Will Artificial Intelligence help Big Data deliver on its promise?

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One of the major trends I have been researching recently, has been the shift in interest towards Artificial Intelligence (AI) in its multiple forms and guises, and the potential it has to analyse vast quantities of data and quickly derive actionable insights. As we all know, AI, Machine Learning and Deep Learning are not new. However, there has been huge investment in the space in recent years and the ability to automatically apply complex mathematical calculations to Big Data – over and over, faster and faster – is a recent development. With steady advances in digitisation and cheap computing power, no wonder people are excited about the possibilities.

One of the areas of AI that gets the most attention is Deep Learning. Researchers have been attempting to train algorithms since the 1970s but limitations, be that computational or data related, slowed that progress. Whilst the algorithms we use today were, for the most part, created decades ago, we were unable to use them effectively. It wasn’t until new technology became available, that they could be applied to massive amounts of data, cheaply and quickly enough that they had the chance to live up to their full potential and help Big Data live up to its promise.

One area which will be interesting to observe is the relationship between Data Scientists and AI. As AI and Machine Learning progresses and evolves, some of the more basic and straightforward tasks that Data Scientists perform  routinely will become automated and will yield great results in productivity. AI is certainly not going to replace Data Scientists any time soon, and can in fact be a massively helpful tool to utilise, however how will they view it: Friend or Foe? Could this also be one of the many ways that the industry can combat the talent deficit, automating the more basic tasks and reserving the more complicated Data Science processes for the Data Scientists?

Today, AI enables computers to communicate with humans, autonomously drive cars, write and publish sport match reports, beat them at board games and find terrorist suspects. The possibilities are endless and will no doubt change the ways in which we will live our lives in the future. Not only does AI present new possibilities in our day to day lives but also within wider reaching areas such as national cyber security, and special projects to combat human trafficking and arms dealings such as the collaboration between NASA and DARPA . When speaking with an expert recently, we were discussing one algorithm which predicts the likelihood of a criminal reoffending and the ways in which this was being used in a courtroom setting to help judges determine a sentence and future parole opportunities. There are also huge opportunities within healthcare, and with recent technological advancements, in some instances, we are able to predict whether an individual will develop a certain disease before they even show any symptoms, just by analysing different aspects of their lives. The possibilities for this technology are endless, and whilst for some this is truly exciting, for others, it is a step too close towards a Minority Report, iRobot, 2001: A Space Odyssey type future.
No matter what your philosophical view of our future, increasingly, the focus on AI/Machine Learning in analytics corresponds to the next logical step, which is gaining advanced insights from Big Data.

No matter what your philosophical view of our future, increasingly, the focus on AI/Machine Learning in analytics corresponds to the next logical step, which is gaining advanced insights from Big Data, the ability to accurately predict outcomes, improve productivity, and gain competitive advantage. Whilst it’s taken a few years to build the right infrastructure to store and process massive amounts of data, this was just the first step. Now, AI/Machine Learning is driving us forward and the combination of Big Data and AI will present incredible opportunities and drive innovation across almost all industries.

AI, Machine Learning and more will be discussed at the Chief Analytics Officer Forum, Fall on October 5-7 in New York. Join us on October 5 for our dedicated Pre-Conference Focus day Machine Learning, Deep Learning and AI for Strategic Innovation and hear about the ways in which leading companies are using AI in innovative ways within their companies. For more information, visit www.chiefanalyticsofficerforum.com

By Vicky Matthews:

Vicky Mathews is the Content Director US/Europe for the CAO Forum. Vicky is the organiser of the CAO Forum, Fall consulting with the industry about their key challenges and trying to find exciting and innovative ways to bring people together to address those issues. For enquiries email: vicky.matthews@coriniumintelligence.com
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How to strategically position the CDO organisation for success?

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In the previous article, A case for the CDO, I discussed the approach for determining if your company needs a CDO and if so, what is the best way to address alignment or positioning of the CDO organisation, at a high-level.

Getting the right set-up with a defined purpose and supportive positioning is critical for the success of the CDO and it warrants a detailed organisational design approach, just as any other function would require, to deliver the best intended outcomes.

Organizational Positioning’ refers to where the CDO org fits within the entire organisation. The decision should be based on the following four important considerations.

A. CDO Span of Control and Scope of Activities
B. Business function prominence in business value chain
C. C-level leader profile
D. Outreach effectiveness for success

Where and how the CDO organisation is created in any company should be a result of evaluation of the points above. Sometimes, changes may be needed as situations evolve. But if careful analysis is performed upfront, your CDO initiative would start strong with the early nurturing, and any subsequent changes would be an effect of general business/company evolution.

Even though CDOs are company executives with a ‘C’ in their title, they typically report to one of the first-line C-level executives. And I think that is the way it should be as, except in a few rare cases, the CDO role is not something that can effectively hold itself as a direct report to the CEO.

CDO is an important, game-changing function for the company, however, there is a degree of detail and mid-level influencing and consensus building that needs to happen in the CDO role, which will not be possible if the role is far removed from the layers where the decisions for data and analytics are made. Therefore, an effective CDO should be able to directly influence at least 3 organisational levels, up and down, including their own.

CDO is an important, game-changing function for the company, however, there is a degree of detail and mid-level influencing and consensus building that needs to happen...

A. CDO Span of Control and Scope of Activities

Depending on how the company is organised - a single entity, multiple entities across business lines rolling into a single corporation, a single company with global presence across continents/countries or multiple levels of aggregation creating more complex structures – CDO span of control and scope of activities will differ.

The higher the CDO org is in the company, the farther removed or limited it will be in execution for actual on-the-ground work for data engineering, governance, architecture, data quality and issue remediation.

In such cases, the span of control would be the actual responsibility for rolling out standardised policies, framework and procedures and maybe even support common tools. The scope of activities may be limited and the local CDO organisations would be executing much of the work.

There is no one approach that will work here, and the key is to do an informed analysis on company structure, interactions, degree of influence and autonomy of the corporate vs sub-entities while defining a firm-wide CDO set-up and roll-out.

Remember, the decisions should be based on what will work for effective management of data across the entire firm, including all sub-entities and it is ‘OK’ to differ in your approach between entities with regard to alignment, structure and coverage.

B. Business function prominence in business value chain: Who carries the weight around?

It is very rare that all functions are equally important or equally loaded in any company. I agree that every function is required. But depending on the industry, complexity, market and nature of the business, some functions within the company are more critical in the value chain than the others. We will call this as driving-function. As such, the leverage they can achieve through effective data and analytics initiatives will be better than if the CDO was aligned somewhere else.

For example, in financial & banking sector, the primary driving functions are Risk Management, Finance, Marketing (Customer 360) and Technology. Data is at the core of everything that fuels the activities and output for these areas. Clean, reliable, timely and relevant data is non-negotiable, as well as high-standards related to the management of this data with adequate controls and governance. As a result, we usually find that the CDOs typically report to CRO, CFO, CMO or CIO.

Whereas in manufacturing, higher education, software, insurance or pharmaceutical sectors, it may make good business sense to evaluate alignment of the CDO function into C’s of alternate verticals (in addition to finance or technology) such as Plant Management, Academic Affairs, Product, Strategy & Innovation, Engineering, R&D, Actuary etc.

CDO is an evolving field and, based on the experience I have across 4 of the 6 sectors mentioned above, there are always more than one possible driving function in each of these sectors. The final decision on where the CDO should be positioned will be based on the company’s unique story along with the talent and capabilities available across the C-level, to support the function.

Note: CDO is a Business – Technology role and while the position/org stays within Business or Technology, the organisation must be staffed with people who can effectively bridge across the two sides. Also, if aligned under technology, the CDO should be a direct report to the CIO, as any other alignment would dilute the effectiveness of the organization or make it more of a technology-only initiative, that it isn’t.

C. C-level leader profile

In the previous article, A case for the CDO, I mentioned that the easiest and quickest way to ensure that the CDO initiative runs into the ground, is to align it with a C-level leader who does not understand the function (even at a high level), not value it, cannot see the strategic benefits of it or have conflicting interests.

These may be extreme words, but the intention is to ensure that the reader understands the criticality in avoiding the mistake of incorrect alignment when it comes to evaluating a C-level leader to whom the CDO will report to. This is as important as choosing the right candidate for being the CDO.

As I discussed in point B of this article – Business function prominence – there may be several candidate functions that are equally dependent on data being managed as an asset, and wanting to drive the CDO. However, not all leaders of those functions are inherently qualified to own the CDO. So what qualities do you look for and what should you avoid?

What to Embrace:

  • Strategic thinker/true leader who fundamentally believes in the value of well-managed data and analytics.
  • Visionary leader who can clearly provide support to CDO, to help garner visibility and acceptance of the CDO function, by effectively helping sell its value among their peers and with the CEO/Board.
  • Leads by example, by willingly standing strong to correct the people, process, technology and control issues within their own function, by working with the CDO, before taking it to the rest of the company.
  • A well-rounded executive who understands the inner workings of the company, broader challenges and opportunities, the various business functions and their inter-relationships.
What to Avoid:

  • Weak leaders. Not everything is black & white and can be represented in numbers only. Most challenges faced by the CDO function are qualitative in nature, such as issues related to cultural/political aspects, job insecurities, conflicting priorities, resource contention and just the change involved in pushing something new that is company-wide. The C-level leader needs to be someone who has the humility, fortitude and capacity to understand the full picture when it is conveyed to them, and support the CDO in all ways to remove obstacles. 
  • Selfish leaders. CDO is a function that must operate across the company. As a result, whether it is under CIO, CFO or CRO, the function should operate across organisational boundaries. That implies the C-level leader is expected to think beyond their independent functions and always willing to have difficult conversations, if needed, to understand different perspectives.
  • Unpopular leaders. Even at the top, there are a few leaders who are not very popular among their peers. If the function is lined up under such a leader, it will be extremely difficult for the CDO and the team to execute on the strategy as the cooperation from other areas can be expected to be sub-par.
  • A leader with a different agenda. Though rare, this could be an issue, not just for CDO, but for any function under such a leader. Sometimes a C-level has a completely different agenda, either to better their own situation or brought in for a different purpose by the management. Whatever be the reason, it is difficult to establish a new function from the ground up under such a person, who in most cases can be attributed to a “bull in a china shop”. It is best to avoid positioning the CDO function under such a leadership as it will be a long time before any benefits are seen from the initiative.

D. Outreach effectiveness for success.

If there is more than one area/leader that would be a good fit for the CDO organisation after evaluating the CDO positioning based on all the three points covered above, then that is a good problem. However, one function/leader combination would have a better outreach effectiveness and execution capabilities than the others would. Make that choice and there will be no regrets.

Disclaimer: All thoughts, ideas and opinions expressed in my articles are my own and do not reflect the views of my current / past employers or clients. No references or details will be provided in these articles that would expose any trade secrets or inner operations of any company whatsoever.

Other articles in this series:

0. The CDO Journey: A practitioner’s perspective      
1. A case for the CDO 

Prakash Bhaskaran is a Business-Technology leader with a passion for solving complex business problems and challenges, using a combination of business process, technology, data, analytics and organizational transformation. Through his varied experience across manufacturing / supply chain, higher education, software development, banking and financial sectors, he helps companies excel at managing data as an asset. Contact Prakash on LinkedIn; Twitter; Email
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What every Chief Customer Officer should be worried about

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It starts with “s” and ends with “s” and, at one time or another, sends shivers up every Chief Customer Officer’s spine. Of course I’m talking about silos – organisational silos, channels silos, product silos, all wreaking havoc on the customer experience.

In their favour, silos promote internal accountability, focus and expertise. But in today’s business world, where customer experience has displaced product and price as the key competitive differentiator, companies need to re-evaluate the raison d’ĂȘtre of an inward-looking siloed approach.

Just think of the times the contact centre is not informed of a campaign by marketing; or the credit card company calls a business owner about a business card without knowing they’re speaking to one of their most loyal Platinum card members. There are a million scenarios of disjointed, dissatisfying service experiences because the left hand doesn’t know what the right hand’s doing.

While silos are difficult to break down completely, it’s still the Chief Customer Officer’s (CCO) role to build and communicate an overarching set of customer outcomes across the organisation. Secondly, the CCO is tasked with building a culture of collaboration to achieve the desired customer outcomes.  This will almost certainly involve cultural change management, new team-based KPIs and reward programs, and cross-functional working groups.

Office politics and individual egos are perhaps the biggest barrier to implementation. It’s imperative that the CCO have the necessary power and authority to overcome these, in order to successfully instigate reform.
Office politics and individual egos are perhaps the biggest barrier to implementation. It’s imperative that the CCO have the necessary power and authority to overcome these, in order to successfully instigate reform.

Given the employee sensitivities which invariably arise from “silo shake-ups”, it’s important to show fairness and transparency. Employees are themselves all customers at the end of the day, and if shown in a logical way (without finger-pointing) how their actions or processes are causing customers to be unhappy, they are more likely to co-operate with proposed changes. Whether it’s through dynamic dashboards on every employee’s desktop or wallboards on every floor of the office, employees should be able to track results of the CCO’s efforts to make the customer experience easier and happier.

Be part of the premiere event for Customer Experience Executives - Chief Customer Officer Forum, Sydney happening on 28-29 November 2016. For more information, visit www.chiefcustomerofficersydney.com   

By Sharon Melamed:  

Sharon Melamed is a digital entrepreneur with 25 years’ experience in contact centres and customer experience.  In 2012, she launched Matchboard, a free website where companies can enter their needs and find “right-fit” vendors of solutions across the customer lifecycle. In 2014, she launched FindaConsultant, an online portal of business consultants.  She holds a double honours degree and University Medal from the University of Sydney, and speaks five languages. Contact Sharon on LinkedIn; Twitter; Email 
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The 80/20 Rule of an Effective Chief Analytics Officer

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We all know the problem – data is exploding, the number of analysts is decreasing and expectations on big data and analytics are ever increasing. In such a scenario, how can one best manage this situation? To become an effective Chief Analytics Officer, is there a ‘rule’ to follow?

To shed light on these issues, we spoke to Cameron J. Davies, SVP, Corporate Management Sciences at NBC Universal. Cameron is responsible for both the corporate management sciences and NBCU news group insights teams, including the development and execution of advanced analytics, data and research strategies driving NBCU priorities such as leveraging big data, personalisation of content, monetisation strategies, alternative measurements, and customer insights.

How has your role evolved over the past 12-18 months? 

CD: Most of these roles tend to follow similar paths when a company like NBCU is just getting started in this arena.  Consequently, my last 12-18 months have been in those initial stages.  The first 6 months were largely about building relationships, listening and getting integrated into the business.  It really doesn’t matter how experienced you are either at “analytics” or the industry, your first step should always be about listening to the business, understanding their struggles, challenges, and opportunities.  You can pick up some quick wins along the way but it is largely just learning.  Months 6-12 are about establishing a strategic vision for how you want to prioritise and drive value.  We called it setting a “North Star” of where we would like to see the organisation in 5 years.  We know the path with evolve and shift, but it is important to set it and then make decisions incrementally as you evolve with the business.  You also spend a lot of time in months 6-18 just doing the heavy infrastructure lifting of establishing your Data Strategy (finding it, storing it, curating it, then syndicating it), most of the first stage value comes from driving efficiency and effectiveness through these processes.  The next 18-36 months is where the job gets really fun and exciting, because with the foundations in place we can begin to really deliver value added integrated tools and processes that help the company make better decisions more often.

What advice would you give someone wanting to become a Chief Analytics Officer, and what are the core skills one needs to have to thrive in the role?

CD: The role is only 20% data and math and 80% human behaviour and organisational change. There are a lot of very smart technically and mathematically talented people who fail at these roles because they don’t understand that. Data and analytical skill sets are really just the table stakes anymore. The people that will excel at these roles in the future (especially where the real growth will be outside of the digital natives) are going to be those that can influence an organisation. I would strongly advise anyone thinking of attempting one of these roles to spend as much time reading, studying their Organisational Behaviour and Psychology “textbooks” as they do trying to dig through the math of the latest machine learning algorithm.

Data is exploding, the number of analysts is flattening and expectations and demand are growing – how does one best manage in this scenario? Should the focus be on processes or business problems?

CD: Yes, There is no “OR”, that is like asking whether I should focus on breathing or pumping blood. If you stop doing either, you die.  Business processes are by nature evolved to deal with a business problem.  Any advanced analytics “tool” you want to roll out or put in place has to absolutely be designed to enhance a specific set of decisions the business makes on an ongoing bases AND do so in a way that can be acted upon appropriately (i.e., fit with the business processes).  For example, a LOT of vendors want to sell media companies “real-time tools”.  The idea of being able to see who is tuning in or out of my program in “real-time” sounds exciting BUT… by the time I put a procedural drama on the air (fully produced), there are very few decisions I can make “in the moment” that will impact the content or airing of that show.  Consequently, what value does that information generate for me in that moment?

The idea of being able to see who is tuning in or out of my program in “real-time” sounds exciting BUT…what value does that information generate for me in that moment?

What is the biggest challenge you face within your role today and how are you looking to tackle it?

CD: We are no different than 99% of the folks out there trying to do this.  Our #1 challenge is non-existent, incomplete, or bad data and/or the inability to quickly process all of the data we have stored (new tools like Hive and Spark are helping with this but still an issue).  We are tackling it via an integrated Data Strategy that aligns with our overall Advanced Analytics strategy.  It starts with a consistent and persistent Master Data and Metadata strategy and moves through to Curation and Syndication in ways that create “single” consistent sources for other use cases like enhanced automated reporting, forecasting, etc.

What is the biggest challenge faced by the analytics/big data industry currently and in what ways does this affect your business?

CD: Too many vendors and too few qualified candidates, especially highly qualified data architects.  In particular, those people that are able and willing to dig down into the bowels of the data to create useful repositories.  Everyone wants to be the “rock star” who does cool math but that can only happen if all of the hard work of data procurement and curation has been done.  Consequently, people want to throw that work back to a vendor who really doesn't understand your data or business and/or a traditional BI group within IT, who by habit and nature tend to think in rows, columns and traditional EDW structures.  There are a lot of start-ups out there right now trying to tackle this particular problem but it is sort of like the promise of a magic diet pill.  Maybe it will exist one day and work well without all of the nasty side effects but for now, it just takes hard work and you have to be willing to roll up your sleeves and get it done.  It isn’t sexy and it isn’t fun but the results can be amazing if you have the tenacity and fortitude to stick with it and get it done right.

Where do you see will be the biggest area of investment in analytics within your industry over the next 12 months?

CD: Distributed computing.  Distributed storage made it possible to gather in and keep all of this “data” but in some ways we are still drinking from the proverbial data “ocean” with a very thin straw.  It is getting better and better and I think this is where you will see the biggest gains over the next year or so.

Hear more from Cameron J. Davies and other leading CAOs at the coming Chief Analytics Officer Forum Fall happening on 5-7 October 2016 in New York. For more information, visit www.chiefanalyticsofficerforum.com   
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The Growing Generational Gap in the CDO Community

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If you Google 'chief data officer', you'll come across a large number of links to articles, white papers etc. entitled "The Emergence of the CDO" or something along those lines.

How long is the CDO going to be emerging for? There are many Chief Data Officers/Offices that have been in situ for a number of years - who've fully emerged.

At Corinium, we pride ourselves on the work we've done supporting the emerging C-suites in the data & analytics community. Just over 3 years ago, when the CDO and CAO titles were mostly new, the networks we created were invaluable to those just getting to grips with the role.

But now, many of those new CDOs are not-so-new CDOs anymore. Their roles, challenges and objectives have evolved. And yet, new CDOs come into existence all the time as companies realise the importance of their data and the need to have someone take leadership of it.

Before I get into this further, I want to clarify that by CDO, I refer not only to the actual Chief Data Officer but also to the Chief Data Office. In some instances, the Chief Data Officer in a company may have been a CDO for 2-3 years yet the company they currently work for has just entered the world of CDO. The generational gap applies to people and companies.

First Generation CDOs

I define a First Generation CDO as someone who has recently taken on their first CDO role and/or a company that has recently employed their first CDO. Person and company have the same challenges at this point.

Our research indicates that First Generation CDOs are typically responsible for the following:

  • Assessing the state of the company's data which, more often than not, is in some state of disrepair
  • Developing a data warehouse that acts as a central repository for all of the company's data
  • Defining the data governance, management and ownership frameworks that will ensure data quality is created and maintained
  • Working with business to understand data requirements and then how to provide them with this data - whilst maintaining control (see point above)
  • Assisting in developing reporting tools through BI, visualisation tools, etc.
  • Ensuring compliance to data or sector-specific regulations - this is mostly true in the financial services sector where most companies employ a CDO to make sure that they're compliant to regulations

In addition to these key responsibilities, the First Generation CDO is concerned with communicating his/her value to the organisation, evangelising the importance of data and building business processes to ensure efficient workflows.

These are all the critical, foundation-building baby steps that need to be taken before moving into the next phase or generation of CDO-ship. The CDO is producing step-changes within the organisation's data architecture and usage. Change is big but perhaps does not deliver significant business value.

Second Generation CDOs

Our research has uncovered that, in the second phase, there is almost a shift away from being a CDO toward being a Chief Analytics Officer. The ultimate end goal for data in an organisation is to have the ability to use it to make good decisions in real time.

It's based on this that I assess the Second Generation CDO as being increasingly responsible for, and involved with, advanced business analytics. The first phase was all about getting data in shape for it to be utilised accurately across the business.

It's at this point where the CDO is involved in the optimisation and transformation of the business.
Our research has uncovered that, in the second phase, there is almost a shift away from being a CDO toward being a Chief Analytics Officer. The ultimate end goal for data in an organisation is to have the ability to use it to make good decisions in real time.

Innovation through data!

The Second Generation CDO becomes an integral part of eking out the hard-fought percentages of business improvement and profitability. Innovation across the organisation has come to rely on data. Product innovation takes a look at how the product is performing, who buys it, how it is manufactured etc. to evolve it and keep its competitive edge. None of this could be done with access to good quality data in real time - or at least in a short space of time.

I've spoken to a number of CDOs who are at the forefront of their company's digital transformation since data (and analytics) plays such a critical role in digitising a business. It's perhaps for this reason that a number of Chief Data Officers have moved in Chief Digital Officer roles.

What does the Future Look Like?

It's not easy to predict what the next generation will look like and how they'll act. I don't think Facebook anticipated that the current youngest generation would not be big users of the service.

I am intrigued by the development of the CDO - and for that matter the CAO and the Chief Digital Officer. Could they all blend into one? Or will they be obsolete in a few years and replaced with a new emerging C-suite?

For now, we'll keep focused on understanding the different needs of the First Generation and the Second Generation of CDOs to ensure we can provide relevant information and networks. It is likely that the next generation will only emerge in 4-5 years time.

By Craig Steward: 

Craig Steward is the Managing Director for Corinium’s EMEA business. His research is uncovering the challenges and opportunities that exist for CDOs and CAOs and the Forums will bring the market together to map the way forward for these important roles. For more information contact Craig on craig.steward@coriniumintelligence.com
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JUST RELEASED: Chief Data and Analytics Officer Forum Singapore - Speaker Presentations

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The Chief Data & Analytics Officer Forum Singapore gathered the region’s leading data and analytics executives to share their insights on developing the infrastructure, ecosystem and buy-in culture whilst providing the strategies to turn data into a strategic asset. 2016 was a fantastic event with engaging presentations, topical discussions and invaluable networking opportunities. The two-day event covered many topics and issues: from the development of data analytics capability, culture, communications and leadership skills and strategies, to deployment of advanced analytics.

Hear more from the leading Chief Data and Analytics Officers at the coming conferences organised by Corinium. For more information, click here. 

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The CDO Journey - Building a case for the Chief Data Office(r)

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(This article is addressed to C-suite executives and business leaders looking to build a CDO organisation within their company.)

If you don’t know where you are going, any road will get you there.
- Lewis Caroll in “Alice in Wonderland”

If you are someone who has been following the evolution of strategies, new technologies, architectural innovation, best practices, success stories and a host of vendor-driven publicity in the data and analytics space, it is very easy to be influenced and assume that this is the direction you want your company to grow into. You may even want to initiate some of these cool projects and proceed with the creation of a CDO role in your organisation.

There is nothing wrong in wanting to embrace the advancements in the data space to position the business for growth, but that decision cannot be based on someone else’s story. Before you or your company start down the path of setting up the CDO, you need to understand what your unique story is. A unique story that is crafted from a combination of problems and opportunities. That is, your case should reflect the collective scenarios of the need to solve existing problems, as well as a larger desire to embrace and grow from opportunities in the marketplace. What usually succeeds in crafting this story is a blend of factual and creative exercises to identify ‘Musts’, ‘Shoulds’ and ‘Nice-to-haves’.

Thinking through the following questions can help with articulating your story better when it comes to making a formal business case.

Is the volume, variety and velocity of data & analytics needs complex and critical enough to justify a CDO? Based on your specific needs, all that is required could be a few tweaks to the existing processes when you may already have a mature organisation supporting it. For example, some companies have a small data footprint when it comes to variety, a very deep requirement in volume and they manage a specific set of functions where complexity is low to medium. Do these companies need a CDO? Maybe. Maybe not. It totally depends on the specific situation and what the intended expectations are.

Beyond solving immediate problems, what are the long-term expectations on data and analytics? Independent of your immediate drivers, there are extended benefits that can be realised through the CDO. If the immediate needs are driven by regulatory/compliance mandates, what are the opportunities that exist for extending the purpose of this function beyond these needs to ensure achieving overall business growth?  In fact, regulatory mandates and regulators are CDO’s best friends, as the primary expectations and principles from these agencies are fully aligned with how data and analytics functions should be rightfully managed – with level of controls, ease of change, comprehensiveness of coverage and adequate management oversight. Make this as a standard yardstick for managing data across the company and you will automatically achieve success with managing the entire business through actionable insights based on reliable data and analytics, not to mention the heightened level of efficiencies created in the process.

Can you or your company support a function that operates across organisational boundaries? Where the function lines up is irrelevant as the application of the processes, procedures, and tool sets are company-wide. Typically, CDOs are aligned within Risk, Finance or Technology, and in some cases, under Marketing or Strategic initiatives area. There is a cultural component involved here that needs to be addressed in almost all CDO initiatives. For a CDO function to be effective, the reach need to be across organisational boundaries. When it is truly addressed this way, it is easy to extend the applicability to realise extended benefits that cannot be perceived initially.

How are you going to support the organisation and its leader to succeed? Who will this function report into? The easiest and quickest way to ensure that the CDO initiative fails is to align it with a C-level leader who does not understand the function (even at a high level), not value it, cannot see the strategic benefits to the organisation or have conflicting interests that the person would rather see it fail than succeed. In the previous point, I discussed that it does not matter where the function aligns, but it is critical that it is aligned within an area where the greatest support can be provided. Also critical is ensuring that adequate support is provided on items related to funding, resources, independent authority, strategic evolution and reporting.

The easiest and quickest way to ensure that the CDO initiative fails is to align it with a C-level leader who does not understand the function (even at a high level), not value it, cannot see the strategic benefits to the organisation...

Once the question “Does your company really need a CDO?” has been answered based on the above-mentioned points, the next step is to sell the case for the CDO, and for this, the full range of benefits need to be established. This will be covered in greater detail in future articles. However, some of the most obvious are listed below.

  • Establishing comprehensive data governance through Business glossary, data lineage, business/technical metadata, and data certification.
  • Handling Data privacy, data classification, access control and entire range of information lifecycle management.
  • Robust and reliable data quality through a structured process of data quality rules definition, assessment, monitoring and reporting.
  • Data Issue identification, inventory, research and remediation activities that may start with data but if properly implemented, can be extended to cover critical aspects of managing the business – across policies, procedures, alerts, broken/missing controls, process gaps & improvements and efficiency creation.
  • Manage data as an asset – address platforms, sourcing, processing and consumption with the company and across vendor relationships as applicable, as well as increased coverage from inclusion of new sources – internal, external and social-media.
  • Promotion of Analytics internally, enhancing customer engagement and experience, behavior predictive modeling for risk mitigation & upsell opportunities and operationalising analytics through front-line systems (digital, including cross-channel evolution, mobile, robotic automation for processes, and enhanced data exchange possibilities across entities).
  • R&D, new product development, market expansion, M&A or new industry diversification.

I have included a lot of benefits and an initial response could be to even challenge these benefits since it covers a wide footprint. Establishing a CDO is an opportunity to really embrace management of data as an asset. It is as important as people asset or financial asset for company’s survival and growth. Unfortunately, not many companies and leaders have embraced this notion yet. The first three or four benefits are the obvious benefits. But if data is well-managed as a business-critical function, there should be no doubt why the extended benefits cannot be realised.

Get creative and reap the boundless benefits. Isn’t it time you start your Chief Data Office?

Prakash Bhaskaran is a Business-Technology leader with a passion for solving complex business problems and challenges, using a combination of business process, technology, data, analytics and organisational transformation. Through his varied experience across manufacturing / supply chain, higher education, software development, banking and financial sectors, he helps companies excel at managing data as an asset.
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Dealing with Data - What are the Rules?

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The promise of an ever-evolving big data landscape and the depths to which analytics can provide companies with new insights, or even new products, means this is an exciting time to be involved in data research.

At the same time, however, we're charting new territory that crosses multiple boundaries, including ethical and privacy concerns. This is especially true, of course, with data that contains personally identifiable information (PII) as this risks exposing individuals to everything from tracking through to fraud if the data should get into the wrong hands. Even here, the definition of compromised data is not always clear cut - hacking and breaches make the news, but intentional or accidental abuse by employees with access to data is also an issue. So on the one hand, data can be invaluable especially when it comes to gaining big picture insights in sectors including governance, health, retail, and finance - but on the other, this must be balanced with the need to protect individual privacy where PII is involved.

Hacking and breaches make the news, but intentional or accidental abuse by employees with access to data is also an issue. 

The logical solution = anonymising data

Separating PII from other non-identifiable data by removing, supressing, or encrypting it. But there are also other options: irreversible aggregation, k-anonymity and importantly, the emerging field of differential privacy.

By its nature, manipulating data to obscure personally identifiable information comes at the cost of accuracy. However, done right, it's possible to make it very hard or (and I use this phrase lightly) nigh impossible to reconstruct personal information while returning valuable information to produce insights. It's important to remember, however, that just because a dataset anonymises PII that it doesn't necessarily mean an individual’s privacy is protected -- two separate anonymised datasets can be combined to glean correlating information and make it possible to still reveal PII. And considering the regularity at which data breaches happen, this also must be considered with respect to data that's already out there (e.g., breached census data paired with already available credit card details to build a personal profile for identity theft).

Concerns around the sharing of data

Inevitably, organisations and institutions can leverage greater use of data by sharing. However even if data is anonymised, responsibility for that data cannot be transferred. If an abuse happens in the hands of another organisation, this shouldn't absolve responsibility for the organisation owning the data.

As a result, as we move to a future where we are leveraging big data more than ever before, it’s vital that all stakeholders who interact with that data have critical investments in cybersecurity. This isn't just good business sense in terms of protecting assets, but also vital to build trust with customers and the public. Otherwise, the value of that data may be compromised if individuals don't trust an organisation to keep their details safe, and so either abstain from providing data, or provide incorrect data.

As we move to a future where we are leveraging big data more than ever before, it’s vital that all stakeholders who interact with that data have critical investments in cybersecurity.

This is only scratching the surface of the considerations involved with the collating, keeping, and management of data, but the potential it provides will see big data and analytics continue to grow rapidly as a sector - it just needs to be remembered that with great value comes great responsibility.

By Ashton Mills:

Ashton Mills is the Outreach Manager - Technology & Innovation at Australian Computer Society – www.acs.org.au
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