Data as an Asset Blog
Our outcomes are a result of our beliefs and the actions that we take, based on those beliefs.
Well, before I read Karen Brown’s Unlimiting Your Beliefs, I was not sure what the ‘Ironman’ really was. When I first heard about this mentioned in a conversation many years ago, my ignorance had me wondering what a comic character Ironman, had to do with endurance!
Having met Karen in the USA earlier in 2018, I was keen to read her book.
In Karen the author, I could see a determined as well as a disciplined human being. With that impression which I gained from our first meeting, I recommended Karen’s book to someone I knew, who was struggling with their belief system. Within a few of days I had a message from this person saying that she had overcome a long held fear of getting on to a rollercoaster! My curiosity led me to getting started with the book, without loosing much time. Thanks to David Allen!
As I was reading about the determination, the discipline and the sacrifices, a person has to combine with absolute conviction, it was clear that personal accountability, combined with the right kind of processes and systems, will make even an Ironman (…competition and not the character!), the most grueling physical test on the planet, achievable for every committed human being.
7 Keys to Greater Success – In Your Personal and Professional Life, Told Through My Journey of the Toughest Race in the World, is the text on the book cover, and the following pages are just that. Starting from Key One, which is Tap Into The Dream/Feel The Dream, Ask for Help & Have Faith to the Key Seven, Hit Your Goals, Enjoy the Victory & Set New Goals, Dream Again, this book is an inspiring lesson for any one who wants to commit to “their toughest ironman.”
As someone who is equally determined in my “personal ironman”, I can vouch for this system that works! Regardless of which “personal” or “professional” ironman that you are pursuing this logical and proven system is a must read for anyone who thinks that they have fallen on their bum!
At this point in time, I am actually driving a complex data program in a global furniture giant in Sweden. And I sure am using the lessons from this book.
Regardless of your career, industry or experiences up until today and as Brian Tracy says on this book’s cover, “…achieve any goal you can set for yourself!”
Great job Karen Brown. What an achievement!
25thMay is fast approaching. Facebook, Apple, Google & Microsoft are out in the press educating people, how to access their personal data.
Facebook for example, will begin asking users if their data can be used to power services like facial recognition in a move to help it comply with a massive new European data law coming into effect in just over a month.
You can access your Microsoft privacy data here, for example. Amazon, Twitter and Google are doing the same.
The one thing that is common between all the tech giants is that they have actively started campaigns to educate their users on privacy. All this is picking up pace, a month before the actual date to be compliant. And the only reason for their swift and timely response, is their data management maturity. Their ability to respond to business eco-system demand in a timely manner. Of course, they may not be perfect but their response is commendable.
Obviously, these companies with better data management practises are able to be more valuable than their contemporaries, because they are more flexible and agile in serving the people involved in the business. They actually manage person-centric data well. Oh, well – better than most other companies.
Facebook, in-spite of the Cambridge Analytics scandal, has been addressing the GDPR needs quite swiftly, as compared to traditional companies, such as banks and insurance companies. There is an inherent agility in a technology business model. And companies in traditional industries undergoing digital transformation efforts can take heart in this fact.
More importantly, in a technology business model, a “person” is right in the middle of everything that happens.
Clearly, the tech giants are showing the two extreme ends of what good could come out of managing data, and what bad could unfold with unmanaged data.
All the best to you folks working hard to get GDPR, right!
When Mark Zuckerberg faced the lawmakers from the Senate Judiciary and Commerce committees on Tuesday the 11thof April 2018, Facebook’s business model was questioned. Sen. Dan Sullivan asked Zuckerberg how he classed Facebook. The debate was about how Facebook considered itself. Whether as a technology company or a publishing company.
Just imagine the predicament which the lawmakers will face if all the businesses in our world transform into digital business models. Most businesses in the world today are investing in transforming into digital business models.
Facebook, Google and Amazon are pioneers and they are indeed, shaping our world.
Lawmakers though, just like most boardrooms, probably failed to keep adequate pace in understanding the role of data in our world. Data breaches and current world events are sufficient evidence of this.
It is perhaps time for lawmakers to upgrade their understanding of these digital business models as well as the role of data.
The fact is, that the digital world is not going to get any simpler, if we do not get a grip on understanding the role of data in our world to begin with.
GDPR has probably come to focus recently and has highlighted the importance of “person centric” data in our world. However, most companies and indeed governments are a long way from being comfortable with managing data.
Knowing that data is a reflection of any process is fundamental towards evaluating any risk, be it enterprise or governmental risk. And the good news is that upgrading skills to manage data is the safest and best way for organisations to stay safe, relevant and compliant, in the digital age.
Whether, the law community starts to include data management as a mainstream topic, remains to be seen.
But, there is no doubt that law makers need to evolve themselves into datapreneurs, if we are to see a sane digital world evolve over the coming years.
More information on the datapreneur is available in my book The Billion Dollar Byte.
The world has seen yet another US gun violence incident on the 3rd of April 2018. Only this time, it was in YouTube’s headquarters in San Bruno, California. Clearly, technology titans are not immune to this menace. Of course, only if America accepts that it is in fact, a menace.
Regardless of which side of the debate you stand, data typically tends to paint a true picture. Well, numbers don’t lie, if the process is kept honest.
With this in mind, I captured some key metrics to assess, America’s ability to act on data on matters related to gun violence. I will let you draw your own conclusions, though.
Since, 2014 there have been close to 300,000 incidents, according to Gun Violence Archive (GVA). The GVA is an independent data collection and research group with no affiliation with any advocacy organisation.
Importantly, there have been 74,632 deaths, including the 3 deaths on YouTube campus yesterday. For us as a society, this should be unacceptable, considering that we say that we are in the digital age and we want to get artificial intelligence and robots to run our lives.
On the contrary, we should be aiming high at making our world a safer place. I would certainly want to have a safer planet for my kids and how about aiming for ZERO tolerance towards deaths caused by gun violence, as a goal?
In order to promote positive actions and potentially eliminate death due to gun related violence, the issue must start and end with the involved parties within the process of gun handling. And to this end, current data and people management practises are mature enough to help, if orchestrated correctly, with the right spirit and intention. If at all anything, our spirit and intent in addressing this issue is a suspect, as opposed to our technological capabilities.
Let’s see how the combination of data and people, can facilitate this scenario.
To begin with, let’s articulate a goal to curtail gun related violence. Here’s my attempt of this. (I’m neither a lawmaker nor a political administrator. But, it is certainly a good enough definition as a father to my kids):
Predict, minimise, control and eliminate events (excluding self-defence) leading to injury or death caused by a gun handling actor.
The assumption here is that guns are made available to the public, primarily for the purposes of self-defence.
In order to establish a sound process to track, monitor and control events leading to gun violence, ALL the involved parties need to be identified, tracked and monitored. i.e., an inventory of all the involved actors, authorised to handle guns must be created and maintained. Any exceptions should be well understood, along with the related risks.
Once this is established, various related data sources must be used to enrich the actor’s data. This could include a ‘mandatory’ mental health data at specific intervals. A propensity model could be developed to identify “high risk” and potentially violent actors.
If there is a commitment to address this issue at a national level, data could be sourced from multiple agencies and integrated to get more holistic perspective.
Gun violence or in fact, violence of any nature is an outcome of a mental health condition, which needs to be addressed and treated systematically. Guns just happen to be an easily accessible weapon to the American public.
If America starts to improve its ability to act on data today, it will set policies that will naturally drive down the current average monthly number of incidents of 4,715, by at least 8%, in order to start a reversal of the 2014 monthly average number. And this will just be a start, which needs to be systematically sustained.
When this happens, there is hope of a ZERO death scenario. But, like everything else, it starts with FAITH. Thanks to President Carter’s new book.
We must act now! Let’s first address America’s inability act on data.
In my book, The Billion Dollar Byte, I advise traditional Fortune 500 companies to emulate the data practices of “digital natives”, such as Google, Facebook, Amazon etc. These companies are not saddled by legacy burdens, unlike those companies that have been founded hundreds of years ago. On the contrary they have gained, an undue advantage through their superior use of data.
However, in March 2018 Facebook started to face questions regarding its handling of data, following reports that research firm Cambridge Analytica improperly gained access to the personal data of more than 50 million Facebook users.
This is unfortunate and disappointing. Especially, as Facebook has played a vital role in shaping our “digital age”, as we now know, today. I personally, am a big fan of these pioneering companies. It’s never easy for them. But, they certainly are doing their best to make this a better world (I hope!).
Everything is not lost for Facebook, though. It just has to get back to ‘the basics, of managing their billion-dollar byte’.
Let’s put this scenario to test using a model that I articulate in the 2017 American Book Fest finalist, The Billion Dollar Byte.
Yes, Facebook is certainly on the other side of the chasm of divide which traditional companies need to get past. However, as a digital native, Facebook has chosen to be a “rebel” by ignoring the basics of its data management policy. Without knowing much about the details of the internal processes itself, I can conclude that the events that unfolded could be attributed to a lack of ‘process discipline’. Yes, Facebook probably has a documented policy but their internal process lapses in ensuring compliance to that policy has resulted in the unfortunate events of a business actor accessing data that should not be. And in the process, the billion-dollar byte, is at risk. WE are at risk. The digital age is at risk.
Ouch!!! It hurts…
Not just Facebook. It hurts all of us aspiring to evolve into the digital age.
But, let’s not loose heart. The good news is that businesses that stick with the basics, will WIN! No exceptions. Also, let’s not forget that WE the users of Facebook are equal partners in it’s evolution.
If Facebook’s processes had the necessary checks and balances in place, we probably would not have the need for a fascinating pioneer like Mark Zuckerberg face embarrassing questions from the members of congress.
All the best Mark! Be honest. Be yourself. Everything else, will fall in place.
In an article in Scientific American, I had written the about how big data can help rebuild america’s ageing infrastructure. This day an age, I am absolutely convinced that the combination of man and technology should be performing tasks better than ever before.
As I was passing through security check at Kastrup airport in Copenhagen, I was observing the progress velocity of the passenger queue. I was wondering how the conditions of both the passengers as well as the security staff could be improved. The process of managing trays on the conveyor belt is certainly a candidate for a robot to manage. Instead, the human staff could focus on making sure that the experience of the customers is improved. I certainly don’t see a huge risk of loosing jobs if processes and key goals of a process are well understood.
While the example above was of how a robot could fit into our life, the one major issue I constantly encounter and question, is ‘our ability to act on data’ as well as our ‘inability to act on data.’ In fact, my organisation, the data strategy lab has been conducting surveys in order to assess where an organisation stands on this spectrum.
It is clear to me as well as the participants of the surveys, ‘our ability to act on data’ is low. i.e., our ‘inability to act on data,’ is high. I find this unacceptable with available technologies and knocking what the combination of people, processes and technology can do.
The Florida Bridge collapse is a recent demonstration loss of life and property due to our ‘inability to act on data,’ in a timely and a comprehensive manner.
To this end, I recently delivered a keynote speech at The ZHAW Zurich University of Applied Sciences. The audience were a group of human capital leaders from various industries. The program was led by a smart, bright and brilliantly enthusiastic Dr. Elena Hubschmid-Vierheilig (https://www.zhaw.ch/de/ueber-uns/person/hubh/).
As a part of the session we were reviewing our ability to act on data as well as our preparedness to address the human capital need of managing an airport operation, which has data potentially being dispensed from numerous devices and elements. The question posed to the group was – “…are we adequately prepared to address this human capital need…?” The unanimous response was – NO!
Fortunately, experts such as Dr. Hubschmid-Vierheilig, have been teaching about the confluence of human capital management, big data analytics and innovation need.
My message to leaders as well as aspiring leaders in the digital age, is to aim at “Getting to YES, Now!” Especially, on matters related to safety, efficiency and compliance. Good profits are bound to follow, when our focus is set right. And of course, it should be on – people. Which is what I call, ‘The Billion Dollar Byte.’
When a great mind departs our world, the void left behind will be felt for a long time to come. This is how it was today, on the day the world learnt of the demise of the Stephen Hawking. He died at age 76.
Interestingly, the Mr. Hawking has not won a Nobel Prize. That is because no one has yet proven his ideas. The Nobel committee looks for proof. Big ideas on the other hand, are not candidates for a Noble Prize. I trust that with available technologies and hopefully with upcoming datapreneurs, in the scientific communities, the world will one day be able to prove the theories of Stephen Hawking.
While we wait for the datapreneurs in the scientific communities to evolve, here’s a list of my top ten favourite quotes of Stephen Hawking, which should inspire business and technology leaders, the people I serve with my craft and profession:
“Intelligence is the ability to adapt to change.”
“While physics and mathematics may tell us how the universe began, they are not much use in predicting human behavior because there are far too many equations to solve. I’m no better than anyone else at understanding what makes people tick, particularly women.”
“People won’t have time for you if you are always angry or complaining.”
“However difficult life may seem, there is always something you can do and succeed at.”
“Life would be tragic if it weren’t funny.”
“We are just an advanced breed of monkeys on a minor planet of a very average star. But we can understand the Universe. That makes us something very special.”
“Work gives you meaning and purpose and life is empty without it.”
“I am just a child who has never grown up. I still keep asking these ‘how’ and ‘why’ questions. Occasionally, I find an answer.”
“I was not a good student. I did not spend much time at college; I was too busy enjoying myself.”
“Science can lift people out of poverty and cure disease. That, in turn, will reduce civil unrest.”
RIP – Stephen Hawking.
Guest Post Contributed by Prof. Bart Baesens, Véronique Van Vlasselaer and Prof. Wouter Verbeke
Fraudsters develop advanced strategies to cleverly cover their tracks in order to avoid being uncovered. They try to blend into the surroundings as much as possible in order not to get noticed. Such an approach reminds in fact of camouflage techniques as used by the military or by animals such as chameleons and stick insects. This is clearly no fraud by opportunity, but rather carefully planned, leading to a need for techniques that are able to detect and address patterns that initially seem to comply with normal behavior, but in reality instigate fraudulent activities.
In their new book, Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques, Baesens, Van Vlasselaer and Verbeke explore various ways of detecting fraud using state of the art analytics.
Detection mechanisms based on unsupervised learning techniques or descriptive analytics typically aim at finding behavior that deviates from normal behavior, or in other words at detecting anomalies. These techniques learn from historical observations, and are called unsupervised since they do not require these observations to be labelled as either a fraudulent or a non-fraudulent example case. Outlier detection techniques have great value and allow detecting a significant fraction of fraudulent cases. In particular, they might allow detecting fraud that is different in nature from historical fraud, or in other words fraud that makes use of new, unknown mechanisms resulting in a novel fraud pattern. These new patterns are not discovered by expert systems, and as such descriptive analytics may be a first complementary tool to be adopted by an organization in order to improve a classic expert rule based fraud detection system.
Descriptive techniques however show to be prone to deception, exactly by the camouflage-like fraud strategies discussed above. Therefore the detection system can be further improved by complementing it by a tool that is able to unmask fraudsters adopting a camouflage-like technique. Supervised learning techniques or predictive analytics aim to learn from historical information or observations in order to retrieve patterns which allow differentiating between normal and fraudulent behavior. These techniques exactly aim at finding silent alarms, the parts of their tracks that fraudsters cannot cover up. Supervised learners can be applied both to predict or detect fraud as well as to estimate the amount of fraud.
Predictive analytics has limitations as well, probably the most important one being that it needs historical examples to learn from, i.e. a labelled data set of historically observed fraud behavior. This reduces the detection power with respect to drastically different fraud types making use of new mechanisms or methods, and which have not been detected thus far and are therefore not included in the historical database of fraud cases from which the predictive model was learned. As discussed above, descriptive analytics may perform better with respect to detecting such new fraud mechanisms, at least if a new fraud mechanism leads to detectable deviations from normality. This illustrates the complementarity of supervised and unsupervised methods and motivates the use of both types of methods as complementary tools in developing a powerful fraud detection and prevention system.
A third type of complementary tool concerns social network analysis, which further extends the abilities of the fraud detection system by learning and detecting characteristics of fraudulent behavior in a network of linked entities. Social network analytics is the newest tool in our toolbox to fight fraud, and proofs to be a very powerful means. Social network analytics allows including an extra source of information in the analysis, being the relationships between entities, and as such may contribute in uncovering particular patterns indicating fraud.
It is important to stress that these three different types of techniques may complement each other since they focus on different aspects of fraud and are not to be considered as exclusive alternatives. An effective fraud detection and prevention system will make use of and combine these different tools, which have different possibilities and limitations and therefore reinforce each other when applied in a combined setup. When developing a fraud detection system, an organization will likely follow the order in which the different tools have been introduced although the exact order of adopting the different techniques may depend on the characteristics of the type of fraud an organization is faced with. In a preliminary but possibly important first step to develop awareness within the organization, an expert based rule engine may be developed. Subsequently in a second step the system may be complemented by using descriptive analytics, followed by adopting predictive analytics and finally social network analysis techniques. Developing a fraud detection system in this order allows the organization to gain expertise and insight in a stepwise manner, hereby as well facilitating each next step. Also, the required data is being gathered and the organization’s IT systems prepared for next steps in an evolution towards developing and deploying a powerful, multi-armed, state-of-the-art fraud detection system.
For more information, refer to: Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques, published by Wiley.
More information about the authors:
Professor Bart Baesens is a professor at KU Leuven (Belgium), and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on analytics, customer relationship management, web analytics, fraud detection, and credit risk management. He has also developed two Self Paced E-learning courses: Advanced Analytics in a Big Data World and Credit Risk Modeling. See www.dataminingapps.com for more information about his research. Bart.Baesens@kuleuven.be
Professor Wouter Verbeke, Ph.D., is an assistant professor of Business Informatics and Business Analytics at Vrije Universiteit Brussel, Brussels, Belgium. He graduated in 2007 as a civil engineer and obtained a Ph.D. in applied economics at K.U.Leuven in 2012. Wouter.Verbeke@vub.ac.be
Véronique Van Vlasselaer graduated magna cum laude as Master Information Systems Engineer at the faculty of Business and Economics, KU Leuven (Belgium). With her master thesis ‘Mining Data on Twitter’, she won the Best Thesis Award from the faculty. In October 2015, Véronique obtained her degree of Doctor in the Applied Economic Sciences with prof. Bart Baesens at the department of Decision Sciences and Information Management. The title of her Ph.D dissertation is ‘FAIR: Forecasting and Network Analytics for Collection Risk Management’ which mainly focused on the development of fraud detection techniques using social network analysis. During her Ph.D, she worked together with Smals Research (RSZ-ONSS) and Atos Worldline. She currently works as an Analytical Consultant at SAS Belgium & Luxembourg. Veronique.Van.Vlasselaer@sas.com
Our current legal system recognises “domestic” and “international” geographic jurisdictions. However, this does not seem to be helping technology firms and law makers agree on matters related to data access for legal proceedings.
The tech giant, Microsoft, which has 100 data centers in 40 countries, is the first American company to challenge a domestic search warrant seeking data held outside the United States.
The case began with a 2013 warrant obtained by prosecutors for emails of a drug trafficking suspect, whose emails were stored in Microsoft computer servers in Dublin.
Microsoft then challenged whether a domestic warrant covered data stored abroad. The Justice Department said because Microsoft is based in the United States, prosecutors were entitled to the data.
This case is a demonstration of governments having to stretch their jurisdiction boundaries, potentially risking the business interests of companies as well as creating tensions with the country governments where the technology footprints extend, as in the case of the data centre presence in Dublin, Ireland.
This major privacy rights fight between Microsoft and the Justice Department reached the U.S. Supreme Court in February 2018. The justices are considering whether U.S. law allows prosecutors to compel technology companies to hand over data stored overseas.
According to Reuters contribute report on CNBC, the nine justices will hear arguments in a case that pits the interests of technology companies and privacy advocates in safeguarding customer data against the demands of law enforcement in obtaining information crucial to criminal and counterterrorism investigations.
This case is likely to be a reference for other countries wrestling with similar concerns. The European Union is also watching this closely, as the GDPR date approaches rapidly. The case ruling is due by the end of June, 2018.
Earlier in 2016, a decision by the New York-based 2nd U.S. Court of Appeals favoured Microsoft with a marked victory for tech firms that increasingly offered cloud computing services in which data is stored remotely. However, President Donald Trump’s administration appealed that ruling to the Supreme Court.
If the US government’s reach were to extend to the data centres all around the world, the globally dominant U.S. based technology companies are likely to suffer, as customers will go to companies in other countries where they do not have to deal with this ‘hassle’.
This is similar to the U.S. government seeking the details of U.S. citizens in Swiss banks, for example. As a result, Swiss banks raised the entry barriers for American citizens seeking a Swiss bank account and in some cases, do not even entertain American citizens as customers.
Such an approach by any government, is likely to be a cause for international tensions.
If our world is to enjoy efficiency and growth gains offered through technological advancements, law makers and governments will need to re-think “jurisdictions” with due sensitivities.
Clearly, our current paradigm of physical jurisdictions in a digital world has its limits. It’s probably time to consider “cyber-jurisdictions.”
Many companies most of us know, mistakenly assume GDPR is purely a legal issue. The reality is far from the truth. In fact, this flawed assumption is because of a limited or no understanding of what data is to the business, and what it is not.
Incidentally, no single department in an organisation can address GDPR on its own, single-handedly. In fact, it requires an enterprise level view to address compliance, effectively, efficiently and more importantly, dare I say – ‘profitably’. For starters, ‘absolute compliance’ may not be possible for many organisations by May 25 2018. However, every CIO must at the least get control on their outcomes, related to GDPR.
Over the past few years, most CIOs started to recognise the importance of data management and data protection. But, GDPR started to add a sense of unprecedented urgency to those efforts. Many CIOs are probably even losing sleep on this.
The European Union’s (EU’s) General Data Protection Regulation (GDPR) will affect virtually any company in any sector around the world that processes the personal data of EU residents. Although, this may tend to put undue pressure on IT executives in order to ensure that their organisations are prepared, CIO’s must educate the enterprise that data matters are indeed a business strategy issue and not just an IT only issue. CIOs must build their case to communicate this to their business colleagues as well as their boards.
The GDPR replaces the EU’s Data Protection Directive 95/46/EC and is meant to harmonize data privacy and data protection requirements across Europe. One of the key difference between the new regulation and its predecessor, however, is that it holds accountable all companies that process personal data associated with EU residents, regardless of whether those companies have a physical presence in the EU or not. The potential penalties for noncompliance, meanwhile, are not trivial, reaching as high as 4 percent of global revenue or 20 million euros, whichever is greater. So, that’s what it is going to cost you if your C-Suite get things wrong.
Here’s a bare minimum, five things every CIO must do in ensuring that his or her organisation, is ready for GDPR compliance, even if you believe you are running late.
- Understand that data is a trail of your business processes. And this data must be managed with increased record-keeping. This is not new to most companies; however, the most undisciplined companies are obviously going to be penalised for this negligence and will have to get their house in order. Thankfully, most IT departments are capable enough.
- Get good at performing data protection impact assessments (DPIAs). Ensure that DPIAs are an integral part of your existing business and technology processes. The GDPR requires organisations to conduct data protection impact assessments for any new processing or changes to processing deemed to represent a high risk to the privacy and protection of EU resident personal data. This calls for a high level of transparency of both the process as well as data landscape.
- Incorporate Privacy by design into your culture and DNA. The GDPR requires privacy and data protection controls to be incorporated by design into any new or existing systems or processes that involve EU resident personal data. Ensure that communications and training programs address this as a part of your culture initiatives.
- Know and treat data sensitively while considering data portability and erasure. Under the GDPR, organisations must provide EU residents with the ability to access, correct, and erase their data, as well as allow them to move it to another service provider if they so choose.
- Step up to a culture of managing data risk in your business. Get control over third-party risk management. Remember, that person-centric data is most valuable to your business anyway. It is the billion dollar byte. GDPR is now an opportunity to get your act together, even when third parties are managing your data.