers whose hand can be more pro-actively forced.

Given that, i’ve tried to set out below a view on why taking a more pro-active stance on Midata would be a good thing for organisations, and merging that with some thoughts on how this will enable that focus on core competencies, and what that will look like in practical deployment terms.

I’ll do so using visualisations of a ‘CRM’ data record; how that is supposed to look, how it usually does look in practice, and what it will look like as the above scenarios deliver in the mid term.

The first visual below shows a theoretical view of what a customer record would look like in the data warehouse sitting behind the customer management systems of pretty much any large business to consumer organisation – from bank, to retail, to utility, to public sector and health provider. Having this in place allows the organisation to run all of the customer management processes they want, to a high standard. The main building blocks of the record are The Customer, The Product/ Service, The Outlet (sales channel), The Relationship between Customer and Product, The Offer (being made to the customer/ potential customer), and The Customer-Organisation Interaction(s). Each sector will have minor (10%) nuances around the detail, and differing terminology in places, but the big building blocks remain the same.

However, there’s a problem……

The second visual (built up from many deep dive assessments) is more illustrative of the reality, the colours being driven, in traffic light style, by data quality, which includes whether it exists in the system at all, along with other classic data quality metrics such as recency/ source of update, completeness, compliance etc.

To avoid too much time analysing the detail – the short version is that many organisations are running their customer management processes on very poor quality fuel.

So what’s going to happen to change that; because the above has been the case for the last 20 years?

The short answer is Personal Clouds (aka Personal Data Services). These will enable the individual to take on a significant chunk of the data management task, and be happy to do so because they will benefit hugely from doing so. Many people will only be vaguely aware that they even have such a thing; the personal cloud(s) will be just a small component of a wider proposition, like a SIM card is to a phone. The recently launched Cheap Energy Club is a good example of the above – a mini personal cloud buried within a much more compelling customer and supplier proposition.

The third visual below is a stab at how the customer record, as we know it now, will change over time. What i’m suggesting is that the significant majority of the customer record will actually be managed by the customer. And that this customer managed portion will itself sub-divide into My Data* (volunteered personal information brought together in a personal cloud by the individual), and Our Data** (co-created/ co-owned data currently managed by the organisation and, over time increasingly made available to the individual).

* For more on this provenance based categorisation of the data around in individual see this post from a few years back covering My Data, Your Data, Our Data, Their Data and Everybody’s Data.

** Confusingly what i’m calling Our Data, UK.gov calls ‘Midata‘. My Data and Midata should not be confused; the former I don’t need to retrieve from somewhere, it’s mine in the first place..

Firstly, there will be huge chunks of cost taken out of current customer information management activity. Many organisations spend tens or hundreds of millions of pounds per year managing customer information.

Secondly, data (fuel) quality will be much improved, enabling the option to run much more efficient and effective customer management processes – across all aspects of the customer lifecycle. To bring this to life, this becomes the mythical ‘360 degree view of the customer’; i.e. the customer has data from across their supply base, not just the single organisational silo view that is the current fuel.

Thirdly – look at what’s left for the organisation to manage…, the data about their products/ services, their outlets (channels), their product/ service offers, and their marketing campaigns. i.e. their core competencies. That’s a scary but ultimately winning proposition for organisations – ‘give up control of something that you value highly but has a high degree of toxicity (customer data), in order to focus much more on that which you do best’.

To round that off, and return to the core point from Craig, we have a fourth visual. The API’s….Each of those three buckets of data thrive on being connected to each other in secure ways, much more so than they do when they are combined. And thrive further still when ‘apps’ and utilities can be pointed at then, or used to bridge them.

If these API’s are designed and deployed well, then the personal data eco-system thrives, and the individual genuinely becomes the point of integration and origination for data about them. In turn, this architecture is also the only really viable one for ‘The Internet of My Things’, which will further turbo-charge the individual and their personal data capabilities.

There’s much more to write on this, including which ‘apps’ are on their way, and how organisations can enable their processes in this way. I’ll save that for another day.

The First Large Scale CRM Plus VRM Business?

Nice to see Cheap Energy Club from MoneySavingExpert make it out the door, having worked on that for a big chunk of last year.

At first glance it might look like another comparison site, but there’s lots more under the hood – data built on the individual side, automated checking, mi-data ready, and a few more interesting bells and whistles….

Will this be the first service built somewhere between CRM and VRM to run at large scale? It certainly has the possibility to do so; I saved £135 per year on my switch, and others much more. And MoneySavingExpert have a big subscriber base of people who trust their advice.

No doubt this will be a story to follow up on….

A CRM plus VRM Venn for 2013

I spent most of 2012 with head down consulting on a couple of big ‘CRM plus VRM’ propositions – more on those when they show up in the wild. So i’ve been pondering on where to focus on in 2013.

I put together this Venn diagram to help think through which areas of our work might reach tipping point in 2013. It looks at the intersection between our three areas of interest – CRM, VRM and Personal Data Services.

The key points I took out from sketching this out were:

1) As an overall theme, I think 2013 will be the year that large organisations with lots of individuals as customers will wake up to the option to build rich, data-driven propositions around volunteered personal information. Critically, this data will being plumbed directly into existing operational CRM systems from ‘something outside’ (whether that be a personal data service, personal cloud, ‘midata’ or some variant thereof) ; Yes CRM plus VRM for real, and built for large scale. The UK midata project, and equivalents elsewhere, will help in that, although more as the spur that makes organisations think about the issue and build their own propositions with the data they hold than about data actually flowing anything like freely.

2) Whilst many/ all of the items on the venn are on their way to a tipping point, some are more ready than others.

3) Offers management, a perhaps obscure, behind the scenes/ yet to really emerge function, will see significant change this year. The current modus operandi of ‘get a contact point and some input data and push offers to it’ has largely run out of road in many key sectors and demographics. The critical aspect of making this happen is that it requires work from both demand and supply sides, i.e. both buyers and sellers. Without both acting together we just get what we have now. We’ll see a number of ways in which I can pull relevant offers via a channel of my choice emerge in the first half of this year, and if well implemented, get momentum in the second half.

4) VRM/ Personal Data Service Hardware. One can get so far with software, but when one adds genuine customer-side hardware to the mix then we get a lot further. So look out for prototypes and then products in that space.

So that’s my target for the year – a hardware device that pulls in offers that I have personalised. No doubt it will tackle some other VRM issues along the way.

Anyone else want one?

Iain

A Classy Way to Go…

The 31st of July marked the end of my favourite online transaction manager service – Wesabe (www.wesabe.com).

I’ve been using the service regularly for the last few years. I did not rely on it, just liked quite a lot about it, such as that:

– It moved financial transaction data from the supplier side to the individual side, and allowed a whole set of tagging and reporting options

– It thus allowed the individual to build a more complete view of their finances than available anywhere else

– It offered a range of security options around the data movement, to suit individual preferences

– It enabled data portability from the start

Unfortunately this last point proved key, because Wesabe announced that they had to shut up shop; I guess the business was not financially viable (yes, that is somewhat ironic….). The viability of genuinely individual-centric internet businesses is a post for another day, but it was the way that Wesabe managed the shut down that impressed:

The key features of the shut down that I think were handled well were:

– Communication, users were given plenty of advance warning; none of this ‘here one day and gone the next’

– Export options, yes that built-in data portability came into it’s own, a range of competitors emerged with ‘import your wesabe’ data propositions to ease the service transition pain

– Enabling and encouraging an open source project to emerge from the ashes

– Complete deletion of data after closure; how many times have we seen the customer list treated as an asset that can be sold off to the highest bidder?

So, Marc et al at Wesabe; thanks for the service and the learnings while it lasted; and thanks for such a classy shut down; and good luck with your next venture.

Filling in the Empty Space – The Personal Data Store

I said here that at present there are very few genuine VRM tools available right for use right now, and that the main reason for that is that the underlying plumbing is not yet in place at any kind of scale.

By ‘plumbing’, I mean that ‘personal data stores’ and all that they imply are not as yet deployed en masse, or with any degree of robust functionality.

Before we get into what it will take to change that, let’s take a look at what I mean by the term ‘personal data store’, because obviously that is open to interpretation, and indeed this has been the subject of much debate in the Project VRM community. To get to the heart of that, I think it is useful to draw a parallel to the deployment of data warehouses within organisations, a process which began some 30 years back, and continues to evolve and extend today. The raison d’etre for a data warehouse within an organisation is normally to pull together the data from multiple operational sources (silo’s), organise that data, enhance it and make it available for use – whether that be for analysis within the warehouse, or via applications that will tap into it. Pulling data in from multiple operational systems is the key, because what is being acknowledged is that no one operational system can pull together a data set that is sufficiently rich, deep and broad to enable all of the functions required to run the organisation. That is to say, we need to distinguish between systems that are there to fulfill a specific task (an operational system such as a CRM application, an ERP instance, or a web site), and those whose main purpose is to generate knowledge, enable understanding and enable sharing information built across multiple business functions.

A further defining characteristic of the data warehouse is that it runs on ‘atomic level’ data, that is to say data that is stored at the lowest level of detail available from the feeder system (e.g. line item of a receipt). When data is stored in this way, it can be aggregated and summarised where appropriate or necessary for use. This then enables a further defining characteristic of a data warehouse….that one cannot predict in advance all of the uses to which the data might be put which storing at an aggregated level would limit. The same will apply in the personal data store.

So what else is involved in data warehousing that might inform our thinking about personal data stores?

Firstly, i’d suggest there is a (mainly manual) ‘discovery’ phase in both that is about identifying and engaging with valid data sources (i.e. inputs to the store). In practice the data to be sourced is driven by the prioritised functionality sought by the user. For example, if my main purpose for the personal data store is to help me manage my health, clearly i’m going to need my health and my health care supplier data, or links to it, in the store.

Next, we need to consider the personal equivalent of the ETL processes and tools deployed in data warehouses; ETL is short for Extract, Transform and Load. In recognising the likely need for ETL equivalents, we imply that:

a) the personal data store will have its own target data schema (design), with greater of lesser degrees of flexibility built in dependent on technical choices. I think there will necessarily be open standards around personal data store design. That’s not the case in the data warehousing world (Oracle, SAP, Teradata, IBM are all largely proprietary), but I don’t think that approach is sustainable for the personal variant which needs to run at greater scale and much lower cost.

b) most/ all of the data sources will not hold data in precisely the same format/ design as the target data schema.

Extract, Transform and Load usually consists a set up phase, and then automation; many ETL tools exist in the data warehouse world and it is reasonable to assume that the same will emerge in the individual space (indeed they already are tactically with data exchange formats like OFX) in the banking world for moving transaction data around. Note that ETL may only be a precursor to a direct feed from a source system into the warehouse, whether they be batch, trickle or real time feeds.

Now that we have data in the warehouse/ store the task lies in organising the data and preparing it for use; there are a range of technology candidates in this area from standard RDBMS to NoSQL databases. At this point, it may be worth diverting briefly to a harsh reality, because it is pretty certain that this same reality will apply within personal data stores. This reality is that many data warehouses actually become ‘digital dumping grounds’ into which data is put ‘in case we need it later’ (note the clash with data minimisation principles in privacy law), and/ or it is not organised/ optimised for use. That does not make them a complete waste of time necessarily, it just means that they are not providing maximum value; ……the well worn phrase ‘Garbage In, Garbage Out’ springs to mind. My colleague John McKean tells this story much more eloquently in his first book, The Information Masters, which dates back to 1999 but is as valid today as it was back then. His research amongst the 30 or so ‘Information Master’ organisations sets out what differentiates the tiny percentage of organisations that get mega-returns on their information investments, versus those that just plod along or suffer regular failure to get a return on investment (hint….the master’s don’t regard the issue as something that ‘the IT folks do’).

The further functions of the data warehouse/ personal data store beyond getting data in, and organising it are:

– Data maintenance, i.e. refreshing data as appropriate, and having processes to keep it up to date, whether that be static data, dynamic data, or reference data.

– Data enhancement, either through combining existing data via queries into new attributes or meta data, or by bringing in further external data (e.g. my credit rating or verification via a third party that a data attribute is accurate at that point in time, or otherwise). This verification piece is a key issue, if I can prove for example that I am a gold level flyer on British Airways, or that i’ve not had any speeding tickets in the last 5 years, or that I do have a specific illness to manage then that ultimately takes a vast amount of guesswork and waste out of the current modus operandi.

– Make available for use; i.e. providing a data access layer that enables the data to flow onward to those entitled to it, in the way that they wish to receive it.

– Archive, there comes a time in the life-cycle of a data attribute, that it is no longer useful. This situation, which will certainly apply in a personal data store, can lead the database manager to either physically move the data elsewhere/ onto back up media (usually after building summary histories that do remain), or just leave it within the warehouse on the basis that storage cost may be less than removal costs.

Two other aspects of data warehousing are probably worth noting

– whilst initially, a data warehouse was most likely to be a single computer (perhaps costing £1m upwards to buy and install), these days the concept of a virtual warehouse is also a perfectly viable option, with data stored physically in different places and brought together as and when required.

– the concept of a data mart has emerged, which means the carving off of a specific set of data to support a subsidiary warehouse tuned to particular task (e.g. a retailer may choose to set up a mart for the team managing the loyalty scheme). Typically the link to the main warehouse remains in place for maintenance and update purposes, but the mart acts more independently in terms of access and use.

So what does all of that mean for the ‘personal data store’ then?

Firstly, I would contend that there is a terminology point to be taken on-board. The data warehouse is a short, fairly well understood term (perhaps because it is 30 years old). But it actually covers a lot of ground, and is much more than just a storage facility. It covers ‘identify relevant data types and sources, enable processes for bringing that into the storage facility, keep it clean and up to date by looking back to the source and other other cross-reference files, aggregate and summarise data where appropriate, enhance and add meta data where useful, and make available for use in a controlled, auditable manner via a range of output mechanisms and formats. That’s a lot functionality to pack into two words….. I think that a personal data store will do pretty much all of those same functions, so the users of the term should ideally aligned with that description, or seek to agree different terms for each of the system components and functions.

Secondly, there should be a recognition that functionality will continue to emerge and evolve over time, rather than all turn up in one big bang deployment.That said, there is clearly a huge upside to deploying with the technology we have available now, than that of 30 years ago. Cost of storage and back up is very low, connectivity is solid, access routes/ devices are many and the range of things that will be enabled by them using the internet/ mobile internet as the main place where this user managed information will be deployed.

Third, my working assumption is that there will be both self managed, and hosted options and that people will chose the options that best suit them and their likely uses. It is probable that stand alone personal data stores might not be that common as the market evolves, and indeed the individual buys into a wider set of personal information management capabilities (e.g. a personal data store, a set of key applications, and a hosting/ back up service).

So, after all that, here’s my working definition of a personal data store:

A personal data store helps me gather, manage, enhance and use information from across multiple aspects of my life, and share that information under my control with other individuals, organisations, or with applications or subsidiary data stores that I wish to enable.

The key, as per above, that this is a multi-life aspect data management platform that is infinitely extensible, and not constrained by the need to operate within a silo-ed context.

Here’s a diagram that seeks to illustrate the personal data store that I think will emerge over time.

Personal Data Store Overview by iainh1

One of the big issues around data warehousing is ‘the business case’ for what is typically regarded as a behind the scenes, not very sexy investment. I think the same will apply to the personal data store, but i’ll save that post for another day…