The UK’s: Government Digital Service (GDS), the US’s: Digital Services (USDS) and Australia’s: Digital Transformation Authority (DTA) are all train wrecks in every meaningful measure of success.
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Preface: I did not write a formal posting on the Data for Policy confab this past September, but wanted to at least share the materials that I presented and discussed during the conference.
Abstract: The notion of Data-driven Policy making and its associated Governance, is often challenged by the fact that the vast majority of Politicians, Civil Servants, Champions of Industry & Non-Profit Leaders are basically illiterate in the domains of data, analytics & decision science. Most of these leaders have come up through their careers making decisions based on gut instinct (experience), group think (consensus) or by using a modicum of summary data & visual analysis, but few have either a base in decision science or statistics, much less have bootstrapped themselves along their careers to become Data & Analytics Literate.
Educators today are faced with the daunting task of preparing future generations of Leaders who must have deep competencies & acumen in all aspects of data, analysis & decision science. Many have chosen to focus on the dubious discipline of so-called Data Science. These endeavors are for the most part a cynical attempt by educators to latch onto the latest fad and to create degree programs based upon cobbling together a hodge podge of disciplines which is sold to unsuspecting students as either an Undergraduate or Post Graduate degree opportunity. All fail at their mission and leave graduates, much less future leaders, with a degree that is sorely lacking in the core skills and competencies required to succeed with.
In my presentation at the Conference I endeavored to trace the roots of how we got into such a mess, what needs to be done to prepare individuals to become Data-driven Leaders and how Educators must re-think their approach to creating/adjust curriculum and programs to put all students on a path to Data & Analytics competency and mastery no matter their chosen field of endeavor. I focused specifically on the notion of Top-down Data Leadership that I coined several years ago and use to drive convergence on the key issues and competencies required by all Leaders, Managers & Employees to be use data, analytics & decision science pervasively across their Organizations.
Handouts & Videos:
data-for-policy-2016-handouts-copy
U-tube Interview: http://bit.ly/2iK4DPZ
Definition: Post-Truth; A phenomena found “after the continuous use of facts & experts derived from “for hire” sources to bolster seemingly outrageous arguments where the public (Electorate) switches off its acceptance of any facts, figures or “truths” and now consciously wants to be deceived (its new comfort zone).
Definition: Decisioning; The art of decision making. A combination of Facts, Evidence, Decision Science, Gut & Instinct. How each is weighted greatly affects the accuracy of the decision.
*Body: For several decades now, Business, Government & Non-Profit Leaders have been pursuing the common goal of Fact (Evidence) based Decision Making. What started out as the notion of Decision Support in the early ‘80’s, soon moved to the emerging field of Decision Science in the ‘90’s & beyond. Decision Science (a widely recognized branch of science) is where Data, Analytics, Algorithms and Decision Theory coalesce into a formalized discipline for Decisioning*. It’s use can be found across many geographies, within all sectors in small & large Organizations. The “Data-driven Cultures” created in these Organizations are much more pervasive than those who simply embrace the marketing term “Data Science” which seems to be focused exclusively on “self-aggrandizement & data wrangling”.
In recent times however, as Decision Science has become much more mature and widely adopted, we find that it has run head-long into the buzz saw of Politics where Data, Facts, Evidence and ultimately the Truth are bent, twisted & broken to fit the needs of ideologies, platforms and agendas in respect to achieving outcomes which are “counter-factual”. One only needs to examine the three most recent Elections/Referendums in the UK, as well as the current US Election cycle, much less the current Brexit negotiations (or the EU Phony War if you rather) to appreciate just how much of a Post-Truth World we have now entered.
In today’s Post-Truth World, not only are stated facts meaningless i.e. lacking in veracity, but the pursuit of the Truth has become derided by many. The arc of this effect has reached the point where the majority of the Electorate are now demanding that it be lied to by its figureheads so as to constantly reinforce its own particular ideology in spite of the reality around it. This is a clear threat to every democracy around the world where an informed, much less literate, Electorate is required to provide checks & balances to government overreach, much less holding them to account in respect to delivering the services & protections that society demands. For someone who has just arrived on Earth and is observing this effect first hand they might ask; “Are there any real differences between so-called Democracies and Authoritarian Regimes?” These effects are no less profound in the Commercial and Non-Profit Sectors where we constantly see “Dubious Data, Questionable Facts & Outright Lies proffered by Executives, spokespeople and PR hacks.
How should we cope with this challenge?
First and foremost, wherever your role lies in the data, information & analytics supply chain you cannot abandon your mission to deliver the highest-quality information & insights in support of Decisioning at every level. You must insure that strong & independent Data Governance & Data Ethics bodies are in place and their guidance is employed by all practitioners and consumers of these deliverables and that regardless of the outcome, the Facts stand on their own merits (subject to peer review and A/B testing, etc.). Only by creating (if not already established) a bedrock data foundation for Decisioning, built on transparency, veracity, lineage, proven rigors & pristine quality can a platform for the “Truth” be achieved, much less maintained. It is critical that as the Post-Truth paradigm plays itself out that this foundation for the Truth be maintained and protected at all costs. The old adage that the “first victim in war is the truth” applies to everything in the Decisioning Supply Chain and those who support it, much less rely on it, must be ever-vigilant to protect its transparency.
Each of us will be challenged to maintain our individual (much less collective) sanity during the course of time that this Post-Truth era plays itself out. We may sound more barking mad at times than those who embrace the Lies and Deception, but this will pass as well. One day when the Light of Truth returns we will be rewarded for beings its stewards, but until then we must “keep buggering on” (KBO as Winston used to say).
* A version of this posting appears in the October 2016 issue of Information Age (www.information-age.com)
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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