Archives For #Business_Leadership

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

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

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

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

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

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

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

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

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

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

Cheers,

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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

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

Conferences:

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

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

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

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

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

Articles:

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

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

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

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

The Data Leadership Nexus (Blog):

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

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

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

 

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

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

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

The Data Leadership Nexus is comprised of these basic components;

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

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

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

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

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

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

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

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

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

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

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