Tag: Board of Directors

CDO, Information Management and Governance

When do data-dependent startups need a Chief Data Officer?

James Howard

More and more startup companies are exploiting business opportunities tied to data.  Whether developing data-dependent AI, re-imagining how to conduct familiar business processes in innovative ways, or intelligently designing and building datasets drawing from a growing variety of sources.  The common theme for this class of business is the reliance on, and exploitation of, data.

In the earliest stages, startups are focusing their energy and time on creating their product or service.  As they begin to mature, they naturally start to move toward a state where they are returning value to their stakeholders – profits.  Perhaps they plan an IPO or to be sold to an investor, or some other larger entity.

This paper explores options and approaches that companies could consider to determine if and when they should appoint a Chief Data Officer (CDO), as well as their scope of responsibilities.

What kind of startups should prioritize appointment of a CDO?

At some point in their lifecycle, any company that is dependent on data will need to implement data management processes.  These include processes to acquire, ingest, catalog, track and at some point, dispose of data. If the data is licensed or belongs to others, they will need to understand and comply with applicable obligations.  They will need to create a data architecture, build repositories and apply appropriate controls to protect the data.

This description admittedly covers a lot of scope.  So the following adds a little structure to the thought process:

Does the startup…

  1. Handle large volumes of data?
  2. Have data as core to it’s business, where completeness, accuracy and currency are critical?
  3. Have products and services that are dependent of data, but are themselves not data products?  (e.g., a website or app with data in the back-end vs. a licensed database)
  4. Need data that is licensed or procured from others?  
  5. Use personal data (PII) or health data (PHI)?
  6. Need to demonstrate data lineage or provenance?
  7. Create new data, which has intrinsic value?
  8. Live with the risk that a data incident could cause irreparable harm?

If the answer to many of these are Yes, then the company should consider appointing a CDO.  Moreover, if the company wants to go public or be bought by another company – especially a public company where the transaction is material, the startup may be expected to demonstrate discipline around the treatment and protection of data, including documented policies and procedures.  While a CDO isn’t necessary to do this, a CDO can design and implement practices and disciplines that will provide comfort in a due diligence setting, and integrate those disciplines into the daily business routine of the startup.

What value can a CDO provide to a startup?  

Removing Barriers:

A CDO can provide a range of value to a startup.  The CDO looks at a company’s business through the lens of data, and is sensitive to both the value (revenue) cycle as well as the risks and obligations, recognizing they go hand-in-hand.  From this vantage point, they can enable the business by sourcing data and removing barriers, and can implement right-sized controls, proportional to actual risks and obligations. In effect. they can enable the data scientists – who seem to always “need…more…data…” – by providing relevant data, aligned with business objectives, where obligations and risks are managed elsewhere.  Call it “unencumbered data”.

Scientific Method:

A CDO understands and recognizes the transformative potential of data, but also a balanced sense of proportion – especially when resources are scarce.  By implementing structure around the activities of data scientists, a CDO can improve the chances that research will be fruitful and aligned with business objectives – with a necessary degree of transparency for stakeholders.  

Protection and Compliance:

Most information that companies want to use will have some kind of requirements around handling.  These will emanate from one or more of the following:

  1. The data is regulated; many data projects will incorporate information about people — PII or PHI — likely controlled by one or more regulatory frameworks (e.g., GDPR, CCPA, GLBA, HIPAA/HITECH)
  2. The data belongs to others and is governed by a contract or Data Use Agreement
  3. The data is valuable and needs to be protected – these protections might be present as a result of the data being regulated.
  4. A breach of the data could result in harm or loss, either to the company or to data owners, and should cause the company to respond in a certain way.

The CDO, who should understand the nature of data, can work with the CISO and counsel to implement proper controls to protect the data and comply with requirements.

Ethics:

By understanding the business and compliance perspectives of data, the CDO can provide perspective on the ethics of data use.  So much of the new digital economy is exploring uncharted territory, where potential uses haven’t yet been imagined. There are lines not yet drawn around what industry should do, even though they can do it.  Data-driven inventions can cause real or perceived harm to consumers as they disrupt industries.  Whether its financial services, advertising/marketing, insurance, consumer electronics, or the breadth of online applications and properties.  Data is central to these and a misstep can be catastrophic.

Optics:

Transparency is a cornerstone of the capital markets.  And while data-driven startups are inventing new ways to conduct business and benefit consumers, much of it is betting on the future.  With so many unknowns, appointing a CDO can help inspire confidence that a data-dependent startup is approaching their objective with a view to managing their data assets for the longer term.

What can a CDO do?

85% of the time, “Big Data” initiatives fail to meet their objectives, and 50% of startups fail in the first year.  Start-ups relying on data can’t afford many false starts. The CDO can spearhead data management activities that can, in aggregate, reduce risk of project failure and increase the likelihood of achieving the desired outcome.  These might include

  • Vision and strategy, involving leaders across the company
  • Data inventory
  • Data architecture
  • Data acquisition
  • Data maintenance and quality
  • Data retention and disposition,
  • Risk assessments, protection and compliance processes

While these are not necessarily discrete activities, and should certainly be scaled to the situation, having a framework in place would be very useful to (1) enable growth, (2) permit introduction of different data sets, and (3) give Boards of Directors, auditors, reviewers and regulators a level of comfort that the company takes data management seriously.

Balancing cost vs value?  Alternatives…

Many early stage startups are focused on laying out the important initial groundwork to sustain themselves — developing products, recruiting talent and identifying customers.  As they move through funding stages and become established, they might be looking toward aggressive growth, IPO and engaging in discussions to be acquired. This is a sliding scale – and it may not make sense to appoint a full-time CDO initially.  Startups should consider engaging a consultant or a CDO on a contract basis to implement and appropriate framework. As time and circumstances evolve, the time commitment can be adjusted.

Who should drive the decision?

The role is so important and strategic, that the CEO should drive the decision to appoint a CDO.  The CDO should expect to work closely with the CEO, as well as the rest of the executive team. Moreover, the CDO should expect to meet with the investors and advisory board to reinforce the role and how it will help the company accelerate forward.

Conclusion

It goes without saying that startups leveraging data science are not at odds with managing data, or the scope of a CDO.  They are extremely complimentary, to the point where an CDO can dramatically improve the probability of a data program, or data-dependent startup, succeeding.  

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

CDO’s Role in Managing Data Breaches

James Howard

In the span of a week, we’ve see data breaches affecting 600 million people.  For perspective, that’s more than every man, woman and child in the US, Russia, Canada, Britain and Australia combined.  And the damage may not be done, as scammers and other bad actors frequently take advantage of the widespread confusion that follows these sorts of incidents.

Moreover, as the investigations unfold, we will begin to see the breadth and depth of what went wrong, who did what, and what steps must be taken to prevent this from happening in the future.

The risk manager in me says this will happen again, just as it’s happened before.  Data experts know all too well the challenges in implementing controls proportional risk, and counter-balancing every data initiative with the right set of controls — starting with asking whether the proposed data collection or use benefits are worth the downside risk.

So what does this mean to a Chief Data Officer?  In a word, everything. Why? Because data is at the center of every breach, and the CDO should be looking at the full picture around both data use and data risk.  The emerging role of the CDO in business positions them as a key executive in helping to reduce the risk of breach as well as to navigate the aftermath, protecting the organization’s brand.

Before a Data Incident

In the normal course of business, the CDO should be executing against the company’s data strategy and vision, and maintaining an inventory of critical data assets.  The inventory should include key meta-data — ownership, obligations, location, permissions, value, uses, etc — which forms an important part of a periodic risk analysis.  

The risk analysis considers threats, vulnerabilities, obligations and relative value of the data to conclude on appropriate protections.  The more progressive CDO’s will construct a holistic threat analysis that answers the question, “what could go wrong?” or “how might information be breached?” taking into account behavior of personnel, company culture, key business activities and positioning of the company in the marketplace.  Typically, such an analysis covers the spectrum from the seemingly mundane (accidents caused by carelessness or poor judgment), all the way to industrial espionage targeting company data, with a total of 5 or 6 categories in between. This analysis serves as a sounding board to validate the range of control activities, which includes everything from policy, to business practices, to training, to technical controls, and some instances where certain risks have to be accepted, insured against, or perhaps transferred elsewhere.

The CDO should provide business requirements to the CIO and CISO for appropriate technical measures to provide protections, which – depending on the sophistication of the company – could range from providing data classifications, to which the CISO or CIO react, all the way to explicit requirements for, say, encryption and access control.  

The inventory shines a light on whether all data on hand is truly necessary, or whether some can be disposed of.  Moreover, the CDO’s analysis of business processes using data can also question whether all data being collected is necessary.

The Board of Directors, senior executive leadership and internal audit should – to appropriate degrees – be aware of how the company is using data as well as the CDO’s assessment of risk and mitigating controls.  This will allow them to understand the risk/benefit around data use, and weigh in whether the business opportunities related to data use are sufficiently compelling.

The CDO maintains relationships with counsel to understand the legal aspect of obligations, and obtain sign-off on the sufficiency of the compliance programs.  The CDO should understand their regulators’ expectations and requirements around handling data, making sure their protection controls meet regulator expectations.  These steps are key, because most breaches — especially where regulated data is involved — will result in legal or regulatory exposure, and having transparency with counsel and regulators with streamline investigations.

The CDO should own (or be a key stakeholder in) the data incident management process. This is the process whereby data incidents — data loss, possible breaches or exposures — are logged, analyzed and investigated.

During a Data Incident

Sometimes, a target organization is aware of a data incident as it’s occurring.  Many companies have processes to respond in this event, which may focus on containment, interruption, or other priorities (allowing an attack to proceed in a controlled way may help law enforcement with their investigation).

The CDO should be available to help answer questions about the nature and location of data that may be accessed, as well as to begin preparing post-incident planning. Some data owners (e.g., Federal Government) have explicitly defined time frames to report data incidents, the CDO can get ahead of these requirements.  

Following a Data Incident

Companies should have a crisis management plan that includes defined procedures to be followed in the event of a cyber attack, data breach or exposure.  The details of these plans are tailored to each company, and generally emphasize damage control and protecting the brand — which in itself may follow one or more tracks, based on the nature of the incident.  

Stakeholders include senior leadership, legal counsel (sometimes supported by outside counsel), the head of security, the CIO and CISO, and often on-call cyber security consultants.  The overall objective is to understand what happened, how it happened, who perpetrated the event, what data was affected, overall impact, and how to repair the damage and prevent the same thing from happening again.  

Along these lines, the CDO should help assess the impact of the loss, in terms to cost to the company — defined as asset value, or competitive impact, or brand damage to the organization.  The CDO can be a resource to analyze the nature of the data to determine whether external notifications are required, and – in conjunction with counsel – whether there is a regulatory impact.  Who owned the data? Do regulators, customers, vendors, partners or clients need to be notified? Is there a timeframe requirement for notification and is there a specific process to be followed?  Do affected parties need to be offered – or are they likely to demand – compensation?

The CDO can help analyze what went wrong, by having an understanding of the processes and policy around data use.  Was there misuse of data or was it stored, processed or transmitted in ways it shouldn’t be? Was there a control failure, or absence of control?

This analysis concludes with a reassessment and remediation of processes and controls.

Conclusion

Most corporate leaders recognize the near-inevitability of a breach or hack.  This is due to a variety of factors, including the increased complexity of information systems, coupled with the expansion of data-rich cognitive and robotics initiatives, many of which rely heavily on data.  Data sets themselves are growing at a dramatic pace.

Companies are appointing CDO’s to try and coordinate the activities around the leverage of data, and increasingly, they are assigned responsibility for assessing and managing risk around data.  This is not a bad thing at all, since it helps keep risk management activities proportional to risk and the nature of the data.

CDO’s should approach the challenge with a plan, emphasizing transparency and engaging appropriate stakeholders.  Whereas today, Boards often look to the CIO and CISO to understand how data handled and protected, going forward they will increasingly look to the CDO.

 

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

Data Regulation is the New Reality

James Howard

On October 28th, the BBC’s Chris Baraniuk reported that recently, Tim Cook was in Brussels to address the International Conference of Data Protection and Privacy Commissioners.  In his remarks, Mr. Cook, referring to the misuse of “deeply personal” data, said data was being “weaponized against us with military efficiency”.  The BBC went on to report that Mr. Cook said “We shouldn’t sugar-coat the consequences,” and “This is surveillance.”

The speech reaffirmed Apple’s strong defense of user privacy rights, in contrast to competitors business model of driving advertising revenue by analyzing people online habits.   “The trade in personal data served only to enrich the companies that collect it, he added.”

Mr Cook also praised the EU’s new data protection regulation, the General Data Protection Regulation (GDPR), and went on to say that other countries “including my own,” should follow the EU’s lead toward protecting personal data.

To be sure, economics are at the heart of the concern.  Given the string of events that have occured, where data is mishandled or exposed, companies are at risk of losing customer and stakeholder trust, and without that trust, it not clear how they can drive or thrive in the data economy.  So coming together in support of a GDPR-like framework makes sense; it raises the conversation to a global level, and can result in a safer and more efficient environment in which to conduct business. Companies that embrace the framework will have more flexibility and resilience, while those firms paying it lip-service will eventually themselves be at the center of their own data crisis.

And therein lies the rub.  Compliance is not the same as data protection, especially when the regulation is principles-based and not prescriptive.  If the objective in implementing a framework is to comply with a regulation, one is tempted to overlay one’s current operating model with the requirements of the regulation and address gaps.  While it may reduce the risk of data incident, it will probably do so by coincidence.

On the other hand, if companies went about handling information with the strongest possible ethics, where they routinely assessed and addressed risk, recognized and avoided moral hazards, then the incidence of breach and miss-use would naturally be much lower.

The obvious competitive issue is that the second scenario is more expensive and less flexible.  Moreover, if a minority of companies took this approach, they would be less prosperous, and economic darwinism would cause them to go extinct.  And suppose there were a major data “catastrophe”, and the market environment were made up of a combination of those that embrace a high degree of data ethics and those that don’t, the market may not recognize and reward the higher resilience of the highly-ethical-but-less-profitable.  Instead, what we’ve seen is the mainstream market reacts with shock and incredulity and – at the prompting of regulators – implement newly-penned frameworks meant to avoid future occurrences of those events.

While one might argue that black swan events are by definition unforeseeable, one can equally argue that waiting for them to strike before implementing any sort of protection strategy simply opens the door to more black swans, and when events do occur, they result in unnecessarily high impact.

Apple’s Tim Cook makes clear his view that status quo is unacceptable.  As an unquestioned highly credentialed leader and insider in the technology (and information) world, his use of words like “weaponized” and “this is surveillance” should not be taken lightly — he knows what he’s talking about.  No doubt more so than the rest of us.

So as with most things, a thoughtful balance must be considered.  The dilemma is how to balance among the following:

  1. The rapid growth the volume to data aggregated by companies, across the board from business-to-consumers, to business-to-business companies, and ranging from companies providing services to those providing goods — and the increasing overlap.

  2. As a subset of that, the increase in the volume of personal data stored online, and the ability to gather even more data about individuals – habits, interests, locations, views and opinions.

  3. The rapid evolution in the science of data analytics, and the ramp-up of technology able to manipulate and compute data on a mammoth scale.

  4. Coupled with this, is the increasing ability to combine and analyze datasets in ways that allow for the creation of new and credible data and conclusions.

  5. As the size and richness of the datasets grow, so do the consequences of an event (whether a breach, misuse, abuse or exposure).  These range from a sense of creepiness when personal data is exposed, all the way to the very real consequences of insidious manipulation of our views and opinions.

In short, how can companies derive benefit from data, while managing the risks?  Neither momentum is letting up — the momentum around utilizing the expanding datasets, or the momentum around data events and subsequent responses from regulators.

One realistic way is to embrace and build a culture around managing all aspects of data, in lock step.  This is built into a data management program, led by a Chief Data Officer, comprised of three interdependent functions:

  1. Data Leverage, focussed on enabling the business use of information,

  2. Data Protection and Compliance, focussed on addressing risk resulting from data leverage, in terms of misuse, loss or non-compliance with obligations

  3. Data Quality, ensuring that the data being used retains its accuracy and integrity

This model is coupled with appropriate oversight, in the form of:

  1. A steering group with senior stakeholders from across the company,

  2. Direct oversight by CEO or COO,

  3. Connectivity into other key functions, including the CIO, CISO, HR and Legal,

  4. Active oversight by the Board of Directors, to support business initiatives and agree with risk mitigations plans.

A standing filter for any and all data initiatives needs to be ethics, and a consideration for the consequences of the genie getting out of the lamp.  Is the company willing to handle the outcome, if an initiative goes wrong? What is the risk, how is it managed, and are the right people accepting the residual risk?

The discussion is reaching a fever pitch with leaders of the most influential technology companies adding their voices to the conversation.  Any company wanting to join the data economy should consider doing so with an appropriate data management framework. This will position them to accelerate as new opportunities present themselves, while being able to manage events as they occur and accommodate compliance requirements that arise.

 

Information Management and Governance, Information protection, Uncategorized

Data Ethics and the CDO

James Howard

A wise man once told a cheeky arachnid, “With great power comes great responsibility!”

This is a particularly relevant quote in the context of the evolving data economy. CDO’s may think of themselves as caped crusaders saving mankind, and the truth is they are indeed playing an increasingly critical role to help ensure that organizations can successfully transition to their rightful place in the new data economy.

Consider the following:

  • Overwhelmingly, CEOs believe leveraging data as an asset will be more than a game-changer, and will soon become a critical differentiator to remain successful and relevant – and not all companies will make it;
  • Available data – both volume and variety – continues to grow at an impressive rate;
  • Data science and tools are moving in lock-step with the data growth, finding new ways to derive value from data, creating transformative and disruptive opportunities;
  • Data events – intrusions, breaches and exposures – are also growing at an alarming rate; in 2018 alone, hundreds of millions of people-related records have been targeted, exposed or breached (and that’s just the ones detected); and
  • Regulators – notably the EU and the State of California – are responding with complicated requirements, that will impact a great majority of organizations, and more jurisdictions will follow.

What is the role of the CDO?

The CDO’s primary responsibility is to establish the vision and execute a strategy to leverage data in a responsible way.  This ranges from monetizing data directly, through sale or licensing data, to creating new or enhancing existing products and services with data, to optimizing operations by augmenting decision-making with data.  This is a tall order, and needs to combine insights into available opportunities, maturity of the organization to embrace change, and expectations of organizational Leadership with the support they provide.  After all, if leadership isn’t on-board, a data program is not likely to be successful.

The other responsibility addresses meeting the obligations tied to the data, which starts with data ethics.   Just because we can do certain things with data, should we?  Consider some inputs to that decision:

  • Harm– As with medicine, and as the business person overseeing data initiatives, the CDO should start from the commitment to “do no harm”. The CDO should have a methodology for analyzing and socializing potential data solutions to understand the potential consequential impacts.
  • Legality– The CDO should collaborate with counsel to develop a clear understanding of where legal boundaries lie. As with “do no harm”, organizations should not break the law.  The CDO has an important role, because sometimes there is legal risk (heightened probability that a law will be – or perceived to be – broken), and analysis presented to decision-makers should be clear.  As with other cutting edge sciences, senior leadership may not be as data-literate as the CDO or the data scientists.
  • Expectations– An initiative may be “legal” – technically – and even cause no actual harm, but the organization should be comfortable that stakeholders or clients would not be so disappointed with an outcome that the organization’s brand is impacted or clients go elsewhere. A consumer-client has a different tolerance level than client-companies; consumers take reactionary queues from society, media and social-networks, often with unpredictable results.  Client companies have their own stakeholders, regulators and clients to look out for, which drive their reaction.  Moreover, an un-harmful but “creepy” initiative may draw unwanted scrutiny from a regulator, resulting in the organization expending resources to address.
  • Profit – will the initiative make money, even if risks are mitigated and obligations are met, and expectations are intact? A CDO will be presented (pitched?) with dozens of cool ideas, and has to know how to analyze them for fit within the organization. This is trickier than it seems, because data science presents data-oriented opportunities in organizations not used to the data economy.   The decision-making process around investing in a new plant or product in, say, a manufacturing company may be very different than deciding to invest in a data-driven feature or capability.  And simply “willing it to happen” isn’t enough.
  • Consequences– Suppose the organization bets wrong.  What if the initiative fails to deliver on the planned profit, or simply doesn’t work?  This is manageable through various pathways – insurance, hedges, accounting treatment, etc.  But what if the organization creates a proverbial monster?  Recent debate around AI comes to mind, with AI appearing to evolving in lab settings.  What if, in hindsight, the organization realizes they did something deeply wrong or harmful – should they have been expected to anticipate and alter course?  Recently, companies have ceased to exist because they pursued what seemed like sanctioned or low-risk data-driven initiatives, failing to anticipate social and political outrage.

The data economy presents opportunities never before available to business.  Some organizations will choose to gamble risk against profit.  Others will take a step back and forego immediate opportunities, adopting a wait-and-see attitude.  Some from each group will succeed while others fail.

Like any new science that affects humanity, data science should adopt a canon of ethics that balances achieving benefit against the risk of harm.

No doubt the CDO plays a central role in making or orchestrating decisions and administering data.  As the steward of the data vision and strategy, the CDO must be able to think through the upsides and downsides with balance and objectivity and be willing to stand behind the ethics of decisions, after the fact.

Contact me at james@jhoward.us

Uncategorized

Data Literacy and the CDO

James Howard

I attended a CIO Event in New York today and there was a great session focused on Data Literacy, presented by Jordan Morrow from QlikView.

Simply put, Data Literacy (in a business context) is a person’s ability to read, understand, analyze and communicate data as actionable information, including using data to support an argument or a proposal.  Jordan conveyed that only ~20-33% of those surveyed (including senior executives) considered themselves Data Literate. At the same time, 80% of senior executives see leveraging data as an asset will be critical for continued success and growth.  

Responsibility for increasing the data literacy falls to the CDO, and should be a high priority, as it is a prerequisite for an organization achieving maturity in the data leverage space, and is a springboard for data innovation.

The benefits are clear.  If an organization achieves a higher level of data literacy, they will:

  • Be able to define a vision that more closely aligns with overall mission
  • Develop a strategy that aligns with culture and is more implementable and focused on achievable objectives
  • Distribute the execution across the organization with more stakeholder buy-in
  • Include data as a basis for decision-making
  • Improve professional skepticism around quality of data

If people are sensitive to the nature of data, they can be expected to incorporate risk-awareness when deciding how to handle data – for example, knowing they are handling PII may cause them to exercise better judgement around it’s treatment, or ask an SME for guidance.

It’s a tall order, especially given the acknowledged low current state of literacy, but can still be approached in a pragmatic way.  There are a number of methodologies out there for increasing Data Literacy that can be adapter to an organization.  Here are some thoughts on approach:

  • The CDO should chair a leadership-level steering committee with representation from all business areas, which sanctions the CDO’s agenda and champions the program;
  • Data Literacy should be on the agenda as a core element and critical-success-factor;
  • Steering committee members should become data literate;
  • Careful thought should go into how the literacy program in rolled out:
    • Culture is hard to change (and requires ongoing messaging and overt steering committee/senior leadership support)
    • Training triggers eye-rolling, especially if it’s not closely tied to a person’s day to day responsibilities
    • Raising literacy is iterative, and should be tied to roll-out of capabilities or products, so awareness and training is relevant and just-in-time.
    • Wins should be celebrated.
  • Since richer datasets might incorporate regulated data, Data Literacy training/awareness should cover appropriate data handling, based the nature of the data.  This has the added bonus in that if it’s delivered just-in-time, it will be more relevant to the use-case being introduced.

I came away from the CIO Event reminded that even though CDO responsibilities are growing on the market-facing side (e.g., data monetization), they should also be responsible for ensuring everyone in the organization is realizing the benefits of the “data economy”.

Contact me at james@jhoward.us