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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

 

 

 

As it has been some time since I posted on The Data Leadership Nexus and Profiles in Data Leadership I thought that I would share with my followers the presentation on these topics that I recently made at the PASS Business Analytics Conference in Santa Clara, CA.

You can view the presentation on SlideShare via the following Link:  http://www.slideshare.net/RXLee1/bac2015-richard-leedataleadershipnexusf

Notes are included on the side as you view the presentation.

Enjoy!

Richard

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

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

 

Nexus (noun). “a connection or series of connections linking two or more things”.

Predictive Enterprise (noun). “The use of predictive capabilities (data, information & analytics) to optimize decision making, mitigate risk and exploit insights for competitive advantage”

Anyone who has read this blog and my many articles in Information Age (www.information-age.com) on the subject of the Chief Data Officer (and its many variants i.e. Chief Analytics Officer, Chief Digital Officer, etc.) over the past year or so is no doubt quite aware that I am neither a fan, nor supporter of the notion of a “Data Czar”. I have attended numerous conferences on this topic and have read the entire litany of rationalizations written by so many out there as to why this role is critical in today’s enterprise. Everyone, except me it seems, is full enamored with this notion and are all happy to cheerlead its success even if they don’t have one of their own yet (you know who I am referring to here). I myself have decided to take a different path than the rest of the pack.

Having pondered, much less experienced first hand the challenges of “How to evolve into a Predictive Enterprise” I want to address the three essential challenges associated with this journey; Executive Leadership, Strategy and Culture. Each provides a critical element of success and yet have been left out of much of the Data & Analytics conversations to date (I touched on all three in my last blog series on “Transformational Leadership for Big Data & Analytics Success”). My aim now is to change that and make them front and center in the discussion going forward while combining them with the technology components of Data, Information & Analytics.

When I was developing the notion of The Data Leadership Nexus in my mind I was focused on how to bring all of the key components together in a way that would ultimately create an aggregate response to the needs of a Predictive Enterprise. The most obvious components of the Nexus are the ones that most everyone dwells on; Data (big and small), Information (data with appropriate context) and Analytics (statistical, descriptive, predictive & cognitive), with the less-obvious being the three critical enablers of Executive Leadership, Strategy and Culture. All are not necessarily equal in significance at any particular point along the Predictive Enterprise journey, but all are necessary nonetheless.

For the moment my working definition of the Data Leadership Nexus is as follows;

The Data Leadership Nexus connects Data, Information, Analytics, Executive Leadership and Organizational Culture to create strategic impact, differentiation and enterprise value within every organization striving to become a true Predictive Enterprise). The Data Leadership Nexus represents the single biggest opportunity to realize the benefits that have been extolled about Big Data and Advanced Analytics and is the linchpin for establishing “a culture of analytics” which fosters evidence-based decisioning, deep insights, full knowledge exploitation and optimized strategic performance while making all such activities pervasive across their enterprise. To me it is the realization of everything data-related that we have been working towards for more than 50 yrs. now in Management Theory, Decision Science and Technology.

Having established the definition and rationale for The Data Leadership Nexus, the next step is to define the means to a successful journey to become a Predictive Enterprise.

The first step, and absolutely the most critical, is to firmly establish the role and accountability of Executive Leadership in this nexus. In my last blog post of July 25th (“Data & Analytics Leadership: Missing in Action”) I made the case that the CEO, Board and Senior Executive Team have essentially been MIA during the entirety of the data & analytics journey to date and that if this does not change fundamentally then the benefits of being a Predictive Enterprise will never be realized. I will expand on those beliefs and more in the next installment of The Data Leadership Nexus, entitled “Leadership Requirements in the Predictive Enterprise.”.

Stay tuned.

Richard

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