One of the key points that overlaps between Data Protection and Information Quality is where he tells us that

Data is the pollution problem of the Information Age.  It stays around, it has to dealt with and its secondary uses are what concerns us. Just as… … we look back at the the beginning of the previous century and sort of marvel at how the titans of industry in the rush to build the industrial age would ignore pollution, I think… … we will be judged by our grandchildren and great-grandchildren by how well we dealt with data, with individuals and their relationships to their data, in the information society.

This echoes the Peter Drucker comment that I reference constantly in talks and with clients of my company where Drucker said that

So far, for 50 years, the information revolution has centered on data—their collection, storage, transmission, analysis, and presentation. It has centered on the “T” in IT.  The next information revolution asks, what is the MEANING of information, and what is its PURPOSE?

Bruce raises a number of other great points, such as how as a species we haven’t adapted to what is technically possible and the complexity of control is the challenge for the individual, with younger people having to make increasingly complex and informed decisions about their privacy and what data they put where and why (back to meaning and purpose).

I really like his points on the legal economics of Information and Data. In college I really enjoyed my “Economics of Law” courses and I tend to look at legalistic problems through an economic prism (after all, the law is just another balancing mechanism for human conduct). I like them so much I’m going to park my thoughts on them for another post.

But, to return to Bruce’s point that Data is the pollution problem of the Information age, I believe that that statement is horribly true whether we consider data privacy/protection or Information Quality. How much of the crud data that clutters up organisations and sucks resources away from the bottom line is essentially the toxic slag of inefficient and “environmentally unfriendly” processes and business models? How much of that toxic waste is being buried and ignored rather than cleaned up or disposed of with care?

Is Information Quality Management a “Green” industry flying under a different flag?

Unfortunately the partner organisation seemed to lack an understanding of the what’s, why’s, when’s, and how’s of their data. This was perplexing as, nice and all as a blank canvas is, sometimes you need to have a sense of the landscape to draw your conclusions against.
The engagement I had from the partner organisation was focussed on their need to be able to take certain steps if certain circumstances came to pass. While the focus on the goal was commendable, it served to generate tunnel vision on the part of the partner that put a significantly valuable project at risk.
Goals and objectives (why) are all well and good. But Knowledge Workers need to be able to link these to processes (how) and information needs (what). Deming famously said that if you can’t describe what you are doing as a process then you don’t know what you are doing. I’d go further and say that if you can’t identify the data and information you need to do what you are doing then you can’t be doing it- at least not without massively increased costs and risks (particularly of non-compliance with regulations).
In the end I made some assumptions about the what’s and how’s of the partner organisation’s processes in order to meet the goal that they had focussed on so narrowly.
That enabled me to map out an approach to data protection compliance based on a “minimum necessary” principle. And that got my client and their partner over the hump.
But, from an information quality perspective, not being able to answer the why/why/how questions means you can’t set meaningful measures of “fitness for purpose”. If you don’t know what facts are needed you don’t know if information is missing. if you don’t know what use data will be put to you can’t possibly tell if it is accurate enough.

So, both Data Protection and Information Quality require people to know the what/why/how questions about their information to allow any meaningful outcome to ensue. If you can’t answer those questions you simply cannot be doing business.
To paraphrase Deming – we need to work on our processes, not their outcome.

• Complying with EU Data Protection regulations
• Ensuring Data Migrations actually succeed
• Enabling timely reporting of Regulatory risks

My mantra in these contexts seems to be distilling down to two bald statements:

• It’s the Information, Stupid.
• Profile early, profile often.

But what do I mean by “Data Profiling”? For the purposes of these conversations, I defined “Data Profiling” as being the analysis of the structure and content of  a data set against some pre-defined business rules and expectations. For example, we may want to know how many (or what percentage) of records in a data set are missing key data, or how many have inconsistencies in the data, or how many potential duplicates  there are in the data.

Why is this of benefit? While a journey of a 1000 miles starts with a single step, that journey must start from somewhere and be headed somewhere. The destination is encapsulated in the expected business rule outcomes and expectations. These outcomes and expectations are often defined by external factors such as Regulatory requirements (e.g. the need to keep information up to date under EU Data Protection principles, or the need to track bank accounts of minors in AML processes) or the strategic objectives of the organisation. The starting point is, therefore, a snapshot of how close you are (or how far you are) from your destination.

In my conversations, I advised people (none of whom were overly familiar with Information Quality principles or tools) that they should consider investing in a tool that allows them to build and edit and maintain Data Profiling rules and run them automatically. Regular Information Quality geeks will probably guess that the next thing I told them was about  how the profile snapshots could provide a very clear dashboard of how things are in the State of Data in their organisations.

Just as, when we are embarking on our journey of 1000 miles, it makes sense for us to regularly check our map against the landmarks to make sure we are heading in the right direction. The alternative is to meander down cul de sacs and dead end trails. Which equates in Information Management terms to wasted investment and scrap and rework. So, profile early and profile often seems to be a good philosophy to live by.

By applying  business rules that relate to your regulatory compliance, risk management, or data migration objectives, you can make Information Quality directly relevant to the goals of the organisation, increasing the likelihood of any changes you bring in becoming “part of the way things get done around here” rather than “yet another darned thing we have to do”.  Quality for the sake of quality was a luxury even in the pre-recession period. In today’s economy it is more important than ever to demonstrate clear value.

And that is the real profoundity of profiling. Without it you can’t actually know the true value of your Information Asset or determine if your current course of action might turn your Asset into a Liability.

It’s the Information, Stupid. So Profile Early and Profile Often.

Visit the radio station website (NewsTalk.ie, tell them your name, your address, your email address, your 3 favourite bands and your favourite foods and a piece of plastic featuring a picture of the host will wend its way to your door.

Simple.

At least it is unless you step back and think about the process from the point of view of Data Protection principles.

Personal data must be obtained and processed fairly for specific purposes. What are the purposes for which NewsTalk wants my personal data? If it is just to send me a card then we walk right into another issue – information gathered should not be excessive to that purpose.

So, if you are just sending me a card, why do you need to know my music and food preferences?

Sensitive personal data, such as data pertaining to medical conditions or political beliefs or ethnic origins is treated with more seriousness under the Data Protection Act. So, depending on the responses to those questions about music and favourite foods, sensitive personal data could be being processed.

The explanation of the loyalty card scheme that is on the NewsTalk website is great and in keeping with the light hearted nature of Tom’s show. However it doesn’t go far enough in explaining or setting out the purposes for which the data is being captured.

Other issues arise as a result of processing personal data via a website, such as the legal requirement to have a privacy policy displayed on the site and the data protection requirements of keeping the data safe and secure and only keeping it for as long as it is needed for the specified purpose. I’ll explore these in later posts.

It is all too easy to fall foul of the simple rules that exist to ensure trust and transparency in how personal data can be processed. Prior planning can ensure that Compliance is an enabler of business and customer interaction rather than a nagging fear of being caught dragging at your actions.

Taking out your Nudie Pen and mapping out what your information objectives, purposes, etc. are (see this tutorial on my company website for an example) is time well spent to make sure you aren’t creating a rod to beat yourself with. Using your Nudie pen to sign up for some Data Protection Training (such as that offered by the Irish Computer Society or my company) would also be a worthwhile step, particularly given the Data Protection Commissioner’s recent findings on the need for the management teams in businesses to be aware of the Data Protection implications of their actions.

The fun part for me of any new mobile phone purchase is playing with the new toy  tool and seeing what it can do that my old one couldn’t. For example, back in the 1990s when I did my first upgrade from my first mobile phone (an ericsson model so old that I actually can’t find it referenced on the internet), I found that the new phone was so much smaller and lighter I was actually able to carry it around.

The irritation I have is when it comes to moving my contacts and synchronising with my various other technologies that hold contact details (laptop, gmail, company address book). Inevitably I wind up with duplication and triplication of contacts. I thought I had the problem licked on the iphone though as there are a number of apps available for managing contact details and reducing duplicates.

However, having spent a few days using them I am unimpressed as they seem to be making a the traditional rookie mistake in de-duping records – assuming that name matching is enough.

My brother and father share a given name and a family name. They have different middle initials, different addresses, different phone numbers, different email addresses (all the stuff that you would have in a contact record on your phone). Each application I tried decided that they were a duplicate entry and merged the records. This was annoying.

In other cases, I have duplicate entries with varying degrees of record completeness. For example, my friend Cathal exists at least 4 times, with one entry having most of his contact details,  with spurious email addresses or social networking nicknames in the others.  The “data quality tool” very kindly merged all the records into the entry that had the least amount of data, and deleting the other records.

Right now I’m considering firing up talend, datanomic, or informatica tools to dedupe a dump from my iphone and reload it to the phone, and then hopefully that will cascade through the rest of my data stores when I synchronise.

But I’ll need to draw a data flow map of all of that to make sure.

Grrrrhhh.

So. If the existing tools for data quality on the iphone are not up to the jobs, what is missing? The good news is that the data sets are fairly clearly structured (once they get into the iphone), so that is less of a concern than the actual processing of matching and consolidation of records.

1. Probability scoring across multiple fields would be nice. If two people have the same name but significantly different contact details then it is very probable they are not the same person. A corollary – if there are two records with the same name and one has contact information and the other record has only a name, chances are they are duplicates.
2. Presentation of matches for review. While the machine can make good guesses where the name and contact details are the same, where there is confusion, the matches should be flagged for a review by the phone user (the “Data Controller”). This way we can avoid having to unpick erroneous matches.
3. Merging of records should be done on a more structured basis, with mapping of fields being user-customisable based on a standard template. I despair of important contact information being dumped into a notes field (it reminds me too much of when I had to try and migrate data out of a Siebel call centre system a few years ago).
4. The matching should be able to cater for multi-lingual input (as phones don’t all live and work in english speaking lands).

There may be other requirements that I am not thinking of here at the moment, but those 4 are a starting point. Perhaps an obliging Data Quality tool vendor will develop an iphone app to a web service for matching contact records.

Personally, I think that having such a service available would help raise awareness of the value of quality non-duplicated contact information to individuals and to organisations.  However, the app on its own isn’t enough as the average smart-phone user may have personal information held in a variety of places and, just like in a large enterprise with lots of data stores, creating a “Single View of Contact” will require you to understand the flow of your contact information around your tools (i.e. does the phone update the laptop and does the laptop synch to google apps and does google apps synch to the phone?) to avoid the cleanup work being undone the next time you plug your phone into your PC.

Information Quality Management poses challenges for the enterprise, but can also create friction for the individual trying to manage something as simple as a list of contacts across multiple information stores.

Do we have an app for that?

The estimated duration of the job was to be about 45 minutes to an hour to hang three fittings. The first two fittings went up in about 20 minutes. The final one, that took us about 4 hours (and as of this morning still isn’t finished. We hadn’t factored on the “creativity” of the electricians who installed the original wiring.

When we opened up the existing light fitting in the living room we were faced with a spaghetti junction of cables. When we wired them into the new light fitting, the light went on but the switch wasn’t controlling it. It seemed we’d wired the light into a loop going somewhere else. We were faced with 5 live wires which had been going into 4 connectors on a connector block. So we had to then test each of the possible live/neutral combinations in turn to find the ones that actually related to the switch (which necessitated our handyman/neighbour having to play with live 240 volt electricity, which is never a good idea).

When we traced the correct cable pair I did a very simple thing. I dug out my label maker and put a label on the cables that related to the lighting circuit in that room. It struck me that that 30 seconds of effort was something that the electrician who wired the house could have easily done when they were installing the cables, making life simpler for him (or her) and for anyone who came after.

We wired everything up and fitted it up for a quick test before finishing the job. I turned the power back on.

Then there was a loud bang and the power went out.

It turned out that there was a break in the live wire we’d just labelled (the important one for the task at hand) slightly further up the cable from where the label was which had pierced through the insulation and come into contact with the metal mounting plate for the light fitting.

As a result, the magic smoke had escaped from the circuit breaker and the light switch.

What had ensued for my neighbourhood handyman and I was instead frustration as  a task which should have taken a half hour stretching into nearly six hours (over 2 days) and additional expense (to the handyman) in replacing the blown components.

To put it another way, for the want of €0.15 of labelling on the part of the original vendor to identify the attributes of the various wires we found (such as “this one runs the lights”), I expended a full half-day of work and the handyman was unavailable for other jobs which would have paid him a lot more than the rate we’d struck for fitting the lights – and that was before the additional cost and complication of having to go to the electrical wholesalers this morning to buy replacement parts and fit them as well.

It struck me that this is a situation we encounter on a regular basis with the information assets of an organisation.

Very often the important data for a given process in a given area is not clearly identified. Management say “give us everything and we’ll figure it out” and call centre screens and web-forms are cluttered with a variety of information capture points.

A failure to understand (or label) the purpose of that information, where it comes from and where it goes to, and its critical path in the business can result in undesired outcomes as soon as anything starts to change in the business, business processes, or technology platform (such as replacing your front end systems with a new one, the nearest analogy I can think of for changing a light fitting).

This results in expended effort on scrap and rework trying to get the blasted thing to work right with the desired outcomes (such as throwing illumination on a problem), and quite often can result in a critical information path way being blown and needing replacement or an internal control process in the business stopping a process.

Of course, things can often be worse in the Information Quality space where the internal controls on quality may not function as efficiently as a circuit breaker and a light switch which have planned failure built in to them to isolate the end user from the dangers of domestic electricity supply. When controls like circuit breakers fail, the results can be… shocking.

Sometimes it is the simplest things that are important, such as knowing what wires relate to the circuit you are fitting a light into, or what items of information are actually critical to the success or failure of a process (both the immediate process and down stream -remember  there were 4 other live wires relating to other circuits that had to be dealt with as well) is a key contributor to the success or failure of any change effort.

What controls do you have to protect your business knowledge workers from the dangers of a high voltage low quality information? Are the mission critical data in your organisation clearly labelled?

I found this on http://www.motivatedphotos.com and it struck me that it is a wonderful metaphor for data integration, information quality, and data governance in many organisations where they are reacting to issues, sustaining silos, or viewing all of this as an IT issue rather than a business challenge, or trying to solve the challenge with series of fragmented department level initiatives.

Thoughts?

I give you “DATA” by Derek and the Dominoes.

What will you do when you get data

Loaded into your new BI?

You’ve been running reports

that don’t make sense for too long

but you can’t blame your poor BI.

Data, you’ve got me on my knees

Data, I’m begging darlin’ please.

Data, darlin’ won’t you ease my worried mind.

I tried to get some information.

But the data lets me down.

Like a fool, I fell in love with you,

But the duff  data turns my whole world upside down

Data, you’ve got me on my knees

Data, I’m begging darlin’ please.

Data, darlin’ won’t you ease my worried mind.

Let’s make the best of the information.

Before I finally go insane

please don’t say we’ll never find a way

or tell me that all BI’s in vain

Data, you’ve got me on my knees

Data, I’m begging darlin’ please.

Data, darlin’ won’t you ease my worried mind.

Of course, if we look further into the archives we can find references to poor quality information dotted through the master works of the blues greats.

• BB King’s under rated “The referential integrity’s gone”, later rereleased as “The Thrill is gone”
• John Lee Hooker’s “I’d got my data workin’ (but it just don’t work on you)”, a song about a failed data migration later reworked and re-released as “I’ve got my Mojo workin’”.
• Robert Johnson’s lost recording “I’ve got Data on my mind”.
• The Blues Brothers “Everybody needs some data (to love)”.

Even older than that, a 7 year old Wolfgang Amadeus Mozart wrote the timeless classic “Twinkle Twinkle little infomraiton record, how I wonder how complete and consistent you are“. Unfortunately his father made him rewrite it as a childish ditty about the stars. Astronomy’s gain was our loss.

The list is endless, proving that the struggle with quality information to drive business value is as timeless as good music.

The story broke in the Sunday Times just after Christmas and has been picked up as a discussion point on sites such as Boards.ie.  TJ McIntyre has also written about some of the legal issues raised by this.

Ultimately, at the heart of the issue is a fundamental issue of Data Protection Compliance and a failure to treat Personal Data (and Sensitive Personal Data at that) as an asset (something of value) that the Hospital held and holds on trust for the data subject. It is not the Hospital’s data. It is not the HSE’s data. It is my child’s data, and (as I’m of a certain age) probably my data and my wife’s data and my brothers’ data and my sisters-in-laws’ data…..

It’s of particular interest to me as I’m in the process of finishing off a tutorial course on Data Protection and Information Quality for a series of conferences at the end of February (if you are interested in coming, use the discount code “EARLYBIRD” up to the end of January to get a whopper of a discount). So many of the issues that this raises are to the front of my mind.

Rather than simply write another post about Data Protection issues, I’m going to approach this from the perspective of Information as an Asset which has a readily definable Life Cycle at various points in which key decisions should be taken by responsible and accountable people to ensure that the asset continues to have value.

Another aspect of how I’m going to discuss this is that, after over a decade working in Information Quality and Governance, I am a firm believer in the mantra: “Just because you can doesn’t mean you should“. I’m going to show how an Asset Life Cycle perspective can help you develop some robust structures to ensure your data is of high quality and you are less likely to fall foul of Data Protection issues.

And for anyone who thinks that Data Protection and Data Quality are unrelated issues, I direct you to the specific wording in the heading of Chapter 2, Section 1 of the Directive 95/46/EC.

The Information Asset Life Cycle

Information, just like any other asset, has a life cycle through which it needs to be managed. Just because you can keep throwing files into a filing cabinet (or, in Data Protection terms, a “relevant filing system“) or hold it forever in electronic storage doesn’t mean you should.

POSMAD model (thanks to Danette McGilvray)

The key stages in the Information Asset Life Cycle are listed below, and are mapped to the 8 Data Protection Principles in the diagram opposite as well.

• Plan
• Obtain
• Store and Share
• Maintain
• Apply
• Dispose

The answers posed to the questions asked at each of these stages affect the ability of the organisation to meet its obligations under the Data Protection Act, as can be seen by the mapping of DP Principles to POSMAD Life Cycle stages.

Just like any other asset, information needs to be managed.

When you are hiring new staff, you plan for what type of people you will need in your business. You’ll need to have strategies for obtaining those staff, planning in place for how to store them (offices, desks etc.). You will (ideally) want to maintain them (training, rewards and recognition, staff retention), and be sure you can Apply them to their job (right tools, adequate resources etc.). Inevitably, you are also going to have to have answers to the question of what you will do with your staff when you no longer need them and need to dispose of them (retirement, redundancy, etc.).

With Information, you need to Plan what type of data you will be capturing and why, and who you’ll share it with. You’ll need to define policies and methods for obtaining that data (e.g. standardised testing protocols such as the Guthrie Card and the structured information captured on hospital test request forms). You’ll need to plan how that data will be stored and shared so it can be found when needed, and can be readily linked to other data etc. You’ll need to have some  consideration to how you will maintain that data (e.g. keeping personal data up to date for as long as you are holding it), and you’ll need to have a clear plan and protocol for how to dispose of the data when it is no longer needed.

Note that in this context, disposal does not necessarily mean the destruction of the data. It could simply be a process or policy that defines when data has become “excessive” and mandates the anonymising of all the data to a level suitable for statistical reporting and study but that is no longer “personal data” in the meaning of the Data Protection Acts.

Of course, just as you have measures that help you track and manage the effectiveness with which you are managing other assets (e.g. tracking equipment services and outage statistics for office equipment or purchase volumes for stationery and paper clips), you should ideally look to develop some metrics that help you know how well you are answering the various questions at each stage in the Information Asset Life Cycle.

Finally, you need to bear in mind that the Data Protection Acts now cover personal data held in formats other than electronic files. So paper based data (e.g. patient information associated with a Guthrie Card) is protected by the Data Protection Act when it is held in a “Relevant Filing System”. So your paper filing needs to bear up to the scrutiny of the Information Asset Life Cycle

The Temple Street Situation

What appears to have happened in the Temple St situation is that there was a failure to properly plan for the management of a key information asset.

• While there was a plan to provide a national scheme for testing, some key questions were not asked at the planning stage. As a result, the answers are not necessarily forthcoming to parents when faced with the test.
  

  Good Data Protection requires Planning

  For example, parents do not always know that the test is being done in Temple St. Certainly, parents were not aware that the data was to be held indefinitely. Ultimately, if Aldi (see image) are able to tell me what my personal data (CCTV images) is to be used for and who I can contact if I have a query, then the HSE and its sub-division and constituent hospitals should have been able to do the same.

• There appears to have been no thought given to the conditions or criteria for reasonable disposal (either outright disposal or anonymising) of the data. This gave rise to a situation where a Data Protection breach was inevitable.
• Parents (acting as legal guardians of their children) were not given the opportunity to opt in or opt out of being part of further scientific research using the blood samples taken from children.
• Likewise, children and adults (and the DPA does not require someone to be an adult to be protected) who have data on file in Temple St. do not appear to have a clear mechanism available whereby they can request that their data be blocked from use in processes other than that for which it was initially provided. (I’ve looked at the list of Data Controllers and Data Processors registered with the Data Protection Commissioner and Temple St. doesn’t seem to be listed in its own right is listed as the “Children’s University Hospital” and it’s not immediately clear from the register whether HSE Dublin North East or Dublin Mid-Leinster covers Temple St.) [Thanks to Hugh Jones, the lead trainer on the Irish Computer Society's Data Protection course for the correction]
• The personal data attached to the blood samples will, in a large number of cases, be woefully out of date and inaccurate – in itself a breach of the Data Protection Act – as there is likely no process to keep that data up to date. If the data is not being maintained, it is not needed and is excessive to the stated purposes for which it is being used. If the personal data (e.g. name and address) on samples that are 26 years old is being used for specific purposes, then one would suggest that any action taken on foot of such analysis is likely to be wrong.

A number of commenters on Boards.ie and elswhere have commented to the effect that the personal data could be excised out when the blood test data or samples were being used. That misses the fundamental point. There is a point in time beyond which having my daughter’s name and address cease to have an actionable value in any analysis of blood tests taken from her. If you don’t need it, then the data you are holding is excessive (in the meaning of the DPA and the EU Data Protection Directives) and should be permenantly removed. Aggregation of samples into clusters based on geographic region would likely allow for data sets suitable for scientific and statistical analysis.

But then we are right back to the Plan stage of the POSMAD model. What was intended to be done with this data? What are the stated purposes for which it is being captured? At what point does the data become excessive for those purposes? What is the plan to dispose of the excessive data (while retaining data appropriate to the stated purposes?

Conclusion

Information is an Asset. It needs to be managed and protected as such. Adopting an Asset Life Cycle approach to planning, with your Data Protection Duties forming the basis for your Key Questions can help your organisation properly plan to manage your Asset in a compliant manner. Furthermore, the Data Protection rules are enablers rather than restrictions as they provide a clear framework within which you can manage the expectations and worries of Data Subjects so that you get better up-take and happy and informed consent to you having the relevant data for as long as you plan to need it.

A key message coming from “DPA-Aware” bloggers affected by this issue is that if they had been asked if they minded anonymised data being held for research purposes they would not necessarily have objected. Investing time in planning and in valuing the Personal Data Asset which the HSE holds on Trust for the affected Data Subjects (they don’t own it) would have avoided the negative reaction and push back from rightly concerned parents and Civil Rights groups.

Want to learn practical approaches to avoiding this type of boo boo in your organisation? Why not come along to my tutorial at the 2010 IDQ Seminar Series event in Dublin on the 22nd and 23rd of February. Use the code “EarlyBird” before Jan 31st to get big savings on the event. If you are interested in just my tutorial, use the code “DoBlog” when registering.

The general format of the event was that a few of the IAIDQ Directors shared stories from their personal experiences or professional insights and extrapolated out what the landscape might be like in 2014 (the 10th anniversary of the IAIDQ).

A key factor in all of the stories that were shared was the need to focus on the needs of your information customer, and the fact that the information customer may not be the person who you think they are. More often than not, failing to consider the needs of your information customers can result in outcomes that are significantly below expectations.

One of my favourite legal maxims is Lord Atkin’s definition of who your ‘neighbour’ is who you owe legal duties of care to. He describes your ‘neighbour’ as being anyone who you should reasonably have in your mind when undertaking any action, or deciding not to take any action. While this defines a ‘neighbour’ from the point of view of litigation, I think it is also a very good definition of your “customer” in any process.

Recently I had the misfortune to witness first hand what happens when one part of an organisation institutes a change in a process without ensuring that the people who they should have reasonably had in their mind when instituting the change were aware that the change was coming.

My wife had a surgical procedure and a drain was inserted for a few days. After about 2 days, the drain was full and needed to be changed. The nurses on the ward couldn’t figure out how to change my wife’s drain because the drain that had been inserted was a new type which the surgical teams had elected to go with but which the ward nurses had never seen before.

For a further full day my wife suffered the indignity of various medical staff attempting to figure out how to change the drain.

1. There was no replacement drain of that type available on the ward. The connections were incompatible with the standard drain that was readily available to staff on the ward and which they were familiar with.
2. When a replacement drain was sourced and fitted, no-one could figure out how to actually activate the magic vacuum function of it that made it work. The instructions on the device itself were incomplete.

When the mystery of the drain fitting was eventually solved, the puzzle of how to actually read the amount of fluid being drained presented itself, which was only of importance as the surgeon had left instructions that the drain was to be removed once the output had dropped below a certain amount. The device itself presented misleading information, appearing to be filled to one level but when emptied out in fact containing a lesser amount (an information presentation quality problem one might say).

The impacts of all this were:

• A distressed and disturbed patient increasingly worried about the quality of care she was receiving.
• Wasted time and resources pulling medical staff from other duties to try and solve the mystery of the drain
• A very peeved and increasingly irate quality management blogger growing more annoyed at the whole situation.
• Medical staff feeling and looking incompetent in front of a patient (and the patient’s family)

Eventually the issues were sorted out and the drain was removed, but the outcome was a decidedly sub-optimal one for all involved. And it could have been easily avoided had there been proper communication about the change to the ward nurses and the doctors in the department from the surgical teams when they changed their standard. Had the surgical teams asked the question of who should they have in their minds to communicate with when taking an action, surely the post-op nurses should have featured in there somewhere?

I would be tempted to say “silly Health Service” if I hadn’t seen exactly this type of scenario play out in day to day operations and flagship IT projects during the course of my career. Whether it is changing the format of a spreadsheet report so it can’t be loaded into a database or filtered, changing a reporting standard, changing meta-data or reference data, or changing process steps, each of these can result in poor quality information outcomes and irate information customers.

So, while information quality is defined from the perspective of your information customers, you should take the time to step back and ask yourself who those information customers actually are before making changes that impact on the downstream ability of those customers to meet the needs of their customers.