Archives For July 2014

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.

 

I am presently waiting in the Boston Airport for my flight home to Seattle after attending the “8th MIT Chief Data Officer & IQ Symposium” this week and wanted to reflect on the above while the thoughts were still swirling around in my head.

The Symposium was extended by 1/2 day to support discussion on “Bridging the Data Science Talent Gap”. There were presentations from Industry, Consultants/Recruiting & Academia with almost a singular focus on the so-called “Data Scientist” (a fictional character resembling a Unicorn in my opinion) and how to create them, find them and leverage them for success. As expected given the demographics of the audience and the presenters the point of view was very much through the lens of technology with a smattering of business speak to provide some balance.

What was so obviously absent from the entire dialog was the role of Business Executives as Leaders of the Data & Analytics Initiatives across their enterprises. Instead, they were relegated to the role of providing the vision (a very limited one), funding, head count requisitions, capital investment funds, consulting contracts, etc. in support of the Chief Data and Analytics Officers, the CIO/CTO and Other Interested Parties and their plans of action. A clear belief was indicated by many that Business Executives were just not up to the task of Leadership. Why is that one should ask?

From my vantage point as an Executive Consultant I have seen this dynamic play out many times and the root case is that the Senior Executive Team is “Missing in Action”. There is a total disconnect between the Strategic Leadership that they provide and the requirements to successfully execute the Disruptive Strategy that Data & Analytics portends. This must change and immediately.

Today’s Senior Executive is not shy when it comes to expansion of their operational portfolios or the pursuit of risky endeavors such as Credit Default Swaps (CDS), Mortgage Backed Securities (MBS), etc. especially when it feathers their nest or vanquishes the competition. However, when it comes to Data & Analytics they are Missing in Action (MIA). This situation has created a management conundrum. Senior Executives cannot be Masters of their Universe when they do not understand the fundamentals of Astrophysics. In other words, their strength (and success) manifests from deep domain knowledge and acumen and applying these to creating sources of competitive advantage for their organization, not cheerleading a disruptive change in their business model which they neither understand nor can work from a position of strength to drive to success. In spite of being strong believers (and advocates) for Data & Analytics the vast majority of Senior Executives are not Analytics Literate. They have never worked in an evidence (or fact) based decision making environment, much less one where everyone across the Enterprise leverages Information & Insights in every task they are responsible for. I could go on for quite a bit more here, but will leave that for later.

I believe that we need to immediately change the dialog in the Data & Analytics Community from “Big Data, Data Scientists, Chief Whatever Officers, Data Lakes, etc.” and focus on Executive Leadership Development (not IT) and determine how to put the entire Senior Leadership Team on a trajectory where they can ultimately assume the Full Accountability for all Strategic Outcomes from applicable Data & Analytics Strategies and Plans. If we do not change this Organizational Dynamic in short order all bets are off.

I will be developing an overview of how to accomplish this in my upcoming series (and presentations) on what I am calling “The Data Leadership Nexus”. Look for an overview of this in early August.

RL

In the two previous installments of this series, I focused my viewpoint on;

1.- Defining a Leadership Paradigm for Big Data & Analytics Success

2.- Establishing Top-Down Accountability

In this final installment I will focus on the roles that optimized Organizational Design and broad Cultural Adoption play in the success of any Big Data & Analytics Success Story.

Suffice it to say, you cannot simply establish Top-down Accountability within the Leadership Hierarchy and expect to achieve real transformation. You must also create a “to be” Organizational Model that is optimized for the strategic mission and the realization of its outcomes, as well as bringing the entire Organization’s Culture on board to support this vision and the pursuit of the outcomes that come with it. Without these critical Organizational endeavors you will not be successful with your Big Data & Analytics Transformation no matter how strong of a Leadership Hierarchy you have created.

Your Leadership Hierarchy (beginning with the CEO & Board and then cascading down to Senior Executives and their subordinates) is collectively responsible for making realizable all of the Big Data & Analytics strategic outcomes as part of their overall operational plans and activities. To accomplish this the Leadership Hierarchy must approach the challenge with an optimized Organizational Structure that has been designed to be fit for purpose for this task and not one where you are trying to leverage a legacy structure that cannot adapt to this new mission. This has been one of the classic mistakes so far as Organizations’ attempt to “bolt on” their Big Data & Analytics strategy to existing structures, rather than address Organizational Design requirements as part of the strategy itself. Examples of this is the use of Competency Centers and Centers of Excellence as catalysts to create critical mass for Big Data & Analytics. Each time this approach is advocated and ultimately undertaken, poor results and a dissipation of Leadership buy-in results as they are not leverageable across the entire Enterprise and typically only serve the needs of the few and not the many. Quick fixes and Organizational band-aids will not work if you want Big Data & Analytics to be truly pervasive. Organizational Design is a process that supports the CEO & Board in moving from Strategy to its successful execution and will require appropriate investment and disruption of the status quo. It is an essential component of achieving the Strategic Outcomes that manifest from your Big Data & Analytics Strategy and should not be undertaken as an after thought. Like any other critical component of the Organization and its Operating Model it must be fully deployed at the time of your Transformation journey as one of the required elements for success .

Secondly, Cultural Adoption is the most critical challenge associated with any Big Data & Analytics strategy and must be fully appreciated, much less addressed at every point along the journey. It can be an accelerator or a de-limiter (much less killer) of any strategic journey and is the total responsibility of the Senior Executive Team to facilitate. Leadership from the top-down has its risks and the most substantial one is not engaging sufficiently and earnestly with the Organization’s Culture. Most of this risk manifests in the multiple layers of management & supervision between the responsible executive and their front-line staff. Culture cannot be changed by edict (or fiat), but rather must be motivated to adapt by a compelling strategy that is lead from the top-down with substantial hands on activities by the executive team to make it real and essential to each staff worker who make up so much of the Organization’s Culture. This cannot be achieved by what is called Change Management. Change Management is little more than cheerleading and communications, with far too much focus on training. It is a poor (if not failed) substitute for truly engaged Leadership working in the trenches to instill & empower all of the front-line staff to embrace Big Data & Analytics and make it truly pervasive in  their daily activities and mindsets. Every Organization that has been successful at real Transformation knows well the requirement to engage with the Culture and to motivate it to not only Adopt the new operating model, but become “rabid fanatics” about its virtues along the journey. Big Data & Analytics Transformational Strategies are no different and if anything, offer unique opportunities to completely transform an Organization from backwards, gut-driven decisioning to one that leverages information & analytics at every turn to be not-only fact-based decision makers, but a true Predictive Enterprise.

To Transform your Organization to become a Predictive Enterprise where Big Data, Information, Analytics and a Fact-based Culture all are leveraged to achieve sustained Competitive Advantage, Disruptive Results  and Market Dominance requires; Top Down Leadership & Accountability, an Optimized Organizational Structure and an Evolved/Engaged Culture. If any of these are missing or sub-optimal then the Strategic Outcomes projected within anyone’s plans will not be realized.

I will write on these same themes as I provide live blogging from this coming week’s MIT Chief Data Officer (CDO) & Information Quality Symposium in Cambridge. The agenda is quite full of interesting opportunities to provide a contrarian viewpoint on CDO vs. Transformational Leadership

RL

PS: I am launching in August & September a new series of thought leadership articles in Information Age (www.information-age.com) and at Data Leadership 2014 (www.dataleadership.co.uk) on the notion of “The Data Leadership Nexus”. These are meant to be a logical extension to this blog series on Transformational Leadership. Here is an overview:

The Data Leadership Nexus is the intersection of Data, Information, Analytics & Leadership to create strategic impact, differentiation and enterprise value within every organization. It represents the single biggest opportunity/challenge in realizing the benefits that have been extoled (and often hyped) about Big Data and Advanced Analytics. It is also the linchpin for establishing “a culture of analytics” and making it pervasive across each enterprise and is clearly the most ignored strategic risk in virtually every organization.

In my last posting I outlined a pathway for Transformational Leaders to use in achieving pervasive Big Data & Analytics success within their organizations. In this installment I am going to focus on the specifics of Top Down Accountability by the entire Senior Executive Team as it leads these transformational efforts.

In spite of all the punditry regarding new management paradigms & leadership structures, the vast majority of all Public, Private & Non-Profit organizations remain hierarchical in structure and cultural behavior. This fact cannot be ignored when establishing both the Strategy for Big Data & Analytics Transformation (BDAT), as well as its execution plan. It is essential to success and If you choose not to leverage this dynamic or try to run counter to it you will fail to achieve any outcome of substance in my viewpoint.

The Senior Executive Team (SET) within each organization is typically organized around major functional elements of the operational model utilized. Strategic direction comes from the CEO & the Board and cascades down to the accountable Executives tasked with its execution and the successful realization of its outcomes. This well established dynamic becomes the means by which we truly transform legacy decision making (from gut-based to fact-focused), insights (minimal to maximal) and analysis (from backward-looking to predictive) to create a true analytics-driven enterprise. In this model, each Executive manifests Strategy Execution by using Big Data & Analytics pervasively across their domain of Accountability to maximize Outcomes. Responsible subordinates drive this down the hierarchy and embed it further into all of their Tactical & Operational endeavors with alignment horizontally. Front-line workers leverage & exploit the Organizations’ Big Data & Analytics operational activities daily.  To achieve this level of pervasiveness, all Senior Executives, subordinates & staff members must be fully committed to successful execution of the Strategy and competent in all the relevant aspects of the data & analytics which intersect with their area of responsibility. This cannot be delegated to  a 4th-level subordinate squirreled away somewhere in a cube who “gets it”. They all “must own it” and rise to the challenge through whatever means are available.

As mentioned previously mentorship, change management and formalized educational activities should be brought to bear in order to bootstrap all Accountable and Responsible Executives, Managers and Subordinates. This represents a major up-front investment by the Organization in the success of the transformational strategy and is a benchmark as to their true commitment to achieving its outcome.  Relying on Competency Centers, Centers of Excellence, Data Scientists, Chief Data Officers, Chief Analytics Officers and other proxies just will not cut it. If Enterprises are going to be successful with Big Data & Analytics then the Senior Executive Team must “walk the talk”. Nothing less will do.

This is clearly a major challenge & undertaking for the current generation of Senior Executives and a great number of their subordinates, but is should not be for the generation to follow. We all (Educators, Consultants, Advisors, Vendors, etc.) must work these transformational enterprises to insure that they develop the deep acumen and competencies within these future business leaders that we intersect with in our endeavors. We can no longer exclusively devote our time, energy and resources to those in the technology department as they are neither accountable or responsible in this future model. Their voice has been diminished and will not be heard at all unless they become more relevant to the more strategic conversation. For more on this see my July 2014 Information Age article (http://bit.ly/1sU3yol) on Leadership during the time of disruption.

In the end, No Enterprise will ever transform itself into a Big Data & Analytics Success unless the process is owned and executed by the Senior Executive Team from a top-down perspective. IT is powerless to achieve this outcome and it is delusional to think otherwise. The current generation of Senior Executives know their business models, competitive environment and organizational cultures well, but are hamstrung by the lack of formal education and competencies in Big Data & Analytics. This can be overcome with our assistance, but we should not lose sight of the end game which is the next generation of Transformational Business Leaders.

In the Final Installment on this topic (for now) I will focus on “Organizational Design & Cultural Adoption”. Stay tuned.

RL