Data Governance - lets make beautiful music together.

I've been in my new post as Director of Data Governance at the University of New South Wales for about a month now.  

Most of my time has been spent trying to get to meet people and hear their perspectives on how things work around campus (or don't), what the key issues are, and just getting to grips with the scale of the challenge in an organisation of approximately 5000 staff (Or 8000. Or 13,500. It kind of depends on which definition of "staff" you're using - but that's another story...)

Anyway, I had the opportunity last week to present to the University's IT investment committee, a senior executive group comprising faculty managers, academic leaders and financial governance. I was allocated 10 minutes to introduce myself and provide an update on the Data Governance agenda. Now, it's already clear that the University has an appetite to do something significant with respect to the usage and accountability for data (the fact that they've hired me is a statement of intent!). But let's be honest - there are going to be relatively few members of the university community who need to (or want to) get to grips with the wider scope, complexity and subtlety of and Enterprise-wide Data Governance and Information Management operating model! 

So I was struggling to think of a way to frame my agenda in a manner that was going to convey the scale of the task ahead without scaring everyone (or boring them rigid), and I came up with an analogy that seemed to resonate with the audience.

If we think of the University (or any other organisation for that matter) as an orchestra, then the various Faculties, Schools and Business Units are the musical sections, and the staff are the individual musicians. The organisation's data is the music to be played and the role of the Data Governance function is analogous to the conductor. 

Now, the outcome for any orchestra is to be able to give a concert to a paying audience (and get them to come back again…). The enabling capabilities which are required to get the concert on stage are a complex mix of contributions from numerous different people, applying multiple processes and skills, with the agreement of all participants to work towards the same goals:

1. All musicians need to have the skills to play their allocated instrument. (not necessarily a given!)
2. Someone has to write the music, orchestrate it, publish it, make sure the sheet music is brought to rehearsals.
3. We have an agreed running order for the concert.
4. Everyone needs to be playing the same tunes, at the same speed, and starting at the same time.
5. Rehearsals and practice (individually, in Sections, and together as an Orchestra).
6. Marketing the concert, booking the tickets, ushering the audience.
7. The performance.

THE CONCERT IS A FAILURE IF ANY PART OF THE PROCESS DOESN’T HAPPEN, AND IT WOULD STILL ALL BE LIKELY TO FAIL WITHOUT THE CONDUCTOR TO BRING IT ALL TOGETHER.

So Data Governance is about consciously and competently orchestrating and conducting all the various efforts throughout the organisation, so that whatever data we have (or need to have) is available, in context, and usable for a range of well-defined purposes.

Underpinning our data orchestra are an established set of formal practices, processes and protocols that define the institutional capability required, many of which may only exist in part, some not at all. Initially, we need to establish which of these services are needed, where are the gaps, and how they will be fulfilled. e.g.

Organisational Capabilities:

• Data Governance Steering Committee, focussing on Data/Information issues.
• Formal identification of Data Owners & Stewards for each data asset.
• Fora that bring together the community of Collectors and Consumers of each given information domain. 

People/Skills:

• Information Management/Business Intelligence Competency Centre
• Value-added analytic services and support the whole-of-institution approach.

Process:

• Business Glossary and metadata management techniques for collating and communicating common & consistent data definitions;
• Data Quality Profiling & remediation service;

Systems:

• Robust, scalable Data Warehouse & BI that is insulated from, and supports, change. 

Now, does everyone need to know or care about all the detailed practices & protocols, or how all the complexity happens? NO.

But I’d content that everyone does need to know about “their bit”, where the information touch-points are with other parts of the organisation, and that whatever their doing fits into the overall context.

To go back to the orchestra analogy, each individual musician doesn’t need to know how the composer and music publisher does their job, but they do need to know that the sheet music is going to be available, and that they’ve got to turn up at the Opera House on Tuesday week for a recital…

Which I guess makes yours truly the baton-wielding eccentric with the funny tailcoat suit and mad hairdo... 

CxO’s are blithering idiots! But what if they’re Idiots Savant…?

A client of mine (let’s call him “Mr. X”) who is the CIO at a government agency (let’s call then “Agency Y”) recently spent a fairly significant proportion of his organisation’s ICT budget for this year on a fairly large data warehouse appliance {let’s call it “Product Z”). Agency Y also got a 20% discount off list price for buying immediately.

“Nice work!” I hear you cry, “They’ve bought a market leader in the field which is constantly improving its technology, they’ve purchased at a discount, and if Agency Y is investing in Business Intelligence platforms, then they must be thinking progressively and wanting to drive more value from the information that’s available in the organisation. Splendid!”

Now, put that purchasing decision in the context of some additional information about the current situation at Agency Y:

• There are no current business projects identified that require BI capability;
• There are no statements of requirement for information-enabled use cases;
• There is no inventory of data holdings;
• There is no Business Intelligence architecture defined;
• There are no plans at present to buy any ETL or BI end-user tools;
• The purchase of Product Z was made without reference to any formal solution selection process (e.g. due diligence evaluation of options in the market, price-testing to see whether other vendors would be more cost-effective, or proof-of-concept to validate that the product actually works).

Does Mr. X’s decision to buy Product Z seem so sensible to you now?! Effectively, at this point in time Agency Y has a 900kg, multi-million dollar paperweight sitting in its data centre.

I was discussing this scenario with my distinguished colleague Ben Bor today and I had started from the perspective that Mr. X is clearly a blithering idiot (like most of the Senior Execs I come across…). However, Ben posed a very interesting question, viz:

What if Mr. X is actually a genius?

Wow! That made me think!

Could it possibly be that the executive decision-making process is such that it is beyond our reckoning? What if this seemingly nonsensical waste of money is actually part of grand plan that we just don’t have the tools to comprehend? Given that Mr. X is at CxO level and we’re not (and probably never likely to be), maybe CxO’s have decision-making insights that transcend the normal logical approach that we mere mortals apply in these scenarios? Is Mr. X (and other executive decision-makers) actually a Savant?

Or is making a multi-million dollar purchasing decision with no evidence, no substantiation, no process and no currently identifiable requirements just really, really, REALLY stupid?

You, dear reader, can decide. I clearly don't have what it takes to understand such things.

BREAKFAST BRIEFING 05/09: Policy, Process & Culture in the lifecycle of an Information Asset

I will be running an interactive breakfast briefing on the topic of "Policy, Process and Culture in the Lifecycle of an Information Asset", to be held on Tuesday 05/09 at 8am, at the Boat House in Canberra.

For further details and to register, please click here: http://www.smsmt.com/About/Events/ACT-Information-Management

Revolutionising the Data Warehouse & Business Analytics: Top-10 Takeaways

I was delighted to chair Ark Group’s inaugural “Revolutionising the Data Warehouse and Business Analytics” conference this week.

The event featured participants from a diverse range of organisations such as Telstra, Australia Post, Asciano, Deloitte, PBT Group, Macquarie University, Uniting Care Heath, University of Technology Sydney and the Australian Sport Commission. Their though-provoking content provided stimulus for a highly interactive forum with some great debate.

A wide range of topics and themes were touched upon during the event, however some concepts were cropping up consistently throughout the various sessions. I’ve captured my own personal “Top 10 Takeaways” from the conference (not in any particular order):

1. Think about “Data Warehouse” as a set of services, not a single monolithic IT system. There needs to be a mind-shift away from the technology-centric view of a highly controlled Enterprise Data Warehouse.

Instead, think of the “warehouse” more as a set of organisational capabilities or services that facilitate information delivery and context-based analytics at point-of-need. The important aspect is not the technology, it’s the usage (and the action that is taken as a result).

A further enabler of this way of thinking is to adopt Agile methods within the data warehouse and analytic environment. Deliver to the requirements that achieve visible business value and accept that ongoing iteration and rework are simply a business-as-usual cost of doing effective analytic business.

2. Apply the principle of “Data First”. The organisation needs to understand the inventory of what data is being captured (or could be captured) in order to start exploring what that information could then be used for. Where possible and within reason, source all of the data that you can, even if you don’t have a specific business requirement in mind.

This also will help to facilitate the “second-sight” required to be ready to meet future emerging business requirements. For example, Google have adopted a philosophy of “throw nothing away” (right down to each mouse-click event and change of font colour on a web page), on the basis that they may be able to derive additional insight in the future that has not even been envisioned yet.

As a starting point, conduct a comprehensive audit of the organisation’s data holdings, so that you understand the information content that is available and can start to align it with the business context(s) that it can be applied to.

3. Ground everything you do in business requirements. Don’t start with the technology and then go looking for a problem to apply it to. Find the business requirement and then apply technology as a tool for enabling the solutions.

This also helps as a principle to guide your relationships with the technology vendors, who’ll happy try to sell you products as the solution to your requirements, even when you haven’t actually defined the problem yet!
(Note that this learning point is complementary to the “Data First” principle, not in conflict with it.)

4. Big Data: there are five “Vs”, not three. In addition to the now ubiquitous Big Data dimensions of “Volume”, “Variety” and “Velocity”, we should also be thinking about “Variability” and “Value”, and the most important considerations are these last two.

Complexity of the data landscape means that we’re not dealing with “structured” or “unstructured” information, we’re dealing with a diverse range of multi-structured data sets.

Meantime, if we don’t understand the context of the information that we’re dealing with and have mechanisms to navigate the impact on successful outcomes, then we need to question whether the activity is worthwhile.

Look for tangible value and ensure that you can explicitly identify and communicate sufficient value to justify the investment (accepting that there will be areas of benefit that may be less quantifiable.)

5. Information Governance is crucial. There needs to be an explicit information value chain that identifies what the decision rights and business rules are, and who is accountable.

There needs to be formal and visible measurement, with control points that then hold people to account. Successful organisations are investing in data quality as a human issue with process and cultural implications, not just technical ones.

6. The success of any data warehouse initiative is directly related to the level of Change Management capability. Transformational impact is achieved when data warehouse and analytics are rolled out pervasively, paying full attention to the human aspects of the change that arises.

This has to be done as a conscious discipline by members of the team who are practiced in Change Management techniques. Organisations will derive more benefit from a relatively small-scale solution that is well socialised and accepted as part of day-to-day business operations, than from a technically excellent analytic warehouse solution with no engagement.

7. A measure of information’s potential value is its likelihood of having unintended consequences. Think about the impact that knowing a particular piece of information could have. What unintended consequences could it lead to if that information is made available to the wrong person or used in the wrong way? If there are far-reaching consequences, then the information probably has significant intrinsic value.

e.g. Knowing someone’s favourite colour probably has little impact on them regardless of who that information was share with, however knowing their political allegiances could be potentially damaging if made known out of context.

8. There is still a lot of “biological ETL” going on. Human beings are still spending a lot of their time mashing up data in spreadsheets, re-keying data from one system to another, collating multiple reports to then derive a subsequent calculation.

Every function that can be rationalised or automated frees up more time for people to think and act.

9. Engage. Visible, active and regular communication is crucial. Share ideas, collaborate, ask awkward questions and expect them to be answered.

Use intellectual curiosity and sceptical scrutiny as tools to drive better thinking.

10. The future is the Cloud and Open-source, and it’s already here. ICT infrastructure is moving to the Cloud at an accelerating rate and organisations should expect (indeed demand) their data warehouse and analytics solutions to operate on Cloud-based platforms.

Open-source solutions are changing the game to the point where it becomes questionable whether costly, proprietary technologies are required any more. NOSQL will become an increasingly pervasive element of the analytic environment.

We all need to adapt our thinking to maximise the benefits of transitioning to Cloud and manage the legislative and regulatory implications (e.g. with respect to Australian Privacy legislation), but Cloud not going to be negotiable.

Challenges for the Information-Enabled Organisation (pre-conference article)

In advance of this month's "Revolutionising the Data Warehouse and Business Analytics" event, Ark Group are running a series of articles that address some of the topics that will arise at the conference.

My contribution, "Challenges for the Information-Enabled Organisation", is published here: http://www.arkgroupaustralia.com.au/News-DWnewperspect.htm

Other associated articles worth reading:

"Adding Social Customer Analytics to the Data Warehouse"  http://www.arkgroupaustralia.com.au/News-socialcustanalytics.htm
Top-10 tips for Data Warehouse Developers" http://www.enterprise-advocate.com/2012/04/top-10-tips-for-data-warehouse-developers/ 
"Big Data Analytics: 2012 predictions" http://tdwi.org/blogs/philip-russom/2012/01/big-data-analytics-2012-new-years-predictions.aspx

Further details for the conference can be found here:
http://www.arkgroupaustralia.com.au/Events-E024datarev.htm
Event entry on LinkedIn

Event Notification 23/24 August: "Revolutionising the Data Warehouse & Business Analytics", hosted by Ark Group

I am delighted to be chairing the forthcoming Ark Group conference "Revolutionising the Data Warehouse & Business Analytics", to take place in Melbourne on 23rd & 24th August.

The conference agenda will explore the following challenges:

• Demonstrating the tangible benefits and ROI of data warehousing
• Effectively managing Big Data
• Overcoming the barriers of to move to agile data ware house
• Maturing organisation’s data quality capability
• Bringing IT costs into control by effectively using Cloud
• New technologies and trends in business analytics

For more details, conference brochure and registration, please click here: http://www.arkgroupaustralia.com.au/Events-E024datarev.htm

Information as a Service, Part 2: what do I do about it?

In an earlier post, I defined the concept of “Information as a Service”, and covered off why successful Information Management requires a change of mindset that emphasises the wider context of why information is required, and for whom. I’d like to now like to turn attention to the impact that Information as a Service can have and some hints-and-tips on how to achieve better outcomes.

IT departments have traditionally struggled to engage with an information-aligned business agenda. The rigours and constraints of IT delivery are focussed on managing the technology infrastructure and applications that store and distribute data (containers and connectors), rather than having linkage to the relevance of the contents used in context. This focus typically requires an approach that is oriented towards policing of controls, process compliance and gatekeeping of expenditure.


In contrast to a technology-centric mindset, an information-oriented approach requires a different and complementary set of skills. Most importantly, it requires a fundamental change of mindset for the information team (whether for data warehousing, business intelligence, analytics or Documents & Records Management). To be able to encapsulate the information content within its business context, the team needs to articulate the relevance and impact that the organisation’s information has on business performance and process effectiveness. This in turn creates a clear line-of-sight from business value, through analytic information services to the underlying data warehousing of information assets focuses the people, processes, and technology towards the optimal management of information.

It becomes clear that without a critical mass of these competencies, organisations will struggle to balance investment in information with the information requirements of the organisation. Having a data warehouse and analytic environment that is fully aligned to the business view of the organisation ensures that management of the Information competency is fully congruent with the required business capability.

Data Warehousing and Analytics programs can deliver value to organisations at any strategic pain-point.  However, each initiative must be matched to the performance management strategies appropriate to your organisation’s business model. This process will drive the right investment in the data warehouse and associated analytic outputs.

A “top 10” of actions that help to develop better engagement and alignment with the “Information As a Service” mindset might include:

1. Managing business performance through visible measurement: this requires explicit investments in executive decision-making via executive dashboards which report directly from operational and management information systems. A strong link is created between reporting processes and actual business performance, setting the foundation for analytics-driven performance optimisation. 
2. Using the information that is currently available to drive new information capture: focusing data warehousing initiatives on making decisions with the best existing information focuses attention on understanding what additional information is required information but is currently not available. This supports proactive management of decision risks through highlighting the gaps to drive prioritisation of new data sources for data warehousing initiatives.
3. Driving commonality of analytic solutions and services: optimising the information delivery process by consolidating and standardising the inventory of common management and operational reports. A coherent approach that co-ordinates across all system enhancement, performance improvement, and transformation initiatives means building an integrated suite of reports that delivers repeatable elements common to overall business performance. Resources can then be re-focussed towards specific value-adding tasks, rather than maintaining multiple, duplicated copies of basic reporting services. 
4. Completeness of data integration: managing a continuous, prioritised pipeline of data integration for all organisational data to ensure the data warehouse suite supports both current and future demands. Data integration requirements should be driven from strategic drivers, proactively acquiring data for future analytic initiatives to enhance responsiveness.
5. Explicit management of ad hoc reporting and analysis: Implementing a Centre of Excellence / Competency centre that is formally accountable for managing a tiered community of users from information consumers, information integrators, statistical analysts, to decision makers
6. Metadata Driven Governance and Delivery: driving scope management, governance and delivery through a co-ordinated approach to metadata management. This ensures the requirements quickly find their way into working solutions and are validated by the business early in the project lifecycle. Using a Business Glossary and metadata-centric Agile delivery methods shifts the focus to the organisation information needs instead of the technology used to deliver the information.
7. “Steel thread” to manage data warehouse delivery risk: When developing business analytic solutions, the focus of planning and management effort should be on business requirements and objectives.  However, there is also a hidden risk in all projects - the unbounded effort in the development work stream caused by detailed technical unknowns. The concept of a “steel thread” maps the end-to-end linkages and dependencies from deploying the underlying warehouse technical platform, through data and analytics application development and on to the final business outcome, based on a tightly bounded sub-set of the overall business requirements. Potential issues in the technical environment, in the use of new technologies, or in the understanding of business logic are identified, tested and mitigated early in the delivery cycle, so that the overall solution implementation is de-risked.
8. Proactive Data Quality Management: assessing overall Data Quality for data sources and implementing appropriate controls and remedial actions to ensure Data Quality is managed in a proactive manner, both during programme execution and beyond into business-as-usual operations. Measurement and profiling, root-cause diagnosis, remedial action and continuous improvement are all necessary elements of a proactive approach to Data Quality. (The linkages between data and its usage in context are explicitly identified, as data quality is only ever quantified as a function of its usage).
9. Formal Data Governance: The people and functions who produce and use information are the people who know its value, understand what they need to save and should know how long a given set of data is going to be useful.  And while business people may know these things, it is often difficult – or even impossible – to get them to articulate their own information needs. Additionally, many departments only give consideration to their own information needs and opportunities for re-use, combination and added value are often missed. A robust and sustainable Data Governance regime provides a common foundation of “Rules of Engagement” and identifies explicit decision rights and accountability for the analytic business mandate. 
10. Delivering analytic solutions that are fun to use: people are more likely to make use of tools and services that are not only easy to use but are also attractive and engaging. Application of user experience (UX) disciplines and data visualisation techniques ensures that information is presented pleasingly and effectively for the intended decision making process.

Aligning data warehouse and analytic services with business outcomes requires a conscious focus and effort, either as an initiative in its own right or as part a holistic approach to implementing Information Governance within an information-enabled business transformation.  Once the overall scope and context of the implementation has been established (e.g. as part of defining the organisation’s Information Management Strategy and Roadmap), the aim is to stand up the new analytic competency as quickly as possible, so that your organisation can begin to realise the benefits of the transformed data warehouse capability.

Event notice - lunchtime seminar 19/07/12 in Melbourne: "Information as a Service"

Following on from last week's blog post on the topic of "Information as a Service,"  I will be hosting a lunchtime seminar on Thursday 19th July from 12-2pm, to take place at SMS's Melbourne offices at Level 41, 140 William Street. This interactive discussion will cover themes including:

• How the concept of “Information as a Service” drives better business outcomes and value
• Why “Information as a Service” requires the implementation of an Information Management Competency Centre (IMCC)
• The key steps necessary to develop the IMCC
• How to effectively embed an IMCC into your enterprise operations
• How to achieve an end-to-end view of your information assets via an IMCC
• How the IMCC integrates and supports wider business initiatives for Information Governance

For further details and to register to attend, please click here: http://www.smsmt.com/About-SMS/Events-Calendar/VIC---Information-as-a-Service.aspx;# 

“Information as a Service” – what is it, and why is it important?

In recent discussions with some of my clients, I've encountered increasing interest in the concept of "Information as a Service." A couple of themes are consistently arising:

• the topic seems to mean different things to different people, and;
• For those that have a point of view, they don't really seem able to articulate what "Information as a Service" really means anyway!

In giving further thought to this, I've identified a number of underlying issues that most clients are trying to address. Consider the following trends and challenges faced by organisations competing in an information-rich environment:

• Growing volume and complexity of data from social media platforms, smart devices, text mining steams, and data available to purchase – all potential sources of competitive advantage.
• Emergence of new technologies which enable the information to be delivered in ever more meaningful ways.
• Business continuity & sustainability are increasingly dependent on the reliability of information management processes and continuous innovation in the management of information.
• Challenges in managing to information policies, aspirations, and obligations for compliance, transparency, and privacy when operating in complex partner ecosystems with outsourced delivery models
• Being able to predict new scenarios and meet rapidly changing business demands, often before they are formally identified by the user community.
• Increasingly there are information components to product offerings - this puts pressure on the timeliness and accuracy of information that was once internal, but is now presented externally to customers.

The feedback I'm getting is that a successful approach to managing all the above complexity requires a fundamental change of mindset for the Information Management community. Many Information Management practitioners will concentrate on the themes of what information needs to be delivered and how it will be delivered. Unfortunately, these critical questions do not engage well with a business audience, who are typically motivated by understanding the wider context of why information is required, and for whom.

Turning this around requires information practitioners to develop a different approach so that all activities in the information value-chain are presented through a business-oriented lens that gives consideration first and foremost to the questions of business context and business outcomes to be derived from making the right information available, at the right time, to the right people. Based on the above, we arrive at a definition for this concept of the managing information value-chain as delivering information as a service:

Critical to the concept of Information as a Service is the ability to encapsulate the information content within its business context, articulating the relevance and impact that the organisation’s information has on business performance and process effectiveness. For example:

• For telecommunications operators, having the ability to reconcile unbilled calls against the total volume of calls carried translates to an understanding of revenue leakage;
• For insurance businesses, ability to accurately correlate total premiums paid per customer against total claims enables additional control on unsubstantiated refunds;
• For government care agencies, correlating the history of different benefit payments to a specific household provides insight to identify possible opportunities for earlier and more effective care interventions.
• For healthcare organisations, performing text-mining analysis across all patient records can enable hidden causes of an infectious outbreak to be identified. 

In other spheres of operation (business process management, for example), the potential benefits of service-based management are well understood. However, this service-based approach is rarely applied effectively to the way in which information is delivered within the organisation. An information management (IM) capability that delivers information as a service has the potential to transform your organisation.

When information is viewed as an asset, establishing the competencies to exploit value from information becomes a business imperative rather than a technical one. This implies the intention to create a clear line-of-sight from business value, through information services to the underlying information assets focuses your people, processes, and technology towards the optimal management of information:

• Creating an integrated view of core shared data critical to your organisation;
• Creating a culture that makes use of the best available information in all decision-making;
• Effectively managing the end-to-end lifecycles of information to maximize value across multiple business capabilities, processes, or information systems;
• Integrating performance management processes (organisational and HR) at executive, management, and operational levels to ensure strategic goals are reinforced throughout the organisation;
• Creating a vision for an information-enabled organisation that drives investment priorities and highlights gaps in capability;
• Ensuring the right people, processes, technology, and roadmaps are in place to support that vision;
• Providing clear line of sight from investment to benefits.

In my follow-on post Information as a Service Part 2: What to do about it?, I explore some ideas on to the impact that Information as a Service can have and some hints-and-tips on how to achieve better outcomes.

Want a successful Information Architecture? Ignore your consultant's advice!

As part of the Information Strategy toolkit within our Information Management consulting practice, we have built up a range of governance, architecture and process frameworks that facilitate rapid client engagement, enable repeatable solutions and maximize the opportunity to get "sticky" with clients (not as unpleasant as it sounds). As well as as being useful tools "in the field" for paid consulting work, I also use these templates as base content when preparing to present at conference sessions, seminars and tutorials. For many situations, our clients will simply run with our template solution frameworks, perhaps with some minor adaptions of the model approach. Assess, configure, adopt. It's a genuine "win/win" - great for the client (simplifies the solution approach, reduces risk, enhances time-to-value) and great for our consulting business (market differentiation, genuine re-usability, and enables us to charge a justifiable premium on standard resource-augmentation day-rates).

A recent engagement with a major Australian Bank required my team to deliver some methodology templates for governing the bank's Information Architecture process. The engagement delivery process started off with a fairly standard discovery phase, where we did a quick-scan of the client's circumstances, using our Information Governance Frameworks as the baseline for the assessment. However, soon after we started tailoring the templates from our "magpie's nest" of shiny re-usable collateral, the client effectively ignored all of the pre-defined content that we'd tabled with them and started writing their own content instead. Pretty quickly, the outputs of the engagement were unrecognisable in comparison with the model content that we'd brought to the party. Indeed, it got to the point where our contribution to creating the final project deliverables was almost peripheral. Yet the client was still delighted to pay our consulting fees in full (to the point where they paid us the full T&M budget, even though we'd not consumed all the days allocated to the project). How could that be?

Where we got to was that the client got lots of value from the analysis process, stimulated by our template materials. By examining our best-practice frameworks, the client's Information Architecture team were able to assess their requirements in a way that they had not been able to do before. Picking apart our templates and models acted as an excellent stimulus to have the internal debate and achieve a consensus that had been missing. So, even though thto framework material didn't meet their needs, it served its purpose in the context of delivering value to the architectural aspects of Information Governance approach.  Having started out with the expectation that the client wanted my team to just "provide answers to their problems", we ended up in a position where they discovered what they really needed was someone to come in and prompt them to ask the right (or at least, different) questions.

Go to market, hire some expensive experts to give you their best advice, and then ignore it. Perfect!

Overall an interesting exercise, and one which has also helped me re-evaluate my personal perceptions of what it means to be called upon as a "Subject Matter Expert". Hopefully, I'll be a better consultant as a result....

(Footnote: as a by-product, my team also got the benefit of stress-testing our template frameworks and we gained some valuable insight which is helping us to further iterate and enhance our Information Governance approach. A happy client and a happy consulting team. Win/Win).

The concept of Information Salience. Or to put it another way: answering the thorny question of "why are we bothering?"

I am currently working with a major government agency (let's call them "Agency X") on their Information Management delivery planning. Agency X has two main purposes - to manage the overall allocation for core funding in their area of government, and to inform the policy agenda for portfolio X at a strategic level. (As is typical in the Australian Public Sector, strategic policy-making and funding are segregated from the operational delivery of services to the public, which are funded by Agency X but executed by various other agencies with their own Ministers).

Agency X already has a relatively clear strategic view of its Information Management agenda. The Information Strategy has recently been endorsed at an Executive level and defines a roadmap of the things that the Agency wants to achieve and has established a sensible timetable for when it wants to do them by. The staff are information-savvy and very motivated by using data, both to monitor the effectiveness of the agency's programmes and as evidence to support the design of new funding initiatives. My current role is to consult with the Agency on an advisory basis and help them flesh out some answers to the "how to do it?" question. So far, so good.

(Aside. Speaking as a taxpayer, I do sometimes ponder the question of whether government agencies should really need to spend so much money using external consultants to do their thinking for them. But then "Consultant-me" quickly gives "Taxpayer-me" a hard mental slap and tells "Taxpayer-me" that about 75% of my business is derived from providing advisory services to government agencies, so would I kindly like to pull myself together and just get-the-bloody-hell on with it...)

Back to Agency X. As we've been going through the Information Management planning exercise and getting some real progress on a workable, progressive plan that will deliver the Information Strategy and meet the overall stated requirements, two thorny questions came up that no-one had previously thought to ask: "Why are we doing this?" swiftly followed by "Why now?". Everyone had been so focused on getting the Information Strategy defined to answer the "what" and "how" questions that "why" didn't ever get thought about - until now. Cue much angst amongst the information user community, who can see their much-desired and long-awaited information capability evaporating before you can say "quantifiable benefits".

(By the way, preparing a robust Business Case might seem like a fairly obvious thing to think about if you're planning any form of investment. Yet in my experience, Agency X aren't at all unusual in their situation, and its not a problem that's confined to government entities. I've come across plenty of commercial businesses that have been similarly naive in their approach to substantiating their rationale for proceeding with an Information Management initiative.)

Having now further explored these questions with Agency X, it became apparent quite quickly that they actually don't have a "compelling event" to make them do something fundamentally different. There would be value overall, yes, but it's largely incremental and often somewhat unquantifiable (statements to the effect of "better policy-making", "delivering a more effective Service programme to the public" etc. etc.). On the face of it, it's pretty difficult, then, to make an immediate case for making the significant investment that would be required if they were to deliver against their strategic Information Management agenda (and it also gets to the heart of why they've not really done much beyond well-intentioned skunk-works up until now).

So, how to deal with this? How to make the business case for investment in Information Management when you can't (easily) show a return?

On examining the situation with Agency X a little further, I've concluded that this classic "we really think that we should but the benefits are unquantifiable so we probably won't" paradox is actually only a symptom. I think that the underlying consideration, and one which can be applied to all organisations, is one of information salience.

Just as with concepts in business process mapping where one can identify the "salience" (or relative importance) of a process to the business, it is similarly possible to categorise the information holdings within an organisation based on their relative importance to the operations of the business. The simple classification schema that I suggest for Information Salience is as follows:

• "Identity" - information is part of the "corporate DNA" that identifies the Organisation to the market; information delivery is fundamentally what the company is known for. For example, Reuters is a pure information business - providing information is simply what Reuters does, information is what people buy from them. A credit-scoring agency or database marketing firm make similar information-as-a-product market offers.
• "Core" - the business operates on the flow of information, and without it, it wouldn't function. For example, under the hood, a bank could be considered an information management company with a banking license. A telecommunications services business is an information management company with a telco operator's license. Without a strong core of robust information management and high-performance data processing at the heart of their business model, these organisations would simply cease to exist. (Contrast this with the example of fast-moving consumer-goods entity, whose manufacturing plant will continue to make stuff and ship it out the door irrespective of whether the management reports on productivity are prepared at month-end).
• "Mandatory" - information has to be controlled and traceable for audit purposes, or to meet legislative obligations. An oilfield drilling and production operator needs to have traceable, auditable management of its information or risk having its license revoked. Government organisations must demonstrate compliance with data protection and Freedom of Information obligations.
• "Hygiene" - back-office functions that deliver underlying support to the Organisation, but are not core to its business operations. Typically, these are processes that should easily be outsourced. Accounts Payable processing and HR payroll are good examples of processes where information is important to their operation, but efficiency and effectiveness of such functions are actually marginal to the overall success of the Organisation. (Aside: interestingly, it's often these types of processes that get a disproportionately significant share of any corporate funding for optimisation and enhancement, even though they're furthest removed from the business value chain!)

Notice too, that the "optimise and enhance" mandate for Information Management can apply to all four categories in the Information Salience model - hence the reason that I have not given it a category of its own.

Back to Agency X. I think they have been struggling to articulate a fundamental case for Information Management because the agency's "core business" doesn't actually rely on information to operate. In contrast to a bank or a telco (where the controllable flow of information IS their business), good information practices for this Agency are a "nice-to-have"; they help to optimise & enhance the Agency's mandate to allocate and distribute government funds, but information is not core to their operations, and it's certainly not part of the Agency's brand identity. It therefore becomes a challenge to quantify the value of investing in an Information Management approach, beyond the bare minimum necessary to achieve the "compliant" tick. Certainly, it's nigh on impossible to put $ value on the benefits.

Applying the above Information Salience model, I'd argue that for Agency X, their requirements are broadly in the "Mandatory" category - they are compelled to do something because of government imperatives for "evidence based policy making" as well as mandates for improved transparency & accountability. Information certainly isn't "Identity" process for them (it's not what they're known for), nor is it "core" (in principle they could quite easily continue to exist, even if they didn't do any reporting on what they're targeted on achieving).

Having identified this underlying challenge in the relative salience of information to Agency X, I can now start to help the Agency identify all of the "mandatory" aspects of reporting, analysis, accountability and auditability that will hopefully add up to a powerful case for taking positive action to improve their Information Management agenda - why they should do it, and why the time is now.

And if we can then approach answering the "how to do it" questions in the right manner, then Agency X will also achieve additional levels of efficiency (do more stuff with the same money) and effectiveness (do the right stuff, to the benefit of more people).

Speaking as a taxpayer, that has to be a good thing.

Fed up being right? Take a tip from a 2500-year-old Greek!

I've had several situations in recent weeks where my client's talented and growing Advanced Analytics team has complained about their problems with business end-users who won’t accept the results of an evidence-based analysis. "it's crazy!" they say. "The models and calculations are sound, the data sets have integrity, we can prove our answer is right! How can the business team still be making gut-feel decisions? They just don't understand!"

The penny might just have dropped for them yesterday though, when their Group Director gave a short presentation on the overall business strategy for the next 12 months. Out of the blue (and unprompted) he said, "we all need to learn that being right isn't always enough", before going on to outline that the political decision-making process often didn't depend on the data, and that bringing people along on the journey was often more important than the actual facts.

This revelation was just the cue I needed to introduce the Analytics group to a technique that I've been applying for some years, based on the main themes from Aristotle's "Art of Rhetoric". In summary, Aristotle identifies three factors that you need to get in balance in order to carry the argument: 

Logos - this is home territory for the analytically minded. This is the underlying proof of the case, and depends on whether the evidence stands up to skeptical scrutiny and examination. The challenge is that if the audience is not skilled enough to grasp the rationale of the argument or follow the logical reasoning being put forward, then the case can go no further! This is the situation my client’s analytic team is currently faced with – the business community aren’t familiar enough with statistical concepts and evidence-based decision making to let the facts stand up for themselves.

Ethos – the reputation, disposition and standing of the speaker in the perception of the audience, based on their ability to project good sense, moral character and goodwill. A message is more likely to be well received if it the audience has confidence in the nature of the speaker; this is established by successfully conveying  oneself as having the relevant experience, expertise and judgment to be talking on the subject. An “expert” with the right credentials will be more credible that someone who is perceived as having less of a track-record (whether or not they’re actually all that knowledgeable). As a consultant, it’s the Ethos dimension that I’m most often trading on, at least in the early stages of a new relationship – if a prospective client has the expectation that I’m an expert, then they’re more likely to hire me! Tools of the trade that help me generate instant Ethos include a good CV, case studies and testimonials from happy clients, and of course plenty of war-stories drawn from my back-catalogue of successes (and failures! There’s always additional credit to be gained from sharing a painfully-learned lesson.)

Pathos – the ability to engage with and appeal to the audiences emotions. Being able to put the listener in a certain frame of mind will make them more disposed to agree with your point of view. Aristotle describes methods of arousing all sorts of emotional responses from an audience, depending how you want the listener to respond. In order to be successful in establishing the right connections with the audience, the speaker needs to be able to carefully judge the listener’s initial emotional state, such that the messaging can then be adjusted accordingly to tap into the desired emotional response. There would be no point giving bad news to an audience that was already angry, regardless of how rational the logic of the situation!

It's this third area of Pathos that's often the missing capability, and interestingly it's the one that sales people, marketeers and politicians operate in most of the time. Who needs facts when you can manipulate people's emotions in order to bend them to your will? (A chilling example of just how powerful the successful use of Pathos can be is illustrated by the rise of the Nazi party in 1930’s Germany).

While in some respects it is this third area that seems to be the most effective aspect of conveying an argument successfully, As Aristotle advises, there needs to be a balance of Logos, Ethos and Pathos in your presentations, or else you are going to get found out at some point. I therefore find it very helpful when preparing a business case or recommendations report to make sure that I've given consideration to all three areas. Here are a few questions that I ask myself in reviewing my presentations:

• Logos: have I prepared the raw facts and supporting evidence clearly and presented them with integrity and traceability? Does the rationale for the requirement really stack up? Have alternative solutions been identified, examined and discounted so that there can be no objections further down the line? Have I reduced the amount of jargon and simplified the presentation of the information in a no-nonsense way that can be understood by the least knowledgeable person in the audience? (If you want an excellent example of how this can be achieved, read Professor Stephen Hawking’s book ‘A Brief History Of Time’).

• Ethos: Have I researched additional 3rd party quotes and made cross-references to other bodies of work? Have I included anecdotes and observations from other stakeholders within the same organization? Have I used examples from my own case studies to compare with the current client’s situation?

• Pathos: Have I identified the “what's in it for me” factors and business benefits that are relevant to the people making the decision? Do I understand their current disposition? If the decision I want them to make is unpalatable, what do I need to do to get them feeling positive before breaking the bad news? (Don't forget the FUD factors - Fear, Uncertainty and Doubt. Perceived risk of failure and the ability to save face are powerful motivators.)

 Don’t worry if you never get around to reading the whole of Aristotle’s book – it’s pretty dry in places and can be hard going! But remembering to apply the underlying themes of Logos, Ethos and Pathos will give you a reference-point to test your messaging before engaging with your audience. So next time you're about to make a presentation or recommendation to a group of stakeholders who might be a little less than data literate, don't forget to get your Greek on!

I am honoured to have been asked by Records and Information Management Professionals Australasia (RIMPA) to run a session at their Information On Demand conference to be held in Sydney on 31st May.

My topic for this interactive workshop will be "Data Governance: who's who in the data zoo?" (a session I previously ran at the Ark Group Data Quality Congress) and will cover the following questions:

• What is Data Governance?
• Who needs to be involved?
• Should I centralize or federate Data Governance?
• How do I get Data Governance on the business agenda?

Effective Data Governance is all about ensuring that your business is deriving maximum value from its information assets, while minimizing risk to the organisation. This requires that organisations successfully execute a number of key processes to support control, risk management, auditability and benchmarking for their data.

However, it also is necessary to ensure that the human factors at play in the organisation are successfully negotiated, and that all necessary participants are engaged to participate in the Data Governance process. 

The workshop will equip participants with the understanding of key human factors associated with a successful organisational approach to Data Governance, and focuses on practical methods and processes of building an information community that collaborates effectively to achieve better business value.

For more details, please see the RIMPA web-site http://www.rimpa.com.au/2012/info-on-demand-conference/