Data, Information & Analytics as Core Competencies in The Predictive Enterprise

September 9, 2014 — 1 Comment

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 

We have explored Top-Down Leadership (#1) and Organizational Culture (#5) in previous postings and will now discuss the combined components of Data, Information & Analytics (#2-4).

In the Data Leadership Nexus the role of Data, Information & Analytics are what Michael Porter calls Core Competencies: “a defining capability or advantage that distinguishes an enterprise from its competitors”. They are not the underlying technologies, associated infrastructure and services that the IT Team is responsible for and what most of the industry conversation continues to myopically focus on i.e. Big Data. Instead, they are the inherent intellectual capabilities & acumen found broadly within the Organization and pervasively utilized across the entire Enterprise. It is in these Core Competencies where we manifest the ability to become a true Predictive Enterprise. The Predictive Enterprise is not a technology, it is an Intellectual and Cultural Construct for Creating Strategic Outcomes for each Organization.

The Core Competencies of Data, Information & Analytics compliment others which are specific to the Industry or Service Sector that the Organization serves e.g. Supply Chain in Manufacturing, Logistics in Consumer Goods, etc. They are that critical pillars that every Organization’s Strategies need to be built on and are ubiquitous in use by everyone within the Enterprise i.e. Core.  Every organization leverages and exploits their Core Competencies to create points of differentiation, drive operational excellence, manage risk appetites and to create/sustain other sources of competitive advantage in the modern enterprise.

As Core Competencies; Data, Information & Analytics drive everyday activities to achieve pervasiveness. Sustainable Competitive Advantage comes from the full leverage of these competencies in respect to the competition or other benchmarks (as found in the Government sector). Typical examples of the leverage points within the Core Competencies of Data, Information & Analytics are the following;

  • Data Curation: The continuous development, enhancement & stewardship of historical, reference, transactional & operational data sources to create the highest intrinsic value and agility for the Organization.
  • Information Exploitation: The business contextualization of Curated Data to create maximum leverage points in support of all Strategic, Tactical & Operational Goals set out by the Organization.
  • Pervasive Analysis: The continuous application of statistical, descriptive, predictive and cognitive decision science to Contextualized Information sources for use in Decision Making, Customer Insights, Risk Mitigation, Performance Improvement and Other endeavors that each member of the Organization is responsible for.

Each Core Competency has companion technical domain activities that are the Responsibility of the IT & Service Delivery Team(s). A collaborative framework is established between Data Leadership and IT/Service Delivery to insure maximum effectiveness and efficiency. IT & Service Delivery works in concert with the Accountable parties in Data Leadership (via a mutually defined RACI) to maintain, sustain and optimize the underlying infrastructure and delivery solutions such that the Strategic Value of the Data is maintained/enhanced and that all Information & Analytics competencies can be fully realized. This approach will typically require new structures in the traditional IT functional suite as well as its Leadership Team. These obstacles are easily overcome once the Organization has established a fully accountable Top-Down Data Leadership structure, strong Strategic Direction and a newly defined Organizational Culture which is driven by the beliefs that; Information is an Asset, Evidence-based Decisioning is the norm, and that the pervasive use of Analysis is the critical path to Real-time Insights, Risk Awareness & Business Agility.

Data, Information & Analytics are no longer outliers in respect to the Short and Long-term Strategies of every Organization. They are constituent components of every Organization’s Strategy in the form of  Core Competencies which must be fully leveraged and exploited to achieve the desired Outcomes and to create/sustain Competitive Advantage in a world where differentiation is hard to achieve and razor thin in scale. Each of these must be utilized to their fullest to create and sustain a Predictive Enterprise.

The Predictive Enterprise has three essential elements for Strategic Success; Effective Leadership, A Committed Organizational Culture & The Exploitation of its Core Competencies. In the next installment of The Data Leadership Nexus we will discuss the Integration of all these elements, along with supporting functions which are required, to achieve a full Transformation of the Legacy Organization into a true Predictive Enterprise.

In the meantime you can follow The Data Leadership Nexus discussion on Twitter via the #DataLeadership hashtag, in the September and October issues of Information Age (UK) (www.information-age.com) and at Data Leadership 2014 in London (October 30th) (www.dataleadership.co.uk). Finally, I will also be setting up private briefings for those Enterprises who are interested in how to transform themselves into Predictive Enterprises for this Fall in the US and UK. If you are interested you can contact me via email: richard.lee@infomgmtexec.com

Thanks for following along.

RL

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Editorial Calendar – September 2014

August 30, 2014 — Leave a comment

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

Blogs:

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

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

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

Articles:

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

Tweet Storms:

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

Conferences:

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

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

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The Role of Organizational Culture in the Predictive Enterprise

August 28, 2014 — 2 Comments

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

 

 

 

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“Leadership Requirements in the Predictive Enterprise”

August 11, 2014 — 2 Comments

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

 

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Overview: “The Data Leadership Nexus”

August 5, 2014 — 1 Comment

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

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August Editorial Calendar

July 28, 2014 — Leave a comment

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

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Reflections on the 8th MIT Chief Data Officer & Info Quality Symposium

July 26, 2014 — Leave a comment

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.

 

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Data & Analytics Leadership – “Missing in Action”

July 25, 2014 — 5 Comments

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

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Transformational Leadership for Big Data & Analytics Success – Part 3: Organizational Design & Cultural Adoption

July 20, 2014 — 3 Comments

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 Big Data, Business Analytics, Business Transformation, Information Management, Leadership, Uncategorized , , , ,
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Transformational Leadership for Big Data & Analytics Success – Part 2: Establishing Top-down Accountability

July 11, 2014 — 2 Comments

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

 

 

 

 

In Big Data, Business Analytics, Leadership , , , , , ,
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