Archives For #dataleadership

Preface*: The Data Leadership Nexus (Copyright 2013) 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.

Body: As we all prepare to attend this May’s (Information Age) “Data Summit” (http://bit.ly/1sznhbV) and to celebrate those chosen as the (Information Age) “Data 50” for 2017” (http://bit.ly/2o6OjaP), I wanted to reflect on how far we have progressed (or not) on the notion of Data Leadership since I began to write about it in these pages (Information Age) in 2013.

The origins of the Data Leadership conversation go back several decades to my time in the supercomputer sector and the “Grand Challenge” problems that we had been tasked in solving. In those days, CPU speed (and cooling requirements) and Network bandwidth dominated the discussion, while Data drove the outcomes. During that time in history Leaders had deep backgrounds in Science, Engineering & Math and all understood first-hand the scope of these challenges, as well as the limited means to surmount them.

Fast forward to today and we find that much has changed since then in terms of the characteristics & competencies of Leaders, as well as Computing & Networking hardware. Today, Data is recognized as centric (in all respects) to solving all Challenges, Grand or not, but not very well understood by those who ultimately have leadership accountability for it.

During this span of time the Data Management Team (an IT function) remains for the most part in charge of all data within each and every Organization. Whether it is under the auspices of a CIO, or an anointed proxy leader such as a CDO, data is still managed by IT at the direction of technical leaders. This is not a measure of any progress whatsoever in respect to either treating data as a key Organizational asset or establishing accountability for its creation, use (via Analytics) and stewardship by the CEO and Board. How can this be one should ask?

I have boiled it down to one common theme; Does your CEO (and Board) have the Right Stuff to do the job (of Data Leadership)? The simple answer is (emphatically), “No, not yet!”

For those who are fans of the book/movie, “The Right Stuff”(1) you might have been persuaded to believe that it was a story about Astronauts and their early struggles & successes, but in reality, it is one about Leadership. NASA as a program was successful not by having better technology, but by leveraging competent & capable Leadership from the top-down. Each Leader in their hierarchy had” The Right Stuff” in respect to fostering the mission & vision of the Program from a position of strength in respect to their core knowledge, skills and acumen. These same strengths are the foundations of Data Leadership as well.

To fully realize the power of digital, data & analytics in any Organization, no matter the sector, the entire leadership team must be competent and capable in exploiting these capabilities in every activity they undertake. They cannot delegate these requirements to so-called Data Scientists, Proxy Leaders e.g. CDO’s, or those in the IT Department who provide service delivery to them. They alone must accept responsibility for the successful execution of your data-driven strategy and be accountable to their superiors (including the Board) if they fail to do so. A true Data Leader must be more than a cheerleader who demands that others provide fruitful outcomes from digital, data & analytics. He/She must lead by example and be “hands on” in terms of approach and delivering the goods. This is the essence of having The Right Stuff, not the Leadership Fluffery that I continue to see across all Sectors. Creating Competitive Advantage from your Digital, Data & Analytics investments and capabilities is a Leadership Accountability that every Data Leader must step up to in order to succeed.

In today’s world, bona fide Leaders are hard to find under the best of circumstances. True Data Leaders are an exceptional find for any Organization and most are an amalgam of many talents. They cannot educated for this role, but rather molded into it based on a variety of life experiences and inherent capabilities. True Data Leaders are well rounded, comfortable with their responsibilities and always have a bit of swagger associated with those who have The Right Stuff.

Please join us on May 18th for the Information Age “Data Summit” and learn more about “Data Leadership and The Right Stuff”.

(1) “The Right Stuff” (’79) – Tom Wolfe’s epic tale of the NASA’s early days and the Mercury 7 Astronaut Program”

*-This posting appears in edited for as an article in the April 2017 edition of Information Age (www.information-age.com) and can be accessed on the IA Hub (www.informationagehub.uk)

Preface:

Governments cannot embrace, much less promote Big Data, Open Data, Analytics, Machine Learning & Ubiquitous Algorithms without protecting the Citizens’ whom they work for. Social Engineering must be by choice, not by default through illiterate political leaders.

Body:

The UK Government as part of its “Digital Economy” initiative has just released with great fanfare the “Data Science Ethical Framework”. Its ministerial champion has characterized it as “harnessing the Progressive power of Data Science while protecting the Public”. It does neither, but clearly illuminates the lengths to which the UK Government (along with others) will go in trying to influence/dictate behavior in areas where they have no literacy at all in respect to understanding the underlying capabilities (Data, Analytics & Algorithms), nor the consequences of the harm (or actual good) that can come if left to their own devices. Not to be left to a footnote however, is the fact that these attempts at behavioral influence do not apply to the Intelligence community or Police services, both of whom want unlimited powers to surveil, gather data on everyone’s daily lives (and perhaps thoughts) and to then use these to ultimately predict behaviors i.e. The Snoopers Charter.

Ever since the notion of Big Data has come onto the scene, many have extolled its virtues in changing the world as we know and understand it. They have hyped with a zeal not previously seen the notions of Data Science, Data Scientists, Algorithms & Machine Learning, etc. Virtually all of them have advocated for its wide-scale use to analyze and predict citizens’ behavior in order to gain deeper insights, without any controls as to “just how creepy” this activity could get in terms of interacting with the public at large. Any attempt to limit the “how and where” Big Data & Analytics should be applied was met by the fury of these same advocates who characterized it as “stifling economic growth and wealth creation”. Not surprisingly, most advocates have been highly influential in getting Governments to go along with their thinking and to take a “hands off” approach. This has not worked out well for consumers who now see their daily lives dissected, analyzed and ultimately manipulated by the algorithms & machine learning associated with the deep behavioral insights now available to almost every organization who invests in Data & Analytics capabilities.

The backlash that now arisen from this lack of control is significant enough that many Governments have created Ethics Councils and other bodies who have gone on to generate reports & recommendations on the issue of  “Ethics in the age of the Algorithm”. Additionally, these same governments (US, UK, EU, etc.) are also major advocates of Digital and have undertaken major Digital Strategy & Transformation efforts within their countries[1]. These efforts have served to further exacerbate the Ethics Problem that we are now experiencing. A common thread found amongst all of this is the seemingly cluelessness that Government Leaders, Ministers & Civil Servants exhibit each and every time they make an address or pronouncement on the topic of Privacy, Ethics, Governance, etc. associated with Big Data, Analytics, Algorithms, Digital, etc.  Clearly, they don’t understand the underpinnings of the issues, nor the reasons why this topic has become so paramount in the public’s mind and their stated demands that it be resolved to their satisfaction.

Data (Big or Small), Analytics (Creepy or Helpful) & Algorithms (Evil or Good) are major influences in how the Digital World around us evolves, much less serves us. Beyond the well-rehearsed platitudes, there needs to be a fundamental mastery of the details associated with these domains by Leaders & Policy Makers who are ultimately accountable for making Citizen’s lives better, much less protecting them from threats. Without strong & competent Leadership, and controls (governance) , these same citizens will be victimized rather than benefited by Data, Analytics, Algorithms & Digital. The requirement for competent leadership is not a political platform for campaigning on, but a focal point for Government action in order to uphold basic human rights, no matter what pace of transformational change the country is experiencing.

An Ethics Framework that relies on self-governance, best efforts and serendipity to insure that consumer Privacy is protected and that Citizens are not victimized by their own data is a recipe for disaster. Government Leaders must commit themselves to leading at all levels and across all domains. They must be literate and competent in the areas that they promote as catalysts for change and not leave Citizens to the vagaries of Data Science, and all that portends to be.

[1] The UK Government has gone so far as to make the “Digital Economy” a centerpiece of the Queens’ Speech in spite of not being able to come up with a companion “Digital Strategy” that was promised quite some time ago.

  • An edited version of this posting appeared in the June 2016 issue of Information Age (UK) (www.information-age.com)

Data-driven Government: The use of data (aka Facts, Information, Insights, etc.) to support all Decisions, Policies, Performance Metrics, etc. required in the daily & long-term operation of Government (at all levels).

Oxymoron: A rhetorical figure of speech in which markedly contradictory terms appear in conjunction so as to emphasize the statement ; gen. a contradiction in terms.

The notion of Data-driven Government presumes to solve the age-old challenge of balancing “head vs. heart”(1)  when it comes to decision making and associated activities in Government bodies. Data-driven Government creates a culture where decision making & behavioral outcomes rely on Data (aka Facts) to drive each and every aspect of day-to-day operations as well as the long-term strategic goals. The concept is not new at all and dates back many decades now, but has had limited success in Government until recently. The Data-driven approach has been brought to the forefront again as Government’s everywhere jump on the Data, Analytics & Digital bandwagons and proceed to Transform themselves into more agile and efficient bodies which can better serve the needs of its citizens, at substantially lower costs. It is clearly an ideology that has caught on in the numerous Digital Transformation Programs that we see around the world (UK-GDS, US-18F, Australia-DTO, EU-SDM, etc.) and has an almost religious zeal to it in respect to how Politicians and Mandarins characterize it in their advocacy activities (much less those who are actively involved in its delivery). However, beyond the rhetoric is the fundamental question; Is Data-driven Government an Oxymoron or a Reality? I will endeavor to answer this in the rest of my article.

Government (as a service and not quite yet a platform) has become increasingly complex to deliver effectively given the growing demands of daily operations and the increased sophistication & demands of Citizens in terms of their expectations from their Government. At the heart of this is a growing awareness, much less recognition, that Government is more and more like a business which now must compete for Customers in a highly crowded field of competitors. While this may strike some as odd, it is clear to most strategists that Government must keep up with advances in Decision Science used by the Commercial Sector in order to survive (at the polls at least).

To become a truly data-driven Government (and not cynically wear it as a fashion statement) the culture of decision making & performance management must change dramatically. This transformation begins at the very top of Government with the elected Officials who are accountable (with their Civil Service partners) for formulating and executing strategy and defining the associated tactics required to achieve the desired outcomes. These Officials must change their spots from being political hacks who use their power to force outcomes, to those who achieve outcomes by leveraging facts & measures. This approach must then cascade down to all levels of Government (Elected representatives & Civil Service) while remaining aligned along this path. The secret sauce in this approach will be balancing the political agenda of elected officials with the needs of citizens. Data-driven Government provides levels of transparency not currently found today even in the most progressive Open Data programs. The data used to drive these decisions must pass scrutiny by oversight bodies, opposing parties and citizens themselves. This leaves little wiggle room for political agendas to be fulfilled using smoke filled backrooms as a proxy for decision science.

Data-driven Government is a rationale that the Open Data community uses in their advocacy activities to justify further adoption and investments. They speak of “dog fooding” by Governments’ in respect to using their own Open Data to drive outcomes as well as enhancing Transparency. I believe that Open Data remains a PR tool for use by governments to control information outflows and to act as a proxy for transparency that comes from Freedom of Information laws. These efforts typify the fact that political power is hard to give up willingly by elected officials, but given the awareness of citizens to these tactics it will not be long before they are non viable.

In the end, will Governments’ have the political willpower to become truly data-driven or will they continue to embrace the politics of cynicism, power and cronyism? It remains to be seen, but strong seeds of change have already been planted and if supported by strong nurturing (via the electorate), plenty of sunshine (transparency) and nutrients (budget) it can and will become a reality.

(1) – The Head (cognitive) is all the rich data & insights that Governments accumulate and the Heart (emotional) being Politics/Human Behavior at its basest.

Note: This posting appears in an edited form in the January 2016 issue of Information Age magazine (www.information-age.com).

 

 

 

In January 2015 I wrote in my Information Age column about what I referred to as: “2015 – The Year of Data Leadership” (posted on my blog as well: http://bit.ly/1SCPZVr). I wrote on this topic periodically over the course of 2015 and included updates in my presentations at the PASS – “Business Analytics Conference (June – Santa Clara)” & Information Age’s “Data Leadership 2015 (November – London)”. Now that the year is finally complete and as we enter 2016 with a full head of steam, I would like to share with all of you a Report Card that I developed which “grades” the progress (or not) that was made in respect to executing on the basic elements of my Data Leadership Nexus.

There are three foundational categories which I would grade each Organization on in their pursuit of becoming a Predictive Enterprise.

  1. Leadership Literacy & Acumen in “All things Digital, Data & Analytics” (aka Top-Down Leadership)
  2. Strategic Leverage of the Organization’s Core Competencies in Digital, Data & Analytics.
  3. Empowering a Culture of Analytics & Data-driven Decisioning. (aka Cultural Adoption)

These three fundamental categories of the Data Leadership Nexus working in concert with each other can produce the maximum transformation & subsequent strategic outcomes in the shortest period of time. All require close monitoring and nurturing by the CEO & Board along the entire journey to insure the appropriate effects are fully instantiated.

The Nexus of Top-Down Leadership, Cultural Adoption and the enabling Core Competencies of Digital, Data & Analytics creates a unique strategic framework for becoming a Predictive Enterprise. Adopting the framework provides a path to strategic transformation, but requires each “leg of the stool” to carry its full weight.

Grading the success of any organization’s transformation into a Predictive Enterprise will always be subjective so I am using a scale of 1-5 (1 =Failing Outright, 3=Trying real hard, 5=Tangible Success) to provide some granularity, but not specificity as to actual performance (think of it as a trend).

The 2015 Data Leadership Report Card

  • Top-down Data Leadership by CEO & Board: (Grade=2)
  • Leverage of Core Competencies in Digital, Data & Analytics (Grade=3)
  • Cultural Adoption & Empowerment (Grade=1)

My Grading Rationale is as follows;

  1. CEO’s & Boards are beginning to move in the right direction in terms of their Accountability for “all things digital, data & analytics”, but more importantly that they are core to their strategy and must be integrated in up-front, not bolted on later. All Eight CEO’s featured in my series, “Profiles in Data Leadership” understand this intrinsically and did not have to be “converted” after the fact. There is much progress that needs to be made in respect to moving from a Technical view (delivered by IT) to a strategic view (driven from the top-down)
  2. Most (if not all) Organizations have invested heavily (and will continue to do so it appears) in digital, data & analytics solutions & capabilities, but have not made the transition to using them as Core Competencies. This is due to the continued fixation on specialization and not generalization of these skills. I see these barriers breaking down over time, but they are a disabler to achieving the pervasive (and not selective) use of digital, data & analytics to achieve competitive advantage and strategic outcomes.
  3. Moving the Organization’s Culture from gut-based & hierarchical decision making to data-driven & fully analytics empowered is a long-term journey for everyone, but is nonetheless the linchpin of strategic success. The use of Proxy Leaders and Unicorns (aka Data Scientists) is counter-productive to this effort as it leaves the vast majority of the Organization on the sidelines. Organizational Culture is the shadow of the CEO (and Board) and reflects their actions and demeanor. If you have a CEO & Board who are dedicated to Top-down Data Leadership you will soon have an Organizational Culture that is in lock step with the plan to transform into a Predictive Enterprise.

In 2016 and beyond I see major improvements in all three foundational categories, especially as the experimentation with the fashion statements of Proxy Leaders and Unicorns fails miserably and common sense/strategic approaches become the norm.

I will continue to write on this matter and to provide a 2016 Report Card over the coming year.

Stay tuned!

RL

 

 

 

 

 

Each year now as I advocate for Top-down Data Leadership by the CEO and his/her Board (as opposed to Proxy Leadership as a “Data Fashion Statement”), I use the 12 Days of Christmas lyrics as a theme to mimic in getting my message out over the holidays (in small bites). 2015 was no exception and you will find below a recap of my Tweets, along with a bit of embellishment beyond the 140 character limits.

Hope you enjoy it.

On the 1st Day of #DataLeadership the #CEO confirmed to the Board his/her Full Accountability for “All things #Digital, Data & #Analytics“. This is the central tenant of the Data Leadership Nexus where leadership manifests from the existing hierarchy which has now assumed full accountability for “All things Digital, Data & Analytics”.

On 2nd Day of #DataLeadership the #CEO & Board outlined the Strategic Outcomes which #Digital, #Data & #Analytics would deliver for the Organization. These core competencies must be leveraged to create tangible outcomes for every Oganization.

On the 3rd Day of #DataLeadership the #CEO & Board set their Data-driven Core Strategy into motion across all facets of their Organization. Data-driven begins with your Core Strategy and all its desired Outcomes. Data (facts) are used to help define the Strategy, to measure its progress along the way and ultimately to characterize the Outcomes in a meaningful way.

On the 4th Day of #DataLeadership the #CEO, Board declared: “We will Transform our Organization into a Predictive Enterprise within 5 yrs.” Transformation is a journey for every Organization. You must set targets along the way and eliminate barriers to success too. This is the role of the CEO & Board and it requires Continuity of Leadership as well as Conviction to achieve the Outcome in a finite time frame.

On the 5th Day of #DataLeadership the #CEO committed the Organization to achieving broad-based #Data & #Analytics Literacy within two years. Data & Analytics must be used pervasively and not selectively. This begins with Literacy & Competencies at all Levels, especially at the top where the most value from facts, measures and insights typically manifests.

On the 6th Day of #DataLeadership the #CEO enacted the Org’s plan to be #Data-driven in All Decisions, Measures & Outcomes going forward. Being data-driven is a major commitment and requires moving from an anecdotal (gut) -based decisioning model to a fact (evidence) -based on. It must occur at all levels where decisioning is required in daily & strategic operations.

On 7th Day of #DataLeadership the #CEO vowed to use #Data & #Analytics pervasively (not selectively) in creating their Predictive Enterprise. Pervasiveness is essential to becoming a true Predictive Enterprise. Data & Analytics can no longer be “specialist functions”, and must be used by everyone in all facets of daily work. This is the linchpin of any transformation strategy used to become a Predictive Enterprise.

On the 8th Day of #DataLeadership the #CEO & Board integrated #Data, #Analytics & #Digital into their #Governance & #Risk accountabilities. Data & Analytics are core to each Organizations strategy, tactics and operations. Their use must be governed accordingly in alignment the Organizations’ overall governance model. This applies to Risk Management as well. Data & Analytics are not outliers and must be integrated into the Org’s Risk Models & related activities.

On the 9th Day of #DataLeadership the #CEO, Board & All Senior Execs began their journey to become #Analytics-Literate Leaders within 2-yrs. The central tenant of the Data Leadership Nexus is Top-down Leadership. However, you cannot Lead what you don’t understand. This requires all senior execs, board members and the CEO to become “Analytics Literate” early in the journey to becoming a Predictive Enterprise.

On the 10th Day of #DataLeadership the #CEO detailed the key elements of Orgs’ Transformational Journey to become a Predictive Enterprise. Every successful Transformation requires a road map that details the key milestones and measures necessitated to achieve the outcomes of the Strategy. These will be unique for every Organization as it maps out its journey and the Outcomes it is pursuing. 

On the 11th Day of #DataLeadership the #CEO & Board assigned #DataStewardship Responsibilities for key #Data Domains across the Organization. There are many critical Data & Analytics domains in every Organization and they must be shepherded through their lifecycle by Stewards who are fully (or partially) responsible for this task. These Stewards are typically at the mid-tier of any organization and act as Asset Managers in the typical sense.

On the 12th Day of #DataLeadership the #CEO empowered the Org to use its rich #Data & #Analytics Talent to become a Predictive Enterprise. Empowerment is essential to the success of any Transformational Strategy. It is the Trust element and each CEO & every Board must instill in the culture of the organization. Empowerment engages every single responsible party in the pursuit of the common goal of becoming a Predictive Enterprise.

Look for more postings on The Data Leadership Nexus and Predictive Enterprises over the course of the year.

All the best in 2016!

RLLeadership-picture

 

Preface:

During November’s Data Leadership Conference in London I will be updating the audience on the progress to date that we have made during 2015: The Year of Data Leadership. I promise to share those findings in a subsequent posting shortly after the conference. In the meantime, this is the premise that started the thought process I used:

“The strategic value of Big Data & Analytics can only be realized when they are fully leveraged and exploited by the entire Enterprise. Top Down Data Leadership is essential to the success of these endeavors.”

Body:

As the focus of industry hype moves from Big Data to the Internet of Things we have a unique opportunity to turn our attention to one of the underlying disablers of broad success in using data & analytics to their full potential in any Organization; the lack of Top Down Data Leadership.  During the past couple of years we have seen a fever pitch in Organizations’ anointing proxies to the status of superheroes in respect to Data & Analytics Officers. While there have been many such appointments, most are now being scrutinized as the widening gulf between the rhetoric and reality becomes more apparent. This effort to create “Chief Whatever Officers” has been foolhardy in my opinion, as it has completely dodges the need for the Board and CEO to become directly accountable for the Organizations management and exploitation of data and their leverage of analytics across the enterprise to create a “culture of evidence-based decision making”. My aim in 2015 is to change this dynamic.

In 2015, I would like to create much more than awareness of this underlying challenge, but to make actionable its solution in what I am calling “The Year of Data Leadership”. In the Year of Data Leadership I would like every CEO and their Board (Public, Private, NGO, Not-for-Profit, etc.) to accept the fact that they (and Not IT) are fully accountable for “all things data and analytics”. I want them to embrace this accountability and make it core to their Strategies and Operational Plans. I am challenging them to step up to this leadership mantle and provide the Organization with a plan of action to put it on a trajectory to becoming a “Predictive Enterprise” within 5 years (2020). This Decision Making transformation would move them from being gut-based decision (relying on experience and anecdotes) making Organization to one where evidence (facts, decision science and the appropriate amount of intuition) guide all decisions at every level.

This is an ambitious undertaking for even the most agile of Organizations, but a necessary one if the competitive advantages of a Predictive Enterprise are ever going to be realized. To accomplish such a Transformation I strongly recommend approaching it as follows;

1.- Immerse the CEO, Board & Senior Executive Team in a series of Boot camps designed to immediately (and measurably) raise their acumen and competencies in the domains of Decision Science & Analytics, for “you cannot lead what you don’t understand”.

2.- Make Data, Information & Analytics Core Competencies in your strategic and operational endeavors. Make then pervasive and break down silos and centers of excellence to make capabilities mainstream and ubiquitous to all aspects of your operational domain. This will require investment in staff development and in the early stages may require shadowing of staff with outside experts, mentors and coaches.

3.- Manifest Cultural Adoption by all members of the Organization of this new strategic paradigm i.e. Becoming a Predictive Enterprise. Organizational Culture is “the shadow of the CEO, Board and Senior Executive Team”. It is found in every corridor and behind every door across the enterprise and is molded from the Top-down. To begin to change a culture requires Top Down Leadership to changes it behavior and modify all cultural norms and activities. The entire Leadership team must engage with the Organization directly (with support by Change professionals) to lead by example in regards to championing the new direction and its virtues.

This three-pronged approach will produce the maximum results in the shortest period of time and requires close coordination, substantial investment of time and resources to succeed. It is truly transformational and should not be a sub-priority to other Enterprise-wide strategic and operational initiatives.

The Nexus of Top-Down Leadership, Cultural Adoption and the enabling Core Competencies of Data, Information & Analytics creates a unique strategic framework for becoming a Predictive Enterprise. All components are required to work in concert to achieve a true transformational outcome within any Organization who wants to fully exploit data & analytics for competitive advantage.

*-This posting in an edited version appeared in the January 2015 issue of Information Age (UK)

Preface:

privacy |ˈprīvəsē| noun “the state or condition of being free from public attention, being observed or disturbed by other people”:

Authors Note:

Members of the Judiciary in the US are now stating without equivocation that “Privacy is only for those with something to hide”. I would doubt that anyone outside their circle of influence agrees with them.

Body:

Privacy is a basic Human Right in the EU and many other geographies and a long established Civil Liberty in the US.  These protections have been in place for many decades and yet never in its history has the notion of Privacy been under a non-stop attack from two opposing and powerful forces simultaneously; that of numerous Internet-based Commercial entities (including illegal ones via Data Breaches) and various Governments’ around the world (for national security and often immoral purposes). All believe with strong conviction that they have legitimate needs (and alleged legal rights) to freely access and use Individuals most personal data (PII) for the purposes of either Commerce or National Security. No matter where you stand on these arguments there is much to be said & argued and it has become “a pundits dream” in terms of opportunities to proffer and pontificate on the subject. All seem to be making to argument to extend their already egregious activities even further. This has created deep polarization by all parties involved with no resolution in sight.

Given all this, the central question in my mind is “Can all of these interests co-exist in some level of balance that is beneficial to all, but benign in respect to sacrificing any Privacy rights and protections that exist today, much less in the future?” I see it as one of the central challenges of our time and worthy of at least one of my columns in 2015.

The success or failure of our ability to reach a consensus on Privacy will be the great enabler (or disabler) of everyone’s dream for what the Internet, Device Applications, the Internet of Things, etc. can provide today and in the future. Without this understanding all may be lost in my opinion. In this regard I may be alone in my thinking, but only time will tell.

How do we achieve this co-existence? No matter the approach taken, building and maintaining Trust amongst all stakeholders is paramount. Today, there is precious little of this due to recent behavior by both Commerce and Governments. Most polls taken today verify this directly and expose the dilemma that Consumers find themselves in (http://www.pewresearch.org/topics/privacy-and-safety/) when trying to embrace new capabilities that technology can provide and to support their Government’s efforts to keep them safe, while maintaining control over something very critical & essential to their wellbeing i.e. Personal Privacy.

For some time now I have espoused the idea of creating a “Universal Privacy Doctrine”. I see it as an understanding about Privacy that would transcend all Governments, Geographies, Languages and Cultures, a sort of passport if you like which would guarantee everyone a set of basic protections for their Personal Privacy. Many have scoffed at this idea, but given the patchwork of laws, policies, etc. that exist on the matter, much less the global reach of the Internet and Government Surveillance it seems to be the only practical way to define a baseline of minimal protections, which can then be built upon. It ultimately solves the dilemma that if Governments’ are responsible for protecting their Citizens Privacy from others, yet can’t be trusted to do so themselves then where do you go for protection? In terms of practicalities it would take a body such as the United Nations to underwrite such a doctrine, to create the mandate and ultimately to marshal the resources required to enforce it. I would see it as “Privacy Peacekeeping” in its most basic form.

We live in a time where Commerce and Government want free and unfettered access to our most Private data and yet offer nothing in return to the Citizen/Consumer. This pendulum has swung far too much away from the status quo of many decades in respect to established Privacy Protections.  We must find a way to re-balance the scales in favor of the Consumer while supporting these other vested interests in Privacy-protected data.

*-This posting originally appeared as an article in Information Age (UK) in February 2015

For More Information:

You can read my Privacy Corner Series on IBM’s Big Data Hub: http://www.ibmbigdatahub.com/blog/author/richard-lee

In particular please check out my article & podcast:

“A matter of Trust” http://www.ibmbigdatahub.com/blog/privacy-corner-april-2014-role-trust-it-applies-privacy