Archives For Information Governance

October & November will be frantic months of activities with a strong focus on Conferences. Check back often for updates and additions. In most cases I will be Tweeting and Blogging live from each conference;

Conferences:

Association of Change Management Professionals (ACMP): “2014 Change Connect Symposium” – October 1-2 – Microsoft Campus Commons (http://www.acmppnwnetwork.org/?page_id=326)

Digital Analytics Association (DAA): “Monster Analytics Mashup” – October 16th – Microsoft Conference Center (http://www.digitalanalyticsassociation.org/calendar_day.asp?date=10/16/2014&event=260#.VCWfF8LF-yM)

Information Age (UK): “Data Leadership 2014” – October 30th – The Grange Tower Bridge Hotel (London) (http://www.dataleadership.co.uk) :

Keynote: “Embracing The Data Leadership Nexus for Strategic Success”

UK Open Data Initiative: “ODI Summit 2014” – November 2-4 – British Film Institute (London) (http://summit.theodi.org/)

Articles:

IBM Big Data Hub: “The Privacy Corner”. “Discrimination and Other Abuses drive the Need for Ethics in Big Data” (http://ibm.co/1sKmkx0)

Information Age (UK): “Transforming into a Predictive Enterprise” (http://www.information-age.com/technology/information-management/123458506/holy-grail-big-data-becoming-predictive-enterprise)

Information Age (UK): “The State of Open Data” (November 15th (URL to be posted at time of publishing)

IBM Big Data Hub: “The Privacy Corner”. “Have we already lost the Privacy battle?” (November – Date TBD)

The Data Leadership Nexus (Blog):

“Reflections on Data Leadership 2014” (November 4th)

“How to Successfully Execute your Transformational Plan for becoming a Predictive Enterprise” (November 15th)

“The Data Leadership Nexus: (Recap)” (Updates throughout the month) (https://infomgmtexec.me/2014/09/16/recap-the-data-leadership-nexus/)

 

The Data Leadership Nexus is a path to success when it comes to realizing the numerous business benefits of Big Data and Advanced Analytics which have been extolled by so many in recent times and yet realized by so few. It is the linchpin of your Strategic Plan for building & sustaining “a culture of analytics” to foster evidence-based decisioning, deeper & broader insights, full knowledge exploitation and optimized strategic performance while making these behaviors pervasive across your entire enterprise. In my mind it is the path to realize everything data-related that we have been working on for more than 50 years now in Management Theory, Decision Science and Information Technology.

By definition: The Data Leadership Nexus is the intersection of; Top-Down Executive Leadership, A fully aligned Organizational Culture and the full exploitation of Data, Information, Analytics to create strategic outcomes, sustainable sources of competitive advantage and enterprise value within every organization that wants to become a Predictive Enterprise.

I define a Predictive Enterprise as: “The use of Predictive Capabilities driven by data, information & analytics to; optimize decision making, facilitate strategic & operational outcomes, mitigate risks and to exploit insights across the entire Enterprise”

The Data Leadership Nexus is comprised of these basic components;

  • Top-Down Leadership (by the Senior Executive Team)
  • Data, Information & Analytics
  • Organizational Culture 

Each component was discussed in detail in previous postings. They can be found using the following links;

#: Overview & Introduction:  https://infomgmtexec.me/2014/08/05/overview-the-data-leadership-nexus/

#: The Motivation behind The Data Leadership Nexushttps://infomgmtexec.me/2014/07/25/data-analytics-leadership-missing-in-action/

#: Top-Down Leadership:   https://infomgmtexec.me/2014/08/11/leadership-requirements-in-the-predictive-enterprise/

#: Organizational Culturehttps://infomgmtexec.me/2014/08/28/the-role-of-organizational-culture-in-the-predictive-enterprise/

#: Data, Information & Analyticshttps://infomgmtexec.me/2014/09/09/data-information-analytics-as-core-competencies-in-the-predictive-enterprise/

#: Additional Background Material: “Transformational Leadership for Big Data & Analytics Success” (Three-part series): 

  1. https://infomgmtexec.me/2014/06/27/transformational-leadership-for-big-data-analytics-success/
  2. https://infomgmtexec.me/2014/07/11/transformational-leadership-for-big-data-analytics-success-part-2-establishing-top-down-accountability/
  3. https://infomgmtexec.me/2014/07/20/transformational-leadership-for-big-data-analytics-success-part-3-organizational-design-cultural-adoption/

In future postings I will discuss; “How to Build & Successfully Execute your Transformational Plan for becoming a Predictive Enterprise using The Data Leadership Nexus as a Strategic Enabler”. 

I have a number of interesting Blogs, Articles and Tweet Storms coming up this month. I have listed them in chronological order. Keep an eye out for updates over the course of the month.

Blogs:

Recap: “The Data Leadership Nexus”(IMECS Blog: http://www.infomgmgexec.me)

“Data, Information & Analytics in The Data Leadership Nexus” (IMECS Blog: http://www.infomgmtexec.me)

“Privacy and The Internet of Things (IoT)” (The Privacy Corner: IBM Big Data & Analytics Hub. http://www.ibmbigdatahub.com/blog/privacy-and-internet-things 

Articles:

“The Data Leadership Nexus as a Strategy” (Information Age (UK) Magazine. http://www.information-age.com).

Tweet Storms:

Second NIST Privacy Engineering Workshop (IAPP Conference, September 15-16, 2014, San Jose, CA) – Follow #priveng for all relevant Tweets.

Conferences:

“Cyber Threat: Evolving Best Practices in Framing and Managing the Risk” (NACD – Seattle, September 23, 2014)

“Communicating Cyber Risk to the Board” – (ISACA – Seattle, September 23, 2014)

The notion of The Data Leadership Nexus has five basic components;

1.- Top-Down Leadership (by the Senior Executive Team)

2.-4.- Data, Information & Analytics

5.- Organizational Culture 

In this posting entitled,“Organizational Culture” I will discuss one of the most widely mis-understood and under appreciated elements in creating a Predictive Enterprise, that of Organizational Culture and the imperative to change it from being data & analytics illiterate to one where information & analysis is used by everyone to drive each decision and to facilitate every strategic & operational outcome.

The Culture of any Enterprise is based on the long-term strategic direction that the organization has undertaken over the course of its history and the collective experiences along the way. It is shaped daily by the actions and activities of the Leadership Team who have guided this journey. Organizational Culture is the shadow of the Chief Executive Officer (and Senior Executive Team) and is found behind every door and felt down every corridor in the Organization. It is the single thread that ties everyone together within any Organization. Given this, Organizational Culture is the most important component of The Data Leadership Nexus that must be leveraged in order to transform an organization into a true Predictive Enterprise.

As one would expect this Cultural Adoption (transformation) must be driven by the Top-Down Leadership of the CEO and his or her Senior Executive Team. We discussed in my last segment on Top-Down Leadership just how essential it is for the entire Executive Team to “walk the talk” in respect to becoming a Predictive Enterprise. This will manifest from their own competencies and acumen in data & analytics and how they position the use of them in every strategic and operational endeavor that the Organization is involved in. Their Leadership comes from these strengths and their lock-step application of the strategic constructs of;

  • “Information as an Asset”
  • “Evidence-based Decisioning”
  • “Information-driven Risk Management”
  • “Competitive Advantage through Advanced Analytics (everywhere)”

Once Top-Down Leadership has set the tone and direction for the “data & analytics way-forward” by their own personal commitments (via OBM goals) and demonstrated actions, then the Organization must address how to “adapt” the Current State Culture into the Future State model. Many Organizations would tend do apply the traditional Change Management (CM) techniques of; Communications, Training & Readiness Preparation and call it a day. In my experience this will not work by itself. Cultural Adoption is not Change Management!

Cultural Adoption requires Engagement, BootStrapping and Practical Application endeavors to augment traditional CM. It requires the Top-Down Leadership Team to directly Engage with the Organization at all levels. This is not a hierarchical exercise, where “orders from the top” can be cascaded down, but a lateral one where these leaders bring their messages directly to the Front Lines of the Organization,  while personally demonstrating to their own subordinates the commitments that they have made to the successful Transformation into a Predictive Enterprise and all that it portends for success. These Engagement efforts must be genuine and felt by all. The entire Top-Down Leadership team must be in sync working in unison towards the common goal and outcome.

In parallel with Engagement, the Organization must BootStrap everyone’s abilities & understandings as to what becoming a Predictive Enterprise entails and how each of them will play a role regardless of job description. Everyone must be on-board with the plan and approach and be actively participating in the pursuit of the transformational outcome via Training, Mentoring, Coaching & Hands-on Instruction. This will create Cultural Adoption momentum that can be sustained through the continuous application of Engagement and bolstered through the daily Practical Application of data & analytics to every decision and pursuit of operational outcomes.

Practical Application is one of the most critical activities because it intersects with Relevance. For any Culture to Adapt there must be strong Leadership, the attainment of Competencies and Understandings as to the Future State Direction, but also Relevance to them personally. Whether a Mature Enterprise or Start-up each member of the Organization must feel a sense of purpose in order to be an active member of the Culture, much less a contributor to the successful outcome of the transformation strategy. It is essential for all levels of Leadership to empower all members of their Organizational Unit to be contributors to the notion of being a Predictive Enterprise. In most cases this will require a complete re-evaluation of roles and responsibilities such that decision making and insights analytics are core to each Information Workers daily activities.

To become a Predictive Enterprise you need committed Top-Down Leadership and a Culture driven by the pursuit of a common strategy & its goals to then fully exploit your rich Data & Information Assets and Deep Analytics Capabilities. In this posting I have endeavored to provide a thin veneer of the requirements and complexities in adapting your Organizational Culture to become a Predictive Enterprise. It is one of the most significant investments in time, energy and resources but an essential one in becoming a Predictive Enterprise.

In my next installment of The Data Leadership Nexus I will explore for my readers the more familiar areas of Data, Information & Analytics, but from what most will regard as a very different perspective than other Thought Leaders.  Look forward to seeing it soon.

RL

 

 

 

In my last post, I laid out the notion of The Data Leadership Nexus and its five basic components;

  • Top-Down Leadership (by the Senior Executive Team)
  • Data, Information & Analytics
  • Organizational Culture 

I will discuss the most important component of The Data Leadership Nexus in this posting entitled, “Leadership Requirements in the Predictive Enterprise”. 

Much has been written about the criticality of strong Leadership. It is an essential requirement to becoming a Predictive Enterprise. One of the foremost thinkers on Leadership, Warren Bennis passed away just last month (July 2014). He chronicled the attributes and characteristics of “The Modern Leader” in his many books on the subject, but his basic conclusion (in my words) on the role of Leadership was; “We can neither transform, nor reach successful strategic outcomes without strong and effective Leadership from the Top Down”. It is on this point alone that I continue to bristle against the growing advocacy for “Chief Whatever Officers”.

No matter the domain (data, data protection, data security, analytics, digital, etc.), I do not agree with the constant drumbeat to appoint a “czar” to fix (or enhance) a function which is the direct accountability of the Senior Executive Team (whom I will refer to as the SET going forward). What is required here is to address the data, information & analytics shortcomings of the Current Generation of Senior Executives in respect to the Key Attributes of; Education, Acumen, Competency & Operational Experience such that they (and only them) can take assume their critical (and natural) role in the The Data Leadership Nexus. We cannot continue to run away from the real problem as to why we are not realizing the benefits from 50+ years of investing inordinately in data, information & (most recently) analytics. Clearly, the CIO (in all forms and incarnations) has not been able to accomplish this and no type of proxy will be able to be successful either. It is simply a waste of precious time and resources to go down this path (CDO, CAO, etc.) and then discover it didn’t work (once again).

Let’s get started. As some of you may have gathered from my recent article in IBM’s Data Magazine ( http://bit.ly/1vvhwea ) the vast majority of today’s Senior Executives do not have all (or even some) of these major attributes in their favor when it comes to Data Leadership. Suffice it to say that these were not essential as they climbed the organizational ladder and honed their Executive skills over the past several decades. However, because of these shortcomings they now find themselves acting as cheerleaders for strategies and capabilities that they do not really understand in detail, nor can lead from a position of strength. This has lead to the use of a crutch by appointing “a czar” (proxy) or being too timid altogether in pursuing sound strategies and outcomes (i.e. limited capital & manpower investments, short-term benefits realization horizons, being “gun shy” of risks, etc.). This short-sightedness has not compensated for their lack of Education, Acumen, Competency & Operational Experience in data, information & analytics and  is subjecting them to the fundamental executive shortcoming of: “You can’t lead (to success) what you don’t understand”.  How we overcome this challenge is the critical path to success in achieving the Leadership component of The Data Leadership Nexus.

The most immediate path to overcoming these Leadership challenges is to bootstrap all of the required attributes for each member of the Senior Executive Team via Mentoring, Coaching, Advisory activities and Academies/Boot Camps. Time is precious with each of these SET members so a personalized plan must be developed and executed in a fashion that demonstrates real-time progress and an acceleration of results to get to a level of capabilities and understandings consistent of the needs for true Data Leadership. These plans will then have a long-range view in order to maximize and sustain results. There are many Boutique Tier 1 & Tier 2 consultancies who have the practice capabilities to fill these requirements for their clients. Most realize, along with myself that it is essential to transfer the required domain knowledge and skills to SET members to achieve strategic success for the Client Organization. At the end of the day, The Client must lead with Advisors/Consultants providing a supporting role in the background. While these boundaries blur at times, it is the most proven path to success in both the short and long haul.

Most importantly we must better prepare the Next Generation of Executives for their own Data Leadership roles by baking all of these same attributes into every aspect of their personal and professional development activities such that they too can assume the mantle of leadership when it is their time and be fully prepared (and tested in advance) for it.

It’s a challenge to provide the necessary detail of the path forward in a short posting, but I hope that I have conveyed not only the necessity of Top Down Data Leadership, but the urgency of addressing the current shortcomings in today’s Senior Executive Teams such that they can assume this accountability along with all of the others they currently have.

In my next posting I will jump down our list of Basic Components to #5 – Organizational Culture. It is a companion to Top Down Data Leadership and is the reflection of how effective and persuasive that the Senior Executive Team is in both articulating and ultimately executing the Organizations’ Data, Information & Analytics Strategies & Tactics. Look for this next posting sometime soon.

Richard

 

Last week I attended MIT’s annual confab on Chief Data Officers and Information Quality in Cambridge (MA). I’ve been to this event before and have watched it grow from an annual retreat on the subject of Information (and data) quality to what I now regard as a “CDO Love-fest”.

My quest in attending this year’s event was to answer this question: “What is a Chief Data Officer; Superhero, False God (of data) or Fashion Statement?”

My answer based on all that I heard and observed is quite straight-forward: It’s a Fashion Statement and here is my rationale for believing this.

A bit of background first however.

  • The Financial Services community has lead the charge in advocating and anointing Chief Data Officers to date. All of the CDO’s appointed are in reaction to Basel Committee for Banking Supervision (BCBS 239 – 2013 “Principles for effective Risk Management (data aggregation & reporting”. http://www.bis.org/publ/bcbs239.pdf ), a critical component of the new regulatory framework post the Banking Collapse of 2008. The role as defined is to coordinate Governance & Provenance activities across disparate components of the organization to ensure timely and accurate Risk data for modeling, stress testing and regulatory reporting.
  • The Government Sector has appointed the second highest number of CDO’s in response to the various Open Government Data initiatives across the world. These CDO’s are acting as coordinators and evangelists for the sharing and leverage of Government data (Federal, State & Local) with Citizens, Entrepreneurs and Industry. Their primary role is to break down internal barriers to sharing all types of Government data and to foster standardization of practices and data formats.
  • The remaining Chief Data Officers are spread across a wide-range of Industry Sectors with Technology, Advertising & Media and Science-driven (i.e. Pharma, Life Sciences, Medical Devices, etc.) being predominant. Their role is to foster broader leverage of data assets within their Organizations as well as to foster a culture of analytics and evidence-based decision making.

My Three Rationale for believing that The Chief Data Officer role is a Fashion Statement:

1.- The motivations behind appointing a Chief Data Officer in all the segments listed above (much less others) is indeed noble, but is not based on sustainability beyond accomplishing the initial (albeit Herculean) tasks assigned to the role. The notion that you can appoint a “Chief Whatever Officer” to any role within an established Organizational Hierarchy is a foolhardy one at best. Authority manifests from a top-down basis beginning with the CEO and the Board. It cascades down to areas of Functional Responsibility defined by the type of Organization and Model that it is structured around. It then further cascades down (layer by layer) to Supervisory and Front-Line Staff. To imagine that you can insert some type of a “Czar” in the middle of this hierarchy who has responsibilities in all directions, but not the Executive Authority is nonsensical at best and reflects the fact that this role was neither well thought out in advance, nor meant to be anything more than a knee-jerk response to impending regulation or long festering problems with data management.

2.- The CDO role has been positioned as  one where it has responsibility for Data Management & Data Delivery as well as Data Governance. This is a clear violation of the Prime Directive of Organizational Governance i.e. Independence (much less Transparency). You cannot Manage and Govern within the same reporting structure (per the OECD “Principles of Corporate Governance”, The Turnbull Report “Internal Control: Guidance for Directors on the Combined Code”, The BIS “Enhancing Corporate Governance in Banking Organizations” and ISACA’s “Control Objectives for Information and related Technology (COBIT)). Those who advocate for the CDO role and its ‘czar-like” structure seem to have no regard for this fact and continue doing it as part of the broader advocacy campaign for Big Data, Data Scientists, etc. where “if you say it loud enough and frequently enough then it becomes its own truth”.

3.- The Chief Data Officer role as described in the numerous publications of the day and by its advocates is centered on the notion of “all things data” in regards to remit, but for the most part remains part of the IT Organization at a subordinate level to the CIO. In spite of the CIO not having been able to solve all the challenges of data management, data delivery and data governance over the past 50+ years there is a fantastical belief that this new role will easily surmount these same challenges while operating within a lower echelon of responsibility. Really? This is truly the most farcical aspect of the “CDO Value Proposition” as it is espoused (chanted) by its “true believers”.

As I indicated earlier, my quest in attending the MIT CDOIQ Confab was to answer the burning question of “Is the Chief Data Officer a Superhero?, a False God (of data)? or a Fashion Statement?’. No one so far has shown any real superhero characteristics that I can detect (i.e. shameless self-promotion is not a superhero virtue) and nobody exhibits any God-like capabilities that I have seen so far (False or not). Given the attrition rate that seems to be rising for CDO’s I would imagine that this is another confirmation of that fact. However, I have seen “The Rise of the Chief Data Officer” as a clear Fashion Statement by many organizations who want to be perceived as “innovators in Big Data, etc.” and are using the appointment of a CDO to foster their agendas and heighten their marketing rhetoric. In the end, no matter how you might characterize the role (or alter ego) of the Chief Data Officer it is neither sustainable nor a success mechanism to solve the many challenges in Data Management, Data Delivery and Data Governance that face us. It will not lead your Organization into the “Age of Analytics” and cannot influence your Organizational Culture to become an “Evidence-based, Predictive Enterprise”. These capabilities can only come from a Structure & Strategy that is “Top-down Accountable and a Fully-aligned Organizational Culture”.

In my new thought leadership series entitled The Data Leadership Nexus (the intersection of Data, Information, Analytics, Leadership & Culture to create strategic impact, differentiation and enterprise value within every organization) I will espouse my belief that the lack of a Data Leadership Nexus represents the single biggest challenge within each Organization in realizing the benefits which have been extolled about Big Data and Advanced Analytics. It is also the linchpin for establishing “a culture of analytics” and making it pervasive across each and every enterprise.

Look for the 1st Installment in this series early in August. It is continuation to July’s “Transformational Leadership for Big Data & Analytics Success” series.

 

Churchill_V_sign_HU_55521As many readers of my articles, blogs and other social media postings well know I am a strong advocate for Business Leaders taking full accountability for all of the Big Data & Analytics strategies & initiatives employed across their enterprises. This accountability manifests from the fact that they are not only positioned at the pinnacle of all strategic endeavors within their organization, but have full responsibility for the stewardship of all Assets as they are defined in both a tangible and intangible fashion. Having said this the $64,000 question that lingers is: “Are they prepared, much less competent enough to take on this accountability?”. The answer for the most part is a resounding NO.

Why is this? As I outlined in my June 2014 article in IBM Data Mag (http://bit.ly/1vvhwea) and April 2014 article in Information Age (http://bit.ly/1j16Vk6), the paramount issues regarding the successful adoption and exploitation of Big Data & Analytics are two-fold: Business Leadership Shortcomings & Lack of Cultural Adoption. Both are very much inter-related and one takes its cue from the other i.e. Culture follows Leadership for the most part. The articles speak to the specifics in more detail than what I will address here, but let me excerpt a few salient quotes;

  • “Today’s Executives & Managers are trained primarily in Operations, Finance, Marketing & Sales, along with a bit of Strategy thrown in for good measure. If you review the profiles of the vast majority of senior executives about 50% have an advanced degree in their field of expertise (MBA, JD, CPA, etc.) but virtually none have been schooled in Decision Science, Information Theory, Analytics or Risk Management.”
  • “Organizations’ remain hierarchical in both structure and cultural behavior today. To change either of these requires engaged & competent Senior Executive teams who are committed to the outcome and will influence & align behaviors to support it.”
  • “The Big Data & Analytics paradigm is based on the notion that Organizations must more fully exploit their information assets and move to a culture of fact-based & data-driven decisioning in order to create new sources of sustainable competitive advantage in a disruptive world around them. To accomplish this, you clearly must engage all elements of the organization, not just a select few. Everyone must make this cultural shift away from hierarchical thinking & “gut-based” decision making to one where the full hierarchy is empowered based on their role & responsibilities to perform analysis and to make decisions as close to the “customer” as possible”

Based on all of this, I will get back to the theme of this posting; “The need for true Transformational Leadership to insure the pervasive success of Big Data & Analytics”. This was the message that I hammered on during this week’s #CXOAnalytics tweetchat with Tom Davenport and John Lucker (Deloitte, who sponsored the tweet-up) and will continue to reinforce at the upcoming MIT #CDOIQ event as well as in my presentation at October’s “Data Leadership 2014” event in London (http://bit.ly/1wFl2n2). I cannot emphasize to everyone enough that we are not going to solve this challenge by appointing Chief Data Officers, Chief Digital Officers, etc. to act as “Communicators and Influencers” between the IT Organization, Risk Management and Business Leadership. No matter what the pundits say and prognosticate, it is not a sustainable model and distracts from the true issue at hand – “Getting Business Leaders to rise to their Accountabilities”.

In my management consulting experience, much less as an executive in senior roles across my career, I have never seen Business Leaders shrink away from the opportunity to take on more and more strategic responsibilities in order to grow their portfolios as well as to deliver transformational results to their business. So why are they not taking ownership of Big Data & Analytics? We know that they are out there cheerleading these efforts based on customer testimonials and event presentations, but virtually none of these same folks “own, much less are fully accountable for its success (or failure)”. Most continue to leave this to IT or some surrogate. I believe that this is due to a lack of any fundamental competency, acumen and mastery in information theory, data science and analytics which leaves them extremely deficient in confidence, vision and leadership potential. In other words, “You cannot lead if you don’t understand what it is you are asked to lead”.

To overcome this we must take actions in the following areas;

1.- Define, Fund & Execute – Mentoring, Coaching and Instructional Programs to bootstrap the current generation of Business Leaders up the level of knowledge (and confidence) required to Lead existing Big Data & Analytics endeavors.

2.- Identify candidates for Next Generation Leadership roles and Mentor & Educate them to advanced levels of competency and acumen such that as they mature into more senior roles they have both the foundation in Big Data & Analytics required, but the hands-on leadership skills (and organizational knowledge) to succeed.

3. – Engage with the Organization’s Culture at Large to make the Big Data & Analytics Vision and its exploitation “Job No.1” for everyone. This engagement requires not only top-down leadership to drive it, but appropriate Change Management and Organizational Design experts to facilitate Cultural Adoption in the Transformed Organization.

These three points each merit a number of detailed follow-up postings which i will focus on for the balance of this Summer, but I did want to live up to the spirt of my title; you need “Transformational Leadership to achieve Big Data & Analytics Success”.

Cheers,

RL


May in the UK

April 26, 2014 — Leave a comment

I will be leaving for the UK on May 3rd to spend a month in London and the Scottish Highlands. I am hopeful for good weather in both locations as it has been so miserable here in Seattle this past Spring and Winter.

During my stay in London I will be participating in the following Conferences/Events:

1.- The Chief Data Officer Summit at the Kensington Close Hotel (http://www.chiefdataofficersummit.com/) (held in conjunction w/ Data Today). I will be tweeting from the event representing Information Age and writing an article on the event for Information Age readers.

2.- The Software Defined Anything Symposium – SDx at the Langham Hotel (http://www.information-age.com/node/50422). I will be keynoting on the topic of “Privacy Engineering for a Software Defined World”. See my article in the May issue of Information Age for a preview of my comments.

3.- OVUM’s Industry Congress 2014 at the Victoria Park Plaza ( http://www.ovumindustrycongress.com ). I will be there with my Information Age hat on and will be tweeting from seminars on Data Management & Data Governance, Digital Strategies and Others topics

4.- Insurance Strategies Perspective – Solvency II Event (http://www.insurancestrategyperspectives.com/news/?page_id=25) – Central LondonI will be there to hear the latest from UK/EU Thought Leaders on the Solvency II Scheme.

Additionally, I will be meeting with colleagues from the Strategic Planning Society, the Strategic Management Forum, Source for Consulting & PCG as well as a number of Business Transformation consultancies. I am looking forward to talking shop with a number of seasoned leaders and practitioners in this space of the consulting market.

Following on to my two-weeks in London are two weeks up in Scotland where I am staying at Bob Dylan’s Highland Estate, Aultmore. (http://www.aultmoreestate.com/) in my favorite village of Nethy Bridge (where I lived in 2006-2007). I will be climbing some Munros, visiting Glencoe and Atlantic Salmon fishing for a week on the Middle Spey at Craigellachie (http://www.fishpal.com/Scotland/Spey/Craigellachie/) with Ghillie, Dougie Ross. This will be the highlight of my trip for sure. Stay tuned for updates and photos of all “The Springers” that I catch (and release) during my fishing.

Finally, I am going to do a detailed study on the new range of Macallan 1824 Series Single Malts (http://www.themacallan.com/the-whisky/the-1824-series/). It just happens that The Macallan distillery is across the River Spey from the Craigellachie fishing beats so…. I will report in on my study as it progresses.

Sláinte

MIT PhotoLast Weeks’ MIT Chief Data Officer and Information Quality Summit was a social media bonanza given the wide rage of coverage and groundswell of advocacy coming from all the camps who have a vested interest in seeing the concept of the “Data Czar” come to fruition. It was no less feverish of an event than those focused on Big Data or the role of the Data Scientist. It was truly an interesting spectacle to observe. I look forward to attending the next one of these “data fests” in the coming months.

As promised in my earlier postings on the Summit here is my Summary in the form of “Five Key Takeaways”

1.- There is no agreement as to “What is a Chief Data Officer?” It is an amorphous role description and has been designed to invoke thought rather than to define just what this executive should be Accountable and Responsible for in the grand scheme of things.

“Data is not stuff. It is the lifeblood of your enterprise and the Business is fully accountable for its Management and Leadership”

2.- A cross-sectional view of the CDO’s in attendance at the event (and a sampling of those not) indicates to me that this is (unfortunately) an IT role in most enterprises who have adopted it so far. This is disappointing, but not a surprise, given the lack of accountability for Information Management that most business leaders have failed to assume.

“IT is neither a seat of power nor influence in today’s enterprise. It is a cost center responsible for Service Delivery”

3.- Regulatory Compliance continues to be the dominant focus for all CDO Discussions and Activities. Keeping their CEO from being broadcast live during their “perp walk in his/her orange jumpsuit” for failure to accurately report on SARBOX, Dodd-Frank, Basel III, etc. is the major motivation for most CDO’s in Financial Services today.

“Risk and Compliance activities can be sources of Competitive Advantage for many enterprises if addressed as “strategic and core” rather than “necessary and evil” by the Organization and its Data/Information strategists and practitioners”

4.- MIT at large is studying (and experimenting with) the Chief Data Officer phenomena very closely. Using “Big Data” sources such as Interviews, Surveys and Social Media they are building a very detailed view (and analysis) of “The What and the Why” around the CDO and Data Scientist frenzies. Their “Cube” model (see my last posting) is a very interesting endeavor in respect to behavioral analysis and the tenants of good organizational design.

“To design a future state Organization focused on creating and embedding a culture of Information Management, Exploitation and Stewardship within it requires a deep understanding of the psyche of the current organization and its ability to change and adapt”

5.- The MIT CDO and Information Quality Summit has its roots in the study and analysis of Data Quality. It has been around for many years now and has only recently added the context of “Chief Data Officer” to its remit. However, the need to radically improve Data Quality has never been more paramount across all enterprises. We have yet to take this matter seriously and continue to treat it as a downstream activity or more cynically as “A hazard of doing business”. The more that we focus on the bright shiny objects of Big Data, Data Scientists, Chief Data Officers, etc. the less that we want to sustain the need to be ever-vigilant on improving Data Quality over the entire lifecycle for Information. We seem to have relegated ourselves to creating more of the same low quality data to attempt to analyze and make decisions from.

“Fundamentally, most data used by Organizations for Decision Making, Reporting and Insights/Analysis is suspect at best. We don’t understand its Provenance and resist all forms of Governance in terms of acceptable usage and behavior”.

As a final note, I will be writing a series of articles on the Chief Data Officer role for Information Age ( http://www.information-age.com/ ) over the coming months as well as speaking on it at upcoming industry events in the US & UK.

Stay Tuned!

Day 3 - MIT Chief Data Officer & Information Quality Forum

MIT Researchers explain their “CDO Big Data Cube” model for the types of Chief Data Officers based on their Interviews, Survey Responses and Other Contributions.

Their core definition of the CDO is an individual who has the expertise to adequately Lead and Administrate these 4-Critical Dims:

1.- Data Quality
2.- Data Governance
3.- Data Strategy
4.- Data Architecture

While these are critical elements of what I call an “Information Management Executive” (and many are now calling Chief Data Officer), there are several others that are just as important;

5. -Executive Leadership and Administration
6.- Communications & Collaboration Excellence
7.- Political Astuteness

All of these critical capabilities manifest into the “the entire package”. Many at this week’s conference doubted the need for deep domain skills as found in points 1-4, but all believe that 5-7 were essential to success. I believe that all are required as Leadership must be demonstrated on both fronts (Business & Technical).

In my next posting I will summarize the Forum altogether and provide my viewpoint on the need for both a unified vision and definition of this critical role no matter how you refer to it.

Standby!