CDO, CPO, Information Management and Governance, Information protection, Privacy

Role of a CDO Supporting Boards of Directors

Executive Summary:

Companies are increasingly looking to leverage data as a new revenue stream or a way to increase efficiency.  However, risks related to data breach continue to figure prominently on Board agendas. A Chief Data Officer acting as an advisor can help Boards and Executive Leadership understand the risks and opportunities around data, which in turn, helps Boards fulfill their responsibilities to the organizations they oversee.

Introduction

Boards of Directors have an important and challenging role.  Among other duties, they are responsible to stakeholders for the performance of the organization they oversee.  This includes not only helping to enable business directions and objectives, but also ensuring Management properly identifies, manages and mitigates risks.

Two areas stand out among the ways that information and data figure prominently:  First, business opportunities created by rapid developments in data science and related computing platforms, and second, risks relating to data breach and loss, often under the heading “Cyber risks”.

Business opportunities

Business opportunities tied to information are becoming more important to companies.  Specifically, the significant increase in the role information re-use, leverage and monetization plays in many companies’ strategic plans, increasingly tied to AI and Digital Strategy.  These are outlined in terms of leveraging data science and the abundant range of available data to:

  • Create net-new products and services, including monetizing data, or
  • Enhance and augment existing products and services, or
  • Enrich management information to drive efficiencies.

These initiatives are not trivial, and the potential benefits are huge, whether as new revenue streams, or optimizing operations; many organizations view leveraging information at the strategic level as critical to their continued success – a matter of survival.  Paraphrasing George Orwell, “whoever controls the data, controls the future.”

And momentum is building at a remarkable rate, both in terms of the volume and breadth of usable data, as well as the sophistication of the tools designed to analyze and leverage data.  

Information risks and obligations

Information-related risk presented to Boards and senior executive leadership are often grouped together under the broader topic of Cyber.  These are generally risks related to breach of systems, theft or unauthorized disclosure of data, intrusions, threats to the integrity of systems and data, and the risk of system outages and disaster recovery.  Many recent incidents are where data is exposed on the internet and where the company realistically has no idea whether an actual loss has occurred.

A second category of information risk is also rapidly emerging with increasing consequence, and that relates to compliance with privacy-related information handling obligations and regulations.  These include, for example, the recently enacted EU GDPR (affecting the handling of personal information belonging to EU citizens), HIPAA/HITECH (affecting the handling of health information), and California’s CCPA (affecting the handling of personal information belonging to residents of California).  

Beyond the regulations, there are increasingly explicit requirements for handling data belonging to other stakeholders, spelled out in contracts or other “data use agreements”.  

Consequences for violating information-handling obligations include,

  • Financial: lost productivity, loss of customers, loss of competitive positioning, etc.,
  • Regulatory: fines or other measures imposed by regulators, if the company was at fault.  In the case of GDPR, fines can be as much as 4% of revenue.
  • Brand: loss of customer trust and confidence in the company’s ability to deliver, or to protect information entrusted to them.

Key questions

When evaluating company’s use of data, Board members and executive leadership should ask themselves certain key questions around how data is being leveraged and managed.  These include:

  • What approach is the company taking to leverage data?  What is the vision? The strategy? Is governance a component of the strategy?  Many companies are racing to implement data leverage plans, and in their haste to make headway, many have been hiring data scientists in leadership roles to drive tactical plans ahead.  As a result, governance is often overlooked. However, without proper governance, it will be hard to create a credible strategy reflecting the needs of the business, as well as identify all the opportunities, priorities, costs and risks.
  • Is the data leverage team (“data scientists”) following elements of the Scientific Method?  Many people calling themselves Data Scientists are proposing initiatives where they requisition increasing volumes of data so they can see what opportunities they can come up with.  By itself, this approach introduces risk, since the company may not have a clear idea what they are getting for their investment in big data. By analogy, pharmaceutical companies wouldn’t fund researchers to “play” in the lab letting them see what new drugs they can invent.  Companies pursuing plans to leverage data should do so following some formal methodology which includes articulating and testing hypotheses.
  • Has a data inventory been performed?  What obligations are tied to the data?  Most companies have sizeable volumes of data on hand, and many are asking how they can monetize and leverage the data.  An inventory is critical if the company is going to leverage or monetize data, and knowing obligations is key to understanding what you can do with data and structuring protections.
  • What is the most valuable data and where is it?  Most data classification schemes are very basic — only 2 or 3 classifications.  While these are simpler to implement for security purposes, they aren’t useful for determining relative value of data or what data is key, and can interfere with otherwise appropriate use and access.
  • Who has access to data, and is that access appropriate?  Without proper data governance, you can’t reliably know whether access to data is appropriate.  Being able to answer this question is required under certain privacy and banking regulations.
  • Is it available to the people who need it, and are safeguards appropriate?  Leveraging data requires that the right people can gain access to the data.  But even while its being processed, certain safeguards still need to be in place, and these may be different than for data “at rest”.
  • Have risks to information been assessed along IT and non-IT lines?  Risks should be assessed based on the business processes that manipulate data — not just IT repositories holding data, or applications touching data.  People are the biggest cause of data incidents, and are responsible — in some way — for most “insider threat” incidents.
  • If information were lost, stolen or exposed, how would you know?  Most companies invest in preventing theft or misuse of data, but its extraordinarily difficult to know when data has actually been breached.  Most of the time, companies find out when an outside agency — such as law enforcement, the press, or a “hacktivist” group tells them. Proper data governance and inventory can help reduce the risk of data loss, and allow the company to focus protection efforts on more important data assets.

Step back

Many enterprise risks concerning data elevated to the Board focus on the technology aspects of the risks.  This is often because that is how the company is organized — anything loosely connected to “data” is directed to the CIO and CISO.  Digging into the risks, however, often reveals that the underlying concern is data: it’s use and the consequence of an incident. Taking a step back, if the concern is data, it may be helpful to separate the data from the IT platform it sits on, and from there, zero-in on the issues – both opportunities and risks.

The role of CDO

Increasingly, companies are appointing CDO’s — Chief Data Officer — tasked with implementing governance over the data initiatives, and aligning activity to execute data strategy.   The responsibilities of the CDO vary across organizations, but in general, they should be looked to by the Boards to help understand and navigate data-related matters.

A good CDO focuses on all aspects data – opportunity, risks and obligations.  They are conversant on the technology tools that process, store and transmit data, and can help the Board members understand the topic with clarity so they can engage with executive leadership.  Board members should consider seeking support and advice from experienced CDOs to help them navigate data-related matters in the organizations they oversee.

Conclusion

Data has always been critical to organizations.  In recent years, its increasingly being recognized and treated as an asset that can be leveraged to provide added benefit to organizations, whether through increased revenue or operational efficiencies, and that benefit is tied to the rapidly evolving field of data science as well as the incredible growth in available data.  With the increased prominence of data at the strategic level, Boards of Directors and Senior Executive Leadership are expected to understand and provide direction around the use of data and management of related risks. CDO’s can serve as a valuable resource to help Boards in fulfilling their responsibilities.  

Contact me at james@jhoward.us

Information Management and Governance, Uncategorized

Role of the CDO: Learning from the Past to Enable the Future

The role of the Chief Data Officer is evolving quickly, and has been compared to the CIO of the early 90’s, in that the CIO role was just starting to take shape, companies were just beginning to appoint CIOs and they were struggling to define responsibilities.  The similarities don’t end there. Consider:

  • Early CIO’s had strong IT backgrounds, but often didn’t truly understand the business they were supporting.  In some other cases, it was the exact reverse – the CIO was a business person with limited (or no) understanding of IT
  • The CIO was a “second tier C-level executive”, often reporting to the CFO.  This was often because in those days, the CFO was thought of as the principal consumer of IT, and companies failed to recognize how computers – notably PCs –  were penetrating and enabling other areas of the business. This lead to frustration among users, “shadow IT” lacking formality and control, and an incomplete understanding of the overall IT portfolio and spend.
  • Every CIO was different, and every IT mission was different, and highly tailored to each company.  In hindsight, the industry was “fumbling” (a term not meant in a disparaging way) as the IT industry went through a massive evolution; some may remember Tom Watson’s prediction that there would only ever be a market for maybe five computers.
  • The CIO’s senior staff were often technically proficient in their respective areas, but not very aware of the needs of the business they were supporting – and they lacked the tools to build the necessary bridges.
  • There was very little interface with “users” (a new term at the time) because most systems under the CIO’s purview were specialized and vertical, or were infrastructure – and end-user computing was evolving on its own, outside the CIO’s scope of responsibility.
  • Numerous “disasters” have taken place tied to IT (whether failed initiatives, outages, breaches or hacks) and the post-event analysis often failed to properly address the underlying issue, perhaps due to lack of understanding, or a desire not to reveal the extent of the issue, or because the business was not fulfilling their responsibility relative to IT governance.

In 1994, Charles B. Wang published the book “Techno Vision: An Executive’s Survival Guide to Understanding and Managing Information Technology”.  In the book, Mr. Wang shines a light on the “disconnect” between IT and the business they support, as it relates to understanding the role technology can play, and he makes suggestions on how to address the gap.

Now in 2018, the CIO is a universally accepted role, but there are still plenty of examples where the CIO has limited (or no) understanding of the business, and the business leaders’ eyes glaze over when any technology topics arise.  And IT is one of the largest line items on corporate budgets.

Enter the CDO

Conservative predictions foresee a massive increase in number of information-related products and services, as well as company spend on information-related initiatives.  Not to mention the exponential growth of information itself.  It’s helpful to look at the “typical” CDO in 2018, as a way to anticipate trajectories and avoid similar pitfalls that were seen with the evolution of the CIO.  Consider for comparison:

  • Most organizations are recognizing the transformative potential that exists in leveraging information, but the majority have not appointed CDOs.  And some organizations have appointed CDOs internally who don’t have an information management background.
  • Many organizations have emphasized the technical aspects of information leverage, and have appointed Data Scientists as the top leaders in information management, who in turn have flushed out their teams with data scientists and analysts.
  • Certain segments of the market – insurance, for example – seem to view information management as an “IT thing” and often place the CDO under the CIO, which immediately limits their ability to be successful.
  • Many companies are reacting to steps taken by their peers, and have appointed “me too” CDOs with limited thought to their responsibilities, scopes and measures.  As a result, vision and strategies are incomplete or non-existent.
  • Upon arrival, many CDOs are dumped on, getting assigned responsibilities that are at best loosely tied to information, but weren’t necessarily part of the scope originally envisioned.  This immediately interferes with their ability to deliver, even if the new responsibilities are appropriate and legitimate.
  • CDO’s teams are often thinly staffed, and are expected to transform the organization by exerting political influence on other leaders, often who have conflicting agendas or are protecting their turf.
  • Many business leaders speak about, but don’t understand, the strategic role that information leverage can play in their organizations, due to a lack of data literacy.

To be sure, none of these should be seen as evidence that the CDO is a passing fad or a failure.  Quite the opposite: there is a recognized need for a CDO, who is emerging as the executive who must pull together and execute a strategy to gain benefit from leveraging information.  Unlike other trendy business fads, the CDO is tasked with making use of a resource that is already there – and growing – increasingly recognized as key to greater prosperity.  By investigating the challenges faced by many early CIOs, there are opportunities for the CDO to learn from the past, and avoid similar issues.  

Support and Empowerment

For most forward-looking organizations, the CDO should be a company-wide role.  The CDO should be seen as a senior executive, should report to the highest levels of the organization, and have broad authority to effect policy and influence behavior.  They should have visibility and accountability to the Board of Directors. In terms of support, the CDO should have resources to execute in a credible way, including personnel and tools.   

Scope and Responsibility

If an organization believes that information is their lifeblood, and that leveraging information is key to continued success (or relevance), then they are acknowledging the strategic importance of information.  The CDO’s scope should align with the role information plays — both in terms of opportunity and obligation. Meaning, they should be tasked with deriving benefit from information in a way reflective of their business, but should also be responsible for ensuring obligations are met and risk is managed for that data.  

Qualification

The CDO is not a technician; they are a business executive.  While it is difficult to imagine there are enough CDO’s in the market who have deep understanding of the businesses of their employers, a good CDO should be able to bridge their skills as an information leader to the businesses they are tasked with enabling.  Just as a banking or manufacturing executive knows banking and manufacturing, the CDO knows information management. And just as that banking or manufacturing executive doesn’t understand every technical nuance of their business, the CDO needs to know enough to direct and guide their specialists.

Structure

Charles Wang, in his book, discussed the disconnect between IT and the business they support, and the risk of this occurring with the CDO is just as real.  In the 24 years since he published the book, some business leaders are just as illiterate in IT as they were then, but the breadth of tools is immeasurably wider.  Data Science is maturing at an incredible pace, and businesses are struggling to understand the intersection between what they do and the potential value data can add.  To help address this, the CDO needs to establish strong relationships with the business counterparts, and help develop data strategies. They need to work with the data scientists to identify potential use cases and opportunities with data, getting the business leaders on board.  While the CDO has a high degree of responsibility for helping execute the data strategies, ultimately the business leaders are accountable to their own stakeholders for the success of the data initiatives within their areas.

One model to establish and maintain the relationships is through a governance council or steering group, chaired by the CDO and attended by senior leaders across the organization.  The members are responsible for their own information investments, and attend the council to help ensure alignment to vision and consistency of strategy.

Scientific Method

WikiPedia tells us that:

Scientific method is an empirical method of knowledge acquisition, which has characterized the development of natural science since at least the 17th century, involving careful observation, which includes rigorous skepticism about what is observed, given that cognitive assumptions about how the world works influence how one interprets a percept; formulating hypotheses, via induction, based on such observations; experimental testing and measurement of deductions drawn from the hypotheses; and refinement (or elimination) of the hypotheses based on the experimental findings.  (before the reader dismisses this for having come from Wikipedia, the definition is pretty consistent with other sources)

The adoption of Data Science in business frequently takes a very different approach, where data scientists are empowered, and ask for more and more data to “play” with to see what they can come up with.  Perhaps this was the result of companies moving directly to the technical solution without first establishing a business vision and strategy, in coordination with their own business leaders. While some very interesting discoveries were probably made, there is likely there were a high degree of false starts, or developments that served no business purpose, or instances where the obligations limiting use of data were violated.  And without an appropriate degree of skepticism, can they be certain the algorithms really work?

Perhaps a more structured approach makes sense, taking a page from Scientific Method.  The data strategy should be articulated by the business, and transformed into a series of initiatives, some of which require research and experimentations. Certain of these should be treated like research endeavours with hypotheses formed – with significant participation by both the data scientists and the business stakeholders – which are proven in a lab setting before productizing and deployment.  

Relationships

The CDO is going to have to rely on relationships to a great extent for several reasons, including (1) the role is new and evolving, (2) many of the responsibilities the CDO should take on are initially held by others, leading to political turf-wars, and (3) at least initially, the responsibility for execution of initiatives is shared with other business stakeholders.  

Certain key relationships stand out, including:

CIO: The CDO’s initial scope probably most closely overlaps with the CIO, partly because up until the CDO’s appointment, many information-related initiatives were likely assigned to the CIO by default.  It’s critical that the relationship evolve more to a service-provider/client model, where the CDO looks to the CIO to develop technology solutions to meet business requirements for information management, and the CDO has to be careful not to overstep and attempt to drive the architecture of the solutions.

CISO: A key responsibility for the CDO is information protection.  Whereas the CISO has historically been responsible for blanket IT security, the CDO should have greater insight into the relative value of information sets, as well as how they should be accessed, transmitted and processed.  Moreover, the CDO should have greater insight into unique handling obligations tied to particular information sets. Meeting those obligations and protecting the information is likely achieved by a combination of controls — administrative, technical, manual, policy, physical, etc., responsibility for which may initially be spread across the organization.  So the CDO should emerge as a stakeholder for the CISO, where the CDO provides requirements and the CISO implements controls to address those requirements.

CPO: Much of the information leveraged by an organization might be subject to regulatory requirements, and some of those my fall into the category of PII, generally managed by the CPO.  Whereas the traditional scope of the CISO overlaps with the CDO, in the case of the CPO, the CPO’s scope is entirely contained within the scope of the CDO (after all, the second “I” in “PII” stands for “Information”).  The privacy rules are only one set of obligations, and apply to only a portion of an organization’s overall information portfolio. So logically, the CPO should move into the office of the CDO — with appropriate relationships with legal counsel to ensure regulations are interpreted properly.

Regulators: In organizations beholden to regulatory oversight (banks, insurance companies, accounting firms, government contractors, healthcare institutions), analysis reveals that a key concern driving the regulations is the handling of information.  And since the CDO’s objective is to manipulate and leverage information, it follows that it’s critical for the CDO to ensure that proposed data-use initiatives conform to regulatory requirements by design. Moreover, everyone — including regulators — are grappling with the new ways information can be used, and the appropriate ways regulations apply.  So it’s critical that the CDO establish a relationship with their regulators, so the regulators see the organization’s use of data through a clear lens and react fairly. This also provides common ground and language in the event regulators identify potential issues — or if data incidents occur.

Risk Management: Most larger organizations have recognized the importance of proactively measuring, monitoring and mitigating risk along lines appropriate to their business structure and objectives.  These evolve from time to time as the business environment changes – for example, the formation of IT Risk Management functions over the last 10 years. They are very useful for a variety of reasons, including establishing a common understanding of what can go wrong, potential consequences, and agreement on appropriate mitigating steps to take.  Given the rapid emergence and evolution of data science — algorithms, AI, cognitive, etc., — the market has limited experience with assessing data risk, grappling issues, and establishing a balanced risk acceptance/mitigation model. And this evolution is taking place at a pace far greater than control and risk management techniques. In the past, implementing formal Risk Management usually follows a catastrophic event that serves as a wake-up call, and the pendulum swings hard back toward the conservative end of the spectrum.  That in itself is a risk, since organizations might overcompensate, lose momentum, give up favorable market position, and miss opportunities while the re-trench. A much better approach is for the CDO to incorporate risk management into processes, by design. Risk should be assessed during design phases and mitigated during development phases, not after the fact.  This strengthens the argument for embracing Scientific Method during the development of data initiatives.

Conclusion

These are exciting times to be involved with information management.  The science is evolving and technology is becoming powerful enough to allow organizations to do incredible things.  Companies are scrambling to invest and exploit the opportunities created by data, and are placing sizeable bets on what they hope will return profit, with some degree of luck.  But “hope” is not a business strategy, and some argue there is no such thing as “luck”. Appointing, supporting and enabling a CDO is a significant step to help ensure success of the program, and applying lessons learned from other new classes of executives can help ensure the success of the CDO.

Contact me at james@jhoward.us

Information Management and Governance, Uncategorized

The Case for a Broad Scope CDO

Information exists is all forms, spread across organizations, and available throughout the marketplace. Forward-looking organizations are identifying and categorizing information assets with a view to leveraging it – perhaps by enhancing existing products and services, by creating net-new revenue opportunities, optimizing business or financial operations, or to more effectively manage risk.

Treating Information Like an Asset

Like with any asset, and as a responsible business person, the Chief Data Officer (CDO) establishes the vision and goals for information use, and implements strategies to achieve that vision – whether they are monetization, product/service-enhancement or business optimization.  As a responsible steward, the CDO governs the information through its lifecycle, and manages risk in a way proportional to the threats, and in consideration of the value of the asset and stakeholder expectations.  

Handling techniques are aligned with the nature of the information and take into account the way the business wants to use information; 

Depending on how the information is stored, transmitted and processed, threats and vulnerabilities may run the gamut of cyber – from traditional hacking all the way to sophisticated industrial espionage schemes – as well as non-technology based threats, such as physical loss, destruction or theft. 

Depending on the nature of the information, it may be subject to a variety of obligations – contractual, GDPR, PCI, HIPAA/HITECH, GLBA, client expectations, etc., many of which include principles-based and/or prescriptive handling requirements, with a wide range of legal, financial, and/or brand damage consequences in the event information is mishandled, lost or breached.  

Stepping Back

So taking a step back, we’re describing a business environment where

  1. The market is demanding a greater degree of data use,
  2. Data science is providing ever expanding opportunities, and
  3. The range of vulnerabilities/threats/obligations are more complex than ever.  

Everyone seems to be focusing on information, and the opportunities and stakes are huge.  Responsible organizations wanting to lead their industries will exploit information assets, meet compliance obligations and manage risks proportionally – and as a result, derive value. 

Role of CDO

It is difficult to see how to manage information in a balanced way in a traditional organizational structure where the revenue/leverage focus of information is separate from the protection focus, which is further separate from compliance focus.  It would seem unrealistic to expect to be fast-moving, nimble, risk-aware and compliant, if data leverage, protection and compliance are all managed in parallel organizations, often with different success criteria and subject to different measurements.  

Organizationally, this suggests building the Office of the CDO by pulling together:

  1. Data vision and strategy: interfacing with senior and business-line leadership, establishing a vision for data use, and defining the strategy to achieve the vision;
  2. Data Governance and Management: designing, building and operating processes and controls for handling information throughout its lifecycle;
  3. Obligations compliance: monitoring and respecting the rules and expectations; and
  4. Information protection: understanding threats and vulnerabilities, and ensuring they are addressed in a proportional way.

Among business trends, information leverage is seen as having the highest potential to deliver maximum value back to organizations.  To derive that ROI, the CDO needs to have the organizational authority to influence and/or drive activity across the enterprise, whether it’s to enable existing product lines’ information ambitions, or to cut through organizational politics and roadblocks.  To achieve that they need to report to the highest levels of the organization, accountable to the management committee and Board. 

Advantages

This model has a host of advantages:

  • It enables senior-level visibility and buy-in for information-related initiatives, 
  • It focuses talent on exploiting and managing a critical corporate asset as a primary objective,
  • It forces the protection efforts to operate in a way that’s proportional to the value of the assets being protected, and the risks to which they’re exposed,
  • It aligns compliance to the way an enterprise wants to use information, and the relevant aspects of the obligations,
  • It raises the profile and creates focused awareness around the information assets,
  • It provides for career opportunity and satisfaction for the participants, because they are more closely exposed to the revenue cycle of their employer, and
  • It aligns investments more closely with objectives and return.

Information is increasingly viewed as the new natural resource. It presents opportunities that can be exploited along with risks that can be managed.  And the pace of change is increasing. Organizations should lay the groundwork now to position themselves for the new Information Age. 

Contact me at james@jhoward.us

 

Information Management and Governance, Uncategorized

Innovation and Data

Data Explosion:

As a benefit of advances in technology, the volume and availability of data is increasing exponentially, including the ability to collect rich data as collateral from operational transactions.

Sensors permit the increased gathering of data, some of which can be procured commercially – performance data from jet engines, weather data around seasonal storms, wrist band data from families visiting amusement parks, patient data from medical devices, etc.

Key Advances – enabling data innovation:

Advances in algorithms enable more sophisticated analysis of data – intelligent automation, cognitive –  creating the ability for automation to become more seamlessly integrated into the user experience. Most – if not all – are hugely dependent on the quality and availability of data.

Advances in cloud platforms enable the analysis of larger volumes of data, more opportunistically with on-demand, cost-effective scaling.

Within organizations, data can be classified into the following:

  1. Marketable data– data-oriented products or services that have market value, whether in raw or refined/aggregated form
  2. Management data– KPI information gathered from business systems, used to inform decision makers
  3. Transactional data– information generated from an organizations business activities, whether banking transactions, audits, sales activities or IoT logs
  4. Operational data– Presentations, R&D activities, thought pieces, brochures, client data processed by employees

Opportunities for Innovations:

The evolving discipline of data science is imagining new, innovative and creative ways to combine data, extract “signals” and drive value – whether its from anticipating possible outcomes (mortgage defaults as a function of weather patterns and number of computers), identifying lost revenue (hospital networks providing costly diagnostic services, but losing higher margin treatment revenue), or identifying interesting correlations (consumer buying patterns following summer storms)

Each of the above classifications of data present opportunities for innovation:

  1. Marketable data is the holy grail: with appropriate governance, harvesting and deriving revenue from data available as collateral from business.  Innovation drives things such as, how can the data be refined or enriched to increase value to licensor?  How must it be anonymized to meet regulatory requirements?  How to achieve fair share of downstream revenue?
  2. Enriching management reporting and optimize processes by introducing additional data e.g. road construction plans influencing product delivery routes or performance of local sports teams affecting snack sales;
  3. Transactions can be mined to optimize performance, contribute to regulatory or management reporting and can be refined with robotics and intelligent automation
  4. Operational data can be cataloged, leveraged – avoiding re-creation – and tracked for compliance with regulations or client expectations, or disposal

Contact me at james@jhoward.us