El vibrante mercado de Big Data en Latinoamérica.

| |
0 comments

Las predicciones sobre el crecimiento del mercado de análisis de datos y Big Data han sido bastante positivas en los últimos años para Latinoamérica. Gartner, Frost & Sullivan y muchos otros líderes en el tema, han estimado un crecimiento cercano al 40% en la adquisición de soluciones e implementación de herramientas para análisis de datos avanzado en los siguientes 4 años.

Ciertamente, los sectores Financieros y Aseguradores se encuentran liderando este fenómeno, bien sea por la necesidad de cumplir con agencias regulatorias en relación al uso y manejo de información o por una iniciativa clara de monetizar sus activos de datos. No obstante, otros sectores locales ya se encuentran en un proceso muy adelantado de modernización e implementación de estrategias corporativas para explotar sus datos.

Por ejemplo, industrias como Marketing, Telecomunicaciones, Retail y Producción de Bienes de Consumo están mostrando un mayor interés en las posibilidades que el análisis avanzado y Big Data les ofrece en términos económicos a mediano y largo plazo. Esta tendencia puede verse directamente reflejada, por una parte, en la aparición de un nuevo rol dentro de las estructuras directivas de dichas compañías – Chief Data Officer o Chief Analytics Officer-, y por otra, en, la implementación de procesos de modernización tecnológica para mejorar la captura y análisis de datos en tiempo real.

Por ejemplo, industrias como Marketing, Telecomunicaciones, Retail y Producción de Bienes de Consumo están mostrando un mayor interés en las posibilidades que el análisis avanzado y Big Data les ofrece en términos económicos a mediano y largo plazo.

A pesar de lo importante de estas iniciativas, y luego de más de 50 conversaciones directas con altos ejecutivos en la región, es evidente que aún hay un buen camino por recorrer antes de poder ver realmente los beneficios comerciales de cualquiera de estos sectores. Las razones principales para ello oscilan entre (1) la implementación de proyectos de modernización tecnológica en sus etapas iniciales; (2) la consolidación de programas de desarrollo profesional privados y públicos; y (3) la divergencia entre las necesidades locales y las soluciones disponibles en el mercado.

Interesantemente, las dos primeras aspectos han sido rápidamente reconocidos y varios agentes públicos y privados han sumando esfuerzos para poder acelerar sus resultados. Proyectos de modernización de infraestructura tecnológica y capacitación ya están en un estado muy avanzado de desarrollo. Mientras que el tercero, aún está lejos de lo que podría llegar a ser. Es claro que el mercado de soluciones local e internacional todavía se está ajustando al cambio organizacional y que se ven sorprendidos al ver el gran conocimiento que los nuevos CDOs y CAOs tiene sobre Big Data y análisis de datos.

Al parecer, son pocas las compañías que reconocen que éstos líderes regionales son los agentes adecuados y directos con los que pueden establecer posibles alianzas comerciales. De igual forma, son pocos los que se han tomado el tiempo de entender cuáles son sus reales necesidades, cuáles podrían ser las mejores formas de colaboración conjunta y cuál podría ser el camino más corto y económico para implementar programas duraderos de explotación de datos.

Por esta razón, Corinium Global Intelligence ha abierto la primera puerta de discusión directa en la región, para permitir que ambas partes tengan la oportunidad de reunirse y discutir sobre las mejor soluciona para solventar esta discrepancia. Del 24 y 25 de Enero de 2017 se llevará acabo el primer Chief Data & Analytics Officer, Central America, en el Marquis Reforma en la Ciudad de México, que reunirá más de 100 especialistas en la materia para discutir los aspectos operativos y estratégicos en la implementación de programas alrededor de la explotación comercial de datos. Esperamos ver a todos los expertos en regionales el siguiente año en México!

By Alejandro Becerra:

Alejandro Becerra is the Content Director for LATAM/USA for the CDAO and CCO Forum. Alejandro is an experienced Social Scientist who enjoys exploring and debating with senior executives about the opportunities and key challenges for enterprise data leadership, to create interactive discussion-led platforms to bring people together to address those issues and more. For enquiries email: alejandro.becerra@coriniumintelligence.com
Read More

Will machines help humans make big decisions in future? Chief Analytics Officers weigh in

| |
0 comments

In a report recently released by PwC entitled PwC’s Data and Analytics Survey 2016: Big Decisions TM, it was revealed that “we’re at an inflection point where artificial intelligence can help business make better and faster decisions.”  The said report “shows that most executives say their next big decision will rely mostly on human judgment, minds more than machines. However, with the emergence of artificial intelligence, we see a great opportunity for executives to supplement their human judgment with data-driven insights to fundamentally change the way they make decisions.”

In our discussions with notable thought leaders in this space for the upcoming Chief Analytics Officer Forum Fall on 5-7 October in New York, we got a deeper insight as to how this trend is felt and viewed on the ground. For example, John France, Head of Sales Operations & Analytics at VALEANT PHARMACEUTICALS sees that the opportunities are limitless. He said that, “if there was a machine that could scan you at home and provide an instant reading on your health (heart, blood pressure, cholesterol, diet, etc…) and then deliver an action plan to correct such as what to eat that day, a work out regime, what meds to take, etc… that could really help save lives”

On the other hand, John Lodmell, VP, Credit & Data Analytics, ADVANCE AMERICA  believes that the increasing collection of geographic information from cell phones or fitness trackers will open up a lot of big data opportunities around movement and traffic patterns. “If you think back to vehicle traffic studies putting “car counters” across the road to track every-time a car crossed a certain point, we now have much richer data and collection techniques that are not fixed to tracking crossing a single point, but overall movement.  I remember hearing years ago that a large retail store was tracking traffic patterns within the stores seeing where customers went.  It provided them tons of useful information around where to place promotional items and how to make things more convenient for customers to find.  I can only imagine that type of information being used for urban planning or store marketing,” he said.

Read our full interviews by clicking on the links below:

Andrea L. Cardozo - Pandora 
Ash Dhupar - PCH 
Cameron J. Davies - NBC Universal 
Christina Hoy - WSIB 
Dipti Patel-Misra - CEP America 
Eric Daly - Sony Pictures 
Inkyu Son - Nexlend 
Jason Cooper - Horizon 
John France -  Valeant 
John Lodmell - Advance America 
Nikhil Aggarwal - Standard Chartered     


To learn more about Chief Analytics Officer Forum Fall, visit www.chiefanalyticsofficerforum.com 
Read More

Driving the CX Agenda: Who’s Behind the Wheel?

| |
0 comments

“Have a very good reason for everything you do” – Laurence Olivier

How does your customer experience look under the glare of your customers' expectations? Olivier’s sentiment cries out for justification, to put the thought process behind every business decision impacting the customer up in neon lights for reflection. What would be revealed?

According to PwC’s 2016 Global CEO Survey ‘Customers remain the top priority, with 90% of CEOs indicating they have a high or very high impact on their business strategy’. But how is that translating into existing CX strategy? The Survey states that ‘customer behaviour, in particular, has become more complicated as values and buying preferences evolve.’

Undoubtedly this rapidly evolving environment makes customer centricity a cornerstone, but who has stepped out from the shadows to ensure it stays firmly in the spotlight?

Customer advocates, Chief Customer Officers, are active the boardroom championing the cause of the customer and putting in place the strategy to promote change, inter-discipline collaboration, organisational alignment and customer-centric decision making. 

NAB announced in July 2016 that they are creating not one but three Chief Customer Officer roles.

However the role of a customer advocate will look very different across organisations and backgrounds vary significantly between individuals. When we take a closer look at how Chief Customer Officers have arrived at their destination, we get a better flavour of the complex nature and diverse remit of the CCO role.

For example Julie Batch was appointed as the Chief Analytics Officer at Insurance Australia Group (IAG) in July 2014. By December 2015, Ms. Batch was heading up IAG’s Customer Labs as Chief Customer Officer, responsible for developing customer propositions and marketing strategies. For IAG, customer experience strategy is intrinsically linked to driving product innovation through data and insights. A natural progression for a CAO.

For Carsales.com.au their Chief Customer Officer, Vladka Kazda, was Chief Marketing Officer at the company for over five years before arriving at the CCO position. Ms Kazda owned and influenced customer experience at every level during her journey to CCO so a logical move.

For others, a natural rise in the ranks via customer experience roles has seen them awarded the CCO role. Damian Hearne, Chief Customer Officer at Auswide Bank has excelled in the leadership qualities required of a CCO to unite across  silos and move the business from delivering an uncoordinated experience to a reliable, deliberate and preferred customer experience. 

Mark Reinke, Chief Customer Experience Officer, Suncorp, has also united the critical elements of customer, data and marketing. The customer listening path is critical but alone, it cannot deliver. It needs the proactive and innovative advocate with the leadership skills to drive initiatives. 

CCOs often have a broad remit but primarily the requirement to develop the competency to operationalise the brand promise. Looking at the language, prioritisation, decision-making, bringing together operating groups, transforming the collaboration process, implementing the customer experience design. There is both faith and science behind the Chief Customer Officer.

Ultimately everyone in the business is involved in putting the customer first, but employee customer advocates are only fostered from a successful customer centric culture. What metrics are being used to measure the impact and success of a CCO?

To learn more about driving change, overcoming the challenges and critically measuring the success of the CCO, join Julie Batch, Vladka Kazda, Damian Hearne, and Mark Reinke as they share their insights at Chief Customer Officer Sydney, 28-29 November 2016

Learn how other organisations are addressing their CX challenges, learn about new approaches and strategies, whilst making new connections with industry peers. Join The Chief Customer Officer Forum LinkedIn group here.
Read More

Top 10 Takeaways at the Chief Data & Analytics Officer Melbourne 2016

| |
0 comments

Feeling empowered and inspired after a fantastic three-day conference in Melbourne last week with over 200 data enthusiasts! The topics were vast and the speakers kept everyone engaged with their wealth of knowledge and stories shared. A massive thank you to all our speakers, sponsors and attendees – we learnt lots and had a lot of fun!

Here are my top 10 takeaways from the conference:



1. On leveraging open data for social good: we can all be superheroes! Thank you Jeanne Holm, City of Los Angeles for your inspiring stories of open data being used to improve the world we live in.


2. On building a culture for data governance: “Work with the willing and win hearts” Kate Carruthers, Chief Data Officer, University of New South Wales

3. On establishing a data quality framework: create a team brand that represents value add to your organisation, and keep your dq metrics simple and powerful - Michelle Pinheiro, IAG



4. On ensuring the success of your data analytics projects: agile, agile, agile, AGILE!

5. On IT and business alignment– it’s simple, says World Vision International's John Petropoulos, if your partner doesn’t get it, you need to re-write it!
   
6. Big data personalisation = world class, machine learning predictive model @Woolworths
   
7. On data privacy – and where is that creepy line? A key point for consideration from Brett Woolley, NAB is content vs intent of personal information used.
   
8. On developing a cost model for data governance… you really ought to check out Gideon Stephanus du Toit’s presentation: http://bit.ly/2cvewwW
   
9. On leveraging machine learning for safer flights into Queenstown – a very cool use case from Mark Sheppard, GE Capital



10. On marketing analytics: “don’t fall for vanity metrics” Geoff Kwitko, Edible Blooms

Thanks again all, and we look forward to catching up in Sydney on 6-8 March 2017!

To discuss the Chief Data & Analytics Officer Sydney 2017 event and speaking/ sponsorship opportunities, please get in touch: monica.mina@coriniumintelligence.com   


By Monica Mina:

Monica Mina is the organiser of the CDAO Melbourne, 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, monica.mina@coriniumintelligence.com.
Read More

17 Quotes on Big Data and Analytics that Will Open Your Eyes to Reality

| |
0 comments

There are times when perception is not a clear representation of reality. Take for example the topic of Big Data and Analytics. The perception is that this ushers in a brave new world where there is actionable intelligence, on-demand data and sexy graphs and charts popping up on our computer screens on the fly. While this could be a reality for some, this is certainly not the case for many – at least, not yet.

In the course of our conversations with noted Chief Data Officers, Chief Analytics Officers and Chief Data Scientists for our conferences and events, some priceless gems of knowledge had been uncovered. Knowledge that can only come from people who’ve actually been on the front lines and understand Big Data and Analytics, warts and all. Here are 17 quotes that will inspire you in your own journey and open your eyes to reality.

1. The reality that ‘real-time’ is not necessarily good all the time.


2. The reality that data governance is an absolute must.


3. The reality that personalization is the name of the game.


4. The reality that CDOs/CAOs/CDSs need to be leaders more than anything.


5. The reality that acceptance to data-driven decision making takes consistent effort.


6. The reality that a CEO buy-in is absolutely important.


7. The reality that the success of Big Data relies heavily on people.


8. The reality that change can only happen when you change yourself.


9. The reality that data and analytics cannot succeed if it’s used as a tool for punishment.


10. The reality that data analytics is not an option. It’s a must.


11. The reality that cool is in.


12. The reality that data breach comes from all angles.


13. The reality that quick wins must happen for long term gain to be sustained.


14. The reality that ‘data ownership’ is passé in today’s environment.


15. The reality that privacy must be ensured at all times.


16. The reality that Big Data will be available to everyone and not just a few select individuals.


17. The reality that expectations today are greater than ever before.


To learn more about Big Data, Analytics and Digital Innovation or to attend our upcoming conferences and meet the leading Chief Data Officers, Chief Analytics Officers and Chief Data Scientists, visit www.coriniumintelligence.com 
Read More

Chief Analytics Officer Survey: 57% say 'culture' a key barrier in advancing data and analytics strategy

| |
0 comments

We have recently conducted a survey of the Chief Analytics Officer Forum attendees to find out some of the key issues facing them and their solutions investment plan in the next 12-24 months. In this survey, it was revealed that 57% of respondents found ‘Driving cultural change’ as the biggest barrier to advancing data and analytics strategy. This was closely followed by ‘Integration of new technology with legacy systems’ (52%) and ‘Getting buy in from business units’ (41%).

The result of this survey actually tallies with key industry findings. In an article entitled ‘4 strategies for driving analytics culture change’ published by CIO.com, it was boldly declared that: “Culture change is hard." It further continues that "the solution lies in a mix of tooling and analysis and information delivery architecture. Often, culture changing strategies can fall flat because they approach the problem from purely a tooling perspective. Vendors offering such tools paint a rosy picture of how the right tool can change the culture and behavior within an organization. However, the problem often is more complex.”

Culture change is hard. The solution lies in a mix of tooling and analysis and information delivery architecture.

Meanwhile, the Chief Analytics Officer Survey also looked at the respondents’ investment plans and a whopping 70% of all respondents (81% of whom are C-Suite Decision Makers) revealed that they plan to invest in Data Analytics solutions in the next 12-24 months, followed by Predictive Analytics solutions (64%) and Business Intelligence tools (62%). It’s also interesting to note that 68% of them choose solutions at Conferences and Events.

More of our findings from the infograph below:


 For more information on how you can join our upcoming events and conferences or if you're interested in sponsorship opportunities, visit www.coriniumintelligence.com   
Read More

Will Artificial Intelligence help Big Data deliver on its promise?

| |
2 comments

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
Read More

How to strategically position the CDO organisation for success?

| |
0 comments

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
Read More
Powered by Blogger.