Archives For #ChiefDataOfficer

Each year now as I advocate for Top-down Data Leadership by the CEO and his/her Board (as opposed to Proxy Leadership as a “Data Fashion Statement”), I use the 12 Days of Christmas lyrics as a theme to mimic in getting my message out over the holidays (in small bites). 2015 was no exception and you will find below a recap of my Tweets, along with a bit of embellishment beyond the 140 character limits.

Hope you enjoy it.

On the 1st Day of #DataLeadership the #CEO confirmed to the Board his/her Full Accountability for “All things #Digital, Data & #Analytics“. This is the central tenant of the Data Leadership Nexus where leadership manifests from the existing hierarchy which has now assumed full accountability for “All things Digital, Data & Analytics”.

On 2nd Day of #DataLeadership the #CEO & Board outlined the Strategic Outcomes which #Digital, #Data & #Analytics would deliver for the Organization. These core competencies must be leveraged to create tangible outcomes for every Oganization.

On the 3rd Day of #DataLeadership the #CEO & Board set their Data-driven Core Strategy into motion across all facets of their Organization. Data-driven begins with your Core Strategy and all its desired Outcomes. Data (facts) are used to help define the Strategy, to measure its progress along the way and ultimately to characterize the Outcomes in a meaningful way.

On the 4th Day of #DataLeadership the #CEO, Board declared: “We will Transform our Organization into a Predictive Enterprise within 5 yrs.” Transformation is a journey for every Organization. You must set targets along the way and eliminate barriers to success too. This is the role of the CEO & Board and it requires Continuity of Leadership as well as Conviction to achieve the Outcome in a finite time frame.

On the 5th Day of #DataLeadership the #CEO committed the Organization to achieving broad-based #Data & #Analytics Literacy within two years. Data & Analytics must be used pervasively and not selectively. This begins with Literacy & Competencies at all Levels, especially at the top where the most value from facts, measures and insights typically manifests.

On the 6th Day of #DataLeadership the #CEO enacted the Org’s plan to be #Data-driven in All Decisions, Measures & Outcomes going forward. Being data-driven is a major commitment and requires moving from an anecdotal (gut) -based decisioning model to a fact (evidence) -based on. It must occur at all levels where decisioning is required in daily & strategic operations.

On 7th Day of #DataLeadership the #CEO vowed to use #Data & #Analytics pervasively (not selectively) in creating their Predictive Enterprise. Pervasiveness is essential to becoming a true Predictive Enterprise. Data & Analytics can no longer be “specialist functions”, and must be used by everyone in all facets of daily work. This is the linchpin of any transformation strategy used to become a Predictive Enterprise.

On the 8th Day of #DataLeadership the #CEO & Board integrated #Data, #Analytics & #Digital into their #Governance & #Risk accountabilities. Data & Analytics are core to each Organizations strategy, tactics and operations. Their use must be governed accordingly in alignment the Organizations’ overall governance model. This applies to Risk Management as well. Data & Analytics are not outliers and must be integrated into the Org’s Risk Models & related activities.

On the 9th Day of #DataLeadership the #CEO, Board & All Senior Execs began their journey to become #Analytics-Literate Leaders within 2-yrs. The central tenant of the Data Leadership Nexus is Top-down Leadership. However, you cannot Lead what you don’t understand. This requires all senior execs, board members and the CEO to become “Analytics Literate” early in the journey to becoming a Predictive Enterprise.

On the 10th Day of #DataLeadership the #CEO detailed the key elements of Orgs’ Transformational Journey to become a Predictive Enterprise. Every successful Transformation requires a road map that details the key milestones and measures necessitated to achieve the outcomes of the Strategy. These will be unique for every Organization as it maps out its journey and the Outcomes it is pursuing. 

On the 11th Day of #DataLeadership the #CEO & Board assigned #DataStewardship Responsibilities for key #Data Domains across the Organization. There are many critical Data & Analytics domains in every Organization and they must be shepherded through their lifecycle by Stewards who are fully (or partially) responsible for this task. These Stewards are typically at the mid-tier of any organization and act as Asset Managers in the typical sense.

On the 12th Day of #DataLeadership the #CEO empowered the Org to use its rich #Data & #Analytics Talent to become a Predictive Enterprise. Empowerment is essential to the success of any Transformational Strategy. It is the Trust element and each CEO & every Board must instill in the culture of the organization. Empowerment engages every single responsible party in the pursuit of the common goal of becoming a Predictive Enterprise.

Look for more postings on The Data Leadership Nexus and Predictive Enterprises over the course of the year.

All the best in 2016!

RLLeadership-picture

 

In advance of my presentation at the Data Leadership 2015 Conference in London (November 26th) entitled: “Profiles in Data Leadership”, I thought that I would set the tone by asking a fundamental question; Do you have what it (really) takes to be a Data & Analytics Leader? I hope you enjoy it.

It seems that everyone today aspires to be a Leader in whatever activity or organization that they are involved in, no matter their background, capabilities or experience.  Many endeavor to pursue the Mantle of Leadership by engaging in “soft activities” such as writing articles & blogs, social media participation, conference presentations, etc., to demonstrate their abilities & potential, but few are successful it seems. Conventional wisdom says that being promoted to Manager is a pathway to Leadership as well. I disagree with all of these approaches.

Over the course of my career I have come to this belief; Leadership is Earned, not Learned! You can educate anyone on the principles of Leadership, but that does not make them a Leader. Leadership only comes from experience, character, fortitude under fire and other key behavioral/cognitive attributes. Given all this, it brings me to the title of my column this month: “Do you have what it takes to be a Data Leader?”

Recently, Information Age announced its selections for the “Data 50”, a group of data leaders & influencers in the UK. The “50” were chosen from a group of nominated candidates submitted this past Summer (2015). The Data 50 represent an interesting cross-section of data folks in the UK from all sectors and I am familiar with a number of them.  Independent of the Data 50, I have been writing over the course of this “Year of Data Leadership (2015)” about the 8 CEOs whom I have chosen for my series; “Profiles in Data Leadership”. Not surprisingly, there is no overlap between these two groups as they do represent completely different ends of the what I refer to as the Data Leadership spectrum. Let me explain why.

At one end we have the notion of what I call “The Data Leadership Nexus”, a strategic framework for becoming a Predictive Enterprise. Central to this concept is the role of Top-down Leadership by the CEO & Board in guiding the successful exploitation of Data & Analytics by everyone across their Organization in order to make it pervasive and ultimately to create sustainable sources of Competitive Advantage. The Nexus presumes that you have a highly functioning Leadership structure in place already, which is fully accountable for strategic, tactical & operational performance in the classic sense, but has also undergone a transformation over time to be highly competent in areas of data & analytics. This Data Leadership Nexus is Transformational in approach and encompasses Executive Leadership, Core Strategy, Organizational Culture & Technology to achieve its desired outcomes.

At the other end of the Data Leadership spectrum, we have the traditional technology-focused Data Management activity within the IT Organization. Leadership here drives functional responsibilities and is focused on how to best deliver data & analytics as a service to Users and Executives. This is a very critical role in every organization and today and is often referred to as that of the Chief Data Officer. In many of these same Organizations this role may also be responsible for Data Governance activities as well as liaison with Business Units to establish SLA’s, Functional Requirements, etc. The emphasis for this role is to provide technology services & expertise in support of the Organization’s Objectives (strategic, tactical & operational).

In order for any Organization to be successful in its quest to become a Predictive Enterprise, the entire Data Leadership spectrum (both ends, much less the middle) must have inherently strong leaders in all roles that intersect with data, analytics & information governance. Whether top-down, bottom-up or middle-out in respect to the location of these roles or their span of responsibilities, every Data Leader must work from a position of strength & experience in respect to knowledge, acumen & abilities. This is a much deeper set of requirements that almost all other managerial or executive positions.

If you want to become a Data Leader (or a better one if you already are) my advice is as follows; You must be a true leader at your core, one who understands not just the technology, but the why & how of making it a core competency for your Organization in its pursuit of strategic excellence. You must be fully accountable for those who work within your span of responsibilities and lead from the heart. Finally, you must steel yourself each and every day to more worthy and capable of the challenge you have been tasked with. In the end, Leadership is not for everyone, especially those who want the spotlight on themselves constantly.

*This posting in an edited version appears as an article in the November 2015 issue of Information Age (www.information-age.com)

As we all begin to make our final plans to attend Data Leadership 2015 late in November (http://bit.ly/1YOKrJV), it struck me after reviewing the agenda once again that we have now reached a point where there are now many discrete & different forms of data being used across most enterprises (Public, Private & NFP) on a regular basis. Much of this data now comes from outside the Organization in the form of Open Data, Reference Data, Social Media Data, etc.  All of these data sources are managed to varying SLA’s and Best Practices in respect to quality, veracity, latency, etc., making them extremely suspect at times in my opinion. However, most Enterprises do not question their sources of this external data and simply embrace it for the “Richness” that it provides without consideration of the care & feeding that it has undergone over its lifetime. Why is there such implicit trust here one might ask especially in light of most Organizations’ challenges with their own data in respect to quality, etc.?

The notion of Data Leadership is one where Data, Information & Analytics are treated as core competencies by every organization. As such, they are strategic in their nature and are major leverage points for the Organization to use in creating Competitive Advantage. These core competencies rely on the fact that the data that underpins them is of the highest quality regardless of metric used to evaluate them with. This requirement transcends all industry segments and applies to Government and NGA’s alike. Bad or misleading data in respect to accuracy impacts everyone in a debilitating way. Given this, every Senior Executive has a Data Leadership accountability to make sure that the highest quality standards are maintained, even if the data is sourced from a 3rd party or from the Open Data Community. Herein lies the rub. How do you manage what you don’t control?

As data is monetized and sold by the pound by Reference Data providers,  much less as it is freed up from the government silos that it has been hoarded in for decades by the Open Data Community, it must be made “fit for purpose” and undergo rigorous conditioning to insure that it is “in shape” for consumption regardless of the use case. This is not the case today with the vast majority of what I call 3rd Party Data, most specifically what is sourced from the Open Data portals that now proliferate the landscape. Reference Data & Social Media data are better managed over their lifecycles because there was always a profit motive behind its creation, but it still has its challenges. I will leave that discussion to a future article. For now, let’s focus on the Open Data world.

Open Data now comes from both Government entities (and NGO’s) as well as Commercial interests. Both use these data sets internally to run their Organization and then “hive off” some (or all) of it for sharing with the Open Data Community. In most if not all cases, it is done as a side activity (begrudgingly) by the IT Staff who are always hard pressed to have enough staff, time & other resources to do their “day jobs”. This creates a dynamic that does not foster high quality data in any regard. To overcome this, we must have Data Leadership by those Executives who are accountable for delivering data products to the Open Data Community. They must insure that all data under their watch is representative of what would be acceptable internally by the Org, much less to a higher standard if possible.

We still live in a “Garbage In, Garbage Out” world. You cannot have successful (or believable) Analytics Outcomes without good data as foundation. Forget about creating Competitive Advantage if everyone continues to waste all their cycles on fixing bad data or questioning the source of their truths.

As there will be representatives from both the providers and the users of these 3rd Party data sources at DL 2015, I wanted to impart one basic message to all who are planning on attending; “Every type of data needs Data Leadership”.

As a community of data & analytics professionals we must insist that all data must be guided by some basic Governance principles that affect the useful lifecycle of the data assets that are being created and consumed. I look forward to discussing all of this further with everyone at Data Leadership 2015.

*This article appears in an edited form in the October 2015 issue of Information Age (http://bit.ly/1RCgB6p).

It’s been a while since my last update on the Eight CEO Leaders featured in my series; “Profiles in Data Leadership”. I am actively working on a presentation for this Fall’s “Data Leadership 2015” conference in London where I will discuss each one of these data leaders in the context of “2015 – The Year of Data Leadership” (that’s a lot of references to Data Leadership isn’t it?).

I thought that I would provide a taste of what will be discussed in November through these 3 short overviews. Hope you enjoy it.

Cheers,

Screen Shot 2015-09-14 at 11.12.32 AM

Screen Shot 2015-09-14 at 11.12.15 AM

Screen Shot 2015-09-14 at 11.11.52 AM

An old American idiom says: “You have too many Chiefs and not enough Indians”.

(*This article originally appeared in the July/August Edition of Information Age (UK) (www.information-age.com))

“This issue of Information Age begins my 3rd year as Resident Thought Leader, “Hype Debunker” and advocate for Top-Down Data Leadership. Over the past two years I have covered a variety of topics in my monthly column, many of which I believe still remain front of mind for you the reader. The one topic that continues to occupy my thinking is that of the madness known as “The Chief Whatever Officer (CWO) Syndrome”. It began with the drumbeat for having a “Chief Data Officer” and has grown substantially in all directions. We are now approaching 100 of these CWO roles, which are being advocated by every pundit, analyst, consultant, recruiter and media hack out there, along with an army of “wannabes” who feel eminently qualified to fill one of these roles. To me, it is an absurd notion that we need to define & hire/designate someone as a “Chief” each time a challenge or opportunity arises that requires Leadership attention & accountability. Isn’t this what we pay the big bucks to the CEO and his/her Team to do? Why do we need a Proxy Leader who is at best only partially responsible for a particular function associated with their role, when we have a CEO & Board who are fully accountable for all strategic outcomes? More importantly one might ask: “How did we get here?” I will attempt to answer all of these in the remainder of my column.

As way of background; over the course of management history we have had an organizational structure that mimics how humans behave i.e. hierarchically. During this time there has always been Senior Leaders at the very top of the Organization with a hierarchy of subordinates cascading down through the logical number of levels required, until you reach the front-line worker. This construct was based on the so-called Knowledge Tree as well as being driven by the practicalities of Span of Control. It has been a workable construct in spite of the dynamics faced by most Organizations in their daily operations and over a long history. Over time these Senior Leaders were denoted as “Chief Officers” in respect to their area of accountability e.g. Executive (CEO), Operations (COO), Finance (CFO), etc. Each Senior Leader had a well-defined remit of functions & activities that they were responsible for and all reported into the CEO (who in theory then reports to the Board) in terms of accountability. This structure has been the status quo in all Organizational sectors for many decades and I suspect it will be for many more to come in spite of the zeal for so-called Disruption.

What has become an affront to this harmonious organizational structure is the zeal & ferocity with which non-management thinkers have begun promoting the hiring of Chief Whatever Officers at every turn. We now live in a world where they believe that Organization’s needs handfuls of these non-executive Proxy Leaders to “own” core competencies such as; data, digital, analytics, customer, compliance, security, etc., etc., all without any final accountability. They also advocate that one Chief Whatever Officer should report to another in some bizarre construct. Enough is Enough! We need to end this tyranny and get back to the basics of Top-down Leadership.

If we truly want the evolving competencies of data, analytics, digital, etc. to be fully transformational and to use them to create sustainable competitive advantage for our Organizations then we need to “bake them into” our core strategies, their execution and the realization of all outcomes. This approach can only be successful when driven by the CEO and Board, from the very top into all levels of the fabric of the Organization. There can be no proxy substitutes for true Leadership in any Organization. It is the height of anarchy.

In all Organization’s, Strategy, Culture & Core Competencies are formulated and nurtured by the Senior Leadership Team in a coherent fashion and embraced by everyone in their daily endeavors. Creating arbitrary points of focus & soft power structures causes confusion, rancor and competition within the formalized structure of the Organization and its natural hierarchies. Success is difficult enough to achieve without creating a minefield of Organizational disconnects along the journey.

In the end, CEO’s and Boards should not be swayed to adopt Fashion Statements, False Gods or Superheroes. The Chief Whatever Officer Syndrome is an amalgam of all three with no long-term sustainable benefits.

As I begin my third year as Information Age’s “Resident Thought Leader” (www.information-age.com) I thought that I would recap my 2013 series for them entitled “The Chief Data Officer – Necessary or Not?”.

Part 1: Introduction

The role called “Chief Data Officer” was created during the past five years primarily to address the growing requirements and sensitivities of Regulatory Compliance in Financial Services & Insurance post the crash of 2008.

In each of these sectors, the need for more rigorous Governance & Provenance schemes forced many CIO’s and Chief Risk Officers to define the need for a “Data Czar”; as someone who had ultimately Accountability for insuring that all Regulatory Data was up to standards, available in a timely fashion and representative of a “Single Version of the Truth” in terms of filing veracity. This reactive approach has created a role that typically lives in IT and has neither the leverage, nor the influence to be effective over the long term.

It is my contention that if information-driven enterprises were serious about “treating their Information as an Asset” that they would have taken a business-driven approach and created this role at the C-Suite or Board of Directors level.

At the recent MIT Chief Data Officers conference in Cambridge (MA) there were many presentations and forums featuring current CDO’s. The majority of these folks came from Financial Services and Government with a smattering from other sectors. With little exception, they came to the role with the proviso that they “get the organizations’ Data in order” to meet critical reporting or analytical needs. This narrowly defined focus troubled me as it appeared that organizations were abandoning both their Data Management and Information Governance Teams in favor of a ‘Czar” who reported directly to the CIO or Risk/Compliance executive and could somehow drive different outcomes than the ones they were struggling to achieve already. One would have to ask “Is this a knee jerk response to a crisis of confidence in their data and its veracity or a real executive role with the influence to drive a “Culture of Data & Analysis?”. I seriously doubt the latter.

As a practitioner of Organizational Design I am always asked “Why?” in respect to the creation of any new executive role beyond the status quo. Organizations remain very hierarchical in structure and adding an additional component (or layer) to the well-established hierarchy is strongly resisted. Typically, this resistance is in the form of questions such as; “Why are you diluting my portfolio of responsibilities”, or “Why add another layer of bureaucracy with no real power?”. In respect to the CDO role I am at a loss as to how to answer either. Additionally, it appears that the only community who is strongly advocating for this new role is the Technical one, not Business leaders. All of the noise and posturing regarding the role is coming from technical thought leaders and consulting practitioners and not from the C-Suite or the Board. This is very problematic in terms of gaining momentum or consensus as to the value and scope of this role.

In order to distance oneself from the current hype and rhetoric surrounding the role of the Chief Data Officer you must conduct an objective analysis of the requirement for leadership and advocacy to support the concept of “Information as an Asset”. This core belief and all that goes with it is the foundational element of ‘Why do we need a Chief Data Officer”. In my subsequent writings on this subject I would like to build such an Analysis for the readers to evaluate and to use in their own efforts to support an internal discussion on “How can we manage our Information Assets over their lifecycle to create maximum enterprise value with acceptable risks?”

Part 2: Managing Information as an Asset

In the short time since my last posting there have been a spate of Chief Data Officer advocacy articles appearing across the landscape. All of these seem to want to glorify the role of a “data czar” while ignoring the current roles of Data Governance and Data Management leaders, much less acknowledging the uphill struggle to get Business Leaders to assume their accountabilities & responsibilities for the data that they use every day to support reporting, analysis & decision making. As if a single person acting as “a data czar” could somehow overcome these challenges (or provide a proxy for the lack of business leadership)?

In this installment, I would like to address these issues head-on in hopes that it may curtail some of the knee-jerk support of the CDO as a savior for all things information-related.

The essence of the challenge is this; “How do we get business leaders to accept the fact that “Information is an Asset”, and as with other assets in their enterprises, it must be managed accordingly over its useful lifecycle. Asset management is a well-understood discipline in the vast majority of enterprises today so this should not intrinsically be an obstacle. However, when you evaluate the behavior of these same organizations in respect to how they treat their information resources there is clearly a fundamental lack of appreciation and respect at virtually every level. If information was being managed as an asset we would not see such poor quality data, the use of multiple versions or the truth for decision making or major privacy breaches on such a frequent basis. It is clear to me that Business Leaders are not taking the notion of “Information as an Asset” seriously at all. To let this responsibility be relegated to IT is a disservice to the entire organization. IT has neither the resources, nor political clout to do any more than “facilitate” information management policies handed down from above.

Information Management (IM) consists of two basic categories in most enterprises today; Managing “stuff” (data) and Mitigating risks (regulatory compliance). Legions of IT workers focus on the “stuff”, while a more elite group manages the risks. The latter is typically what we call “Data Governance” (the former being Data Management) and is a relatively recent component with a spotty track record to date. In most enterprises Data Governance is still in an early stage of maturity and struggles to maintain relevance. However, we now see a trend where the Chief Data Officer is being positioned as a manager of these functions as well as the “Liaison with the Business”. This liaison role is meant to foster influence and collaboration with all information-driven areas of the business, while enhancing the delivery of information products and services to them. I have seen this model used in so-called Competency Centers with some success.

The creation of a new role called Chief Data Officer does little, if anything to change organizational behavior in respect to accepting the belief that “Information is an Asset”. Furthermore it obscures the fact that Business Leaders are not assuming their natural accountabilities and responsibilities for managing one of their most critical and leveragable assets; their information. Given the current state of the industry it appears that they would rather have IT identify a “new neck to choke” when things go awry with information resources, if there is a bad regulatory report created or even worse when a privacy breach occurs. This cannot remain the status quo. We cannot continue to create new information-related roles to abstract direct accountabilities for information stewardship from its natural owners; the business.

In my next installment I will focus on “How to create a business-lead culture of Information & Analysis within any enterprise.

Part 3: Creating an Organizational culture that treats Information as an Asset

In our Information-driven world one would expect that Executives on both the Business & Operational side of the house to naturally assume ownership (and stewardship) of this critical asset base. It seems only logical when you look at how the Treasury, Distribution, Real Estate, Fixed Assets and other related functions (which manage the lifecycle of Tangible & Intangible Assets) are located in the Organizational Hierarchy.

However, when it comes to Information (and its underlying Data), this logic appears to be out of alignment in most enterprises across the globe (A few notable exceptions might be information-centric enterprises such as Google, Amazon, Twitter, etc.).

How did we get to this logical disconnect one might ask? In my experience it has been the steady decline in the strategic role of IT, along with the acquiescence of their natural leadership responsibilities by Business Executives whom are still immature in their approaches to exploiting information resources & capabilities. These two trends have created a toxic mix of lack of focus/sensitivity combined with living in a world where “data & information are just stuff” and as such are managed to service & cost levels (by IT).

To break this cycle of behavior you must adapt your culture to treat Information as an Asset. This is accomplished by applying Cultural Adoption Methods from the discipline of Organizational Change Management (OCM). It is in essentially a “Top-Down, Bottoms-Up and Middle-Out” approach where all “influencers and owners” are engaged simultaneously. A new belief is established in everyone that this intangible asset that we call Information must be treated as a precious and extremely valuable one. A recognition must exist that the Organization succeeds or fails in large part on the Quality, Richness & Full Exploitation of its information in regards to all aspects of the business model i.e. Customer, Suppliers/Partners, Research & Development, Competitive Differentiation, Services & Products, Brand Success, Legal Mitigation, etc. Only when the entire Organization realizes and embraces the notion that “Information is our most valuable Asset” and that “Each of us has Personal Stewardship Responsibilities” can you realize the full measure of value that is manifest in your information resources.

I have successfully applied these Cultural Adoption techniques in a number of Organizations going back many years now. While simple in concept it can be very challenging to define an approach for each type of Organization that will be successful. Some early activities to help me size up this challenge include; C-Suite evaluations to define “Champions and Enablers”, The measurement of the psyche of the Organization in respect to “Ability to Adapt” and “Levers for Success” and locating hidden pockets of “Information Exploitation” to identify Change Leaders & Success Mechanisms. These evaluations allow me to size up the scope of the challenge, to define the strategy for success and to layout the integrated plan for success. The only Organizational Design component of this entire activity is the establishment/optimization of the appropriate levels of Governance required for guiding the management & full exploitation of all Information Assets over their useful lifecycle. This governance body is essential to separating Oversight (doing the right things) from Operations (doing things right) a key overall requirement. Nowhere is there a requirement for a “data czar” or “uber executive” accountable & responsible for all Data. This single point of failure approach has no place in any Organization that truly believes (and behaves accordingly) the notion that “Information is an Asset”.

The concept of the Chief Data Officer has been fostered by many within the Technology side of the house and completely ignores the central issue that the Business must assume its natural leadership accountability in managing and optimizing all Information Assets over their natural lifecycle. These responsibilities for Stewardship are lead by the business in partnership with Technology and must be embraced by everyone at a personal level in order to succeed. Only then can any Enterprise claim that they “Treat Information as an Asset”.

A 2014 Follow-on Article: “Why you still don’t need a Chief Data Officer”

For those who have followed my writings on the subject of the Chief Data Officer beginning last summer (2013), you know well that I am no advocate of this role. Having endured one wave of hype after another on this subject and being that I just attended the CDO Summit here in London, I felt that it was time for an update.

What I initially believed was a bit of overzealousness in response to new regulatory statutes (BCBS 239 Pillar II) have now become downright cynical. Every Vendor, IT analyst and CDO Wannabe is out beating the Chief Data Officer drum each day in the belief that if you say something loudly and frequently enough then it becomes the truth. To be clear, there is absolutely no justification whatsoever for a Chief Data Officer, much less the 20+ other “Chief Whatever Officers” currently being advocated.

In terms of facts, this is what a number of recent surveys (Gartner, etc.) tell us;

1.- Most CDO’s have been created out of the wreckage of failed Data Governance programs.

2.- The vast majority of CDOs remain in financial services and are a direct result of a knee jerk response to complying with the BCBS239 “data management” requirement.

3.- Virtually all CDO’s are non-executive, reporting 1-3 Tiers below the C-Suite, usually to the CIO. Few sit on the business side at an appropriate point of leverage and oversight.

4.- The typical job description for a Chief Data Officer reads as follows:

“Wanted: Knight in shining armor sitting upon a white horse. Needs to solve all data-related challenges that the CIO, Risk, Audit, Compliance, Legal, etc. have not been able to do for the past 50+ years. Must be a visionary, highly influential and yet operationally focused. The Chief Data Officer is fully accountable for the veracity and provenance of all Regulatory filings, but will have no operational authority. “

I could go on here, but suffice it to say what is being touted by all as critical to the success of Big Data & Analytics is doomed to fail for a variety of reasons.

First and foremost, the CDO’s remit as described in most cases is in total conflict with established guidelines for effective Governance (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)). You simply cannot have one leader responsible for both Governance and Operations. It is a total conflict of interest, which cannot be resolved no matter who sits in the CDO seat.

Second and equally critical, is the requirement for Business Leaders to take accountability for all of their Information & Analytics endeavors and to stop looking for someone else to do it on their behalf. For any organization to become an “Analytics-driven Enterprise” it must be have capable and competent leaders in all levels of the business. These leaders must set the tone and direction for Big Data & Analytics and drive the cultural belief that “Information is one of our most critical assets and we are accountable for its stewardship and exploitation”. IT cannot do this no matter what they call the messenger and if we don’t change this dynamic we will fail as an industry to achieve the potential that Analytics, Big Data and our Legacy data have to offer.

In summary, while many of my peers will criticize with my continued resistance to join the chorus of voices advocating for the role of CDO I cannot endorse a failed strategy when the right one continues to stare us in the face. Success with Big Data & Analytics can only come from top down leadership by the Business side of the organization.

Footnotes:

Organizing for Success. For those experienced in Organizational Dynamics and Corporate Governance the notion of a ‘Chief Whatever Officer” is a hard one to support. While being noble in its cause, these “czar-like” roles are counterproductive to the outcomes desired and fly in the face of governance practices and ultimately create chaos and rancor. If they are absolutely necessitated to help bring focus and critical mass to an emerging focus area then they should be designed to “self-expire” in 18-24 months at the outside. Short-term needs cannot outweigh the long-term stability of the organization and its culture.

Why do Data Governance Programs continue to fail so spectacularly? Recent surveys show that many DG Programs have either failed to meet their stated goals and objectives or have receded into the status quo of the past. The principal reasons are directly attributable to; 1.- Being located in and lead by the IT organization.   2.- Being unique and outside of existing Corporate Governance & Risk Management endeavors and 3.- Lack of or waning sponsorship by Business Leadership. The solution to this challenge is not to re-group and create a “data czar”, but to drive the belief that “Information is an Asset” from the business side where all Assets have traditionally been managed and nurtured.

Finally, a January 2015 column focused on “Making 2015 a Year of Data Leadership”.

As the focus of industry hype moves from Big Data to the Internet of Things we have a unique opportunity to turn our attention to one of the underlying disablers of broad success in using data & analytics to their full potential in any Organization; the lack of Top Down Data Leadership. During the past couple of years we have seen a fever pitch in Organizations’ anointing proxies to the status of superheroes in respect to Data & Analytics Officers. While there have been many such appointments, most are now being scrutinized as the widening gulf between the rhetoric and reality becomes more apparent. This effort to create “Chief Whatever Officers” has been foolhardy in my opinion, as it has completely dodges the need for the Board and CEO to become directly accountable for the Organizations management and exploitation of data and their leverage of analytics across the enterprise to create a “culture of evidence-based decision making”. My aim in 2015 is to change this dynamic.

In 2015, I would like to create much more than awareness of this underlying challenge, but to make actionable its solution in what I am calling “The Year of Data Leadership”. In the Year of Data Leadership I would like every CEO and their Board (Public, Private, NGO, Not-for-Profit, etc.) to accept the fact that they (and Not IT) are fully accountable for “all things data and analytics”. I want them to embrace this accountability and make it core to their Strategies and Operational Plans. I am challenging them to step up to this leadership mantle and provide the Organization with a plan of action to put it on a trajectory to becoming a “Predictive Enterprise” within 5 years (2020). This Decision Making transformation would move them from being gut-based decision (relying on experience and anecdotes) making Organization to one where evidence (facts, decision science and the appropriate amount of intuition) guide all decisions at every level.

This is an ambitious undertaking for even the most agile of Organizations, but a necessary one if the competitive advantages of a Predictive Enterprise are ever going to be realized. To accomplish such a Transformation I strongly recommend approaching it as follows;

1.- Immerse the CEO, Board & Senior Executive Team in a series of Boot camps designed to immediately (and measurably) raise their acumen and competencies in the domains of Decision Science & Analytics, for “you cannot lead what you don’t understand”.

2.- Make Data, Information & Analytics Core Competencies in your strategic and operational endeavors. Make then pervasive and break down silos and centers of excellence to make capabilities mainstream and ubiquitous to all aspects of your operational domain. This will require investment in staff development and in the early stages may require shadowing of staff with outside experts, mentors and coaches.

3.- Manifest Cultural Adoption by all members of the Organization of this new strategic paradigm i.e. Becoming a Predictive Enterprise. Organizational Culture is “the shadow of the CEO, Board and Senior Executive Team”. It is found in every corridor and behind every door across the enterprise and is molded from the Top-down. To begin to change a culture requires Top Down Leadership to changes it behavior and modify all cultural norms and activities. The entire Leadership team must engage with the Organization directly (with support by Change professionals) to lead by example in regards to championing the new direction and its virtues.

This three-pronged approach will produce the maximum results in the shortest period of time and requires close coordination, substantial investment of time and resources to succeed. It is truly transformational and should not be a sub-priority to other Enterprise-wide strategic and operational initiatives.

The Nexus of Top-Down Leadership, Cultural Adoption and the enabling Core Competencies of Data, Information & Analytics creates a unique strategic framework for becoming a Predictive Enterprise. All components are required to work in concert to achieve a true transformational outcome within any Organization who wants to fully exploit data & analytics for competitive advantage.

Going Forward:

In my future writings & presentations I will continue to advocate for what I see as the best approach to achieving the goal of becoming a Predictive Enterprise, one where Data Leadership manifests from the Top-down. I am confident that others will join in this call as the False Gods of Data and Fashion Statements fall by the wayside and a more realistic approach is embraced by all.

I encourage everyone to subscribe & read my monthly column in Information Age as well as to continue to follow this this blog for future updates.

RL

 

 

 

Each day we seem to be bombarded with more and more hype about the need for Proxy Leaders aka Chief Whatever Officers and other Fashion Statements such as Data Scientists. There are specialist recruiters, IT Analysts and Conference organizers who promote these roles along with a chorus of IT people who seem to not have much respect for their boss, the CIO. Frankly, I am sick of hearing/reading all of it and in spite of my best efforts to tune out these voices out they seem to be everywhere. It appears to me that the entire vendor, analyst & pundit community have sold the farm on the success of these IT Superheroes in spite of a legacy of more than 50 years of failure by IT to lead in respect to Data, Information & Analytics. I am not one of these “true believers in the next data prophet”. For my money when it comes to creating effective Data Leadership  I am going to bet on the traditional organizational hierarchy which begins with the CEO (in partnership with his/her Board). To that end that is why I have devised The Data Leadership Nexus in the fashion that I didFor those who have been following my Data Leadership Nexus articles, blogs and tweets you know that I have been promoting the notion that “2015 – The Year of (Top-Down) Data Leadership”.

In support of this, I have been working with Clients and other Like-Minded Thinkers to develop 5-year plans for CEO’s & Boards to transform their Organizations into Predictive Enterprises within this timeframe (if not sooner). To help better understand what that journey looks like from the perspective of those who have already undertaken it (albeit on a slightly different path at times) I am authoring a new series which profiles these Data Leaders.  It is loosely modeled after JFK’s book entitled “Profiles in Courage” something that I was inspired by in my youth.

I have several of these profiles in development now. The first two out of the gate will be;

  • Maryland Governor Martin O’Malley the CEO behind CitiStat (Baltimore) and StateStat (Maryland)
  • Brian Cornell, the new CEO of Target Corporation
  • Jim Smith, CEO of Thomson Reuters
  • Alistair Currie, CEO/COO of ANZ Bank

I believe that you will find all of these profiles very compelling and all will run counter to the many waves of hype that you are subject to on a daily basis in respect to data & analytics advocacy and management. Look for these postings in the coming days. In the meantime you can Recap (or read in full detail) all aspects of The Data Leadership Nexus starting here: (https://infomgmtexec.me/2014/09/16/recap-the-data-leadership-nexus/)

Stay Tuned!

Richard

“Courage profiles” by Source. Licensed under Fair use via Wikipedia

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/)

 

I have a number of Thought Leadership items slated for going live in August. Below is a listing of their titles and publication dates.

  • August 1st (WordPress Blog Series): “The Chief Data Officer: – Superhero, False God of Data or Fashion Statement? – Reflections on the MIT 8th Annual CDO & IQ Symposium” (Cambridge, MA) (www.infomgmtexec,me)
  • August 5th (WordPress Blog Series): “Overview: The Data Leadership Nexus” (www.infomgmtexec.me)
  • August Early (approx) – IBM Big Data & Analytics Hub: The Privacy Corner – “Privacy and Social Experimentation” (www.ibmbigdatahub.com). If you want to follow all of my blogs on the Big Data & Analytics Hub use this link to set up an RSS feed: (http://www.ibmbigdatahub.com/blog/feed/richard-lee)
  • August 11th (WordPress Blog Series): “The Data Leadership Nexus: Leadership Requirements in the Predictive Enterprise” (www.infomgmtexec.me)
  • August Late – Sept. Early: Information Age: Monthly Column – “The Data Leadership Nexus” (1st installment in this series) (www.information-age.com)
  • August 30th (WordPress Blog Series): “The Data Leadership Nexus: Organizational Change” (www.infomgmtexec.me)

Keep an eye out for calendar updates and additional postings.

Enjoy!

RL

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.