Retail Digital Transformation

In the last 7 to 5 years an unprecedent shift occurred in the way consumers interact with retail companies. Consumers complete transactions either online or in-store. Consumers still buy goods at physical stores and switch from physical to digital and back to physical. Contrary of what we may think – and this is also confirmed by retail customers with international presence I am working with – stores continue to contribute almost half of all retail growth; brick-and-mortar sales are not shrinking, but actually growing [1].

Hence, the big question is, where it relies the difference on how we interact and sell, if everyone is doing the same and copy the approaches? Where it lies the competitive advance of doing it differently?
Make a difference means mastering the art of:

  • In-store experience: is related with virtual shopping assistants, with sensing emotions by analyzing expressions related with prices, promotions and the products offered, mixed reality, which the customer can experience the product virtually or get more features by connecting to his personal profile and discover if there is a match. By recognizing and interpreting facial, biometric and audio expressions, new artificial intelligence technologies can identity customers emotions, reactions or mood and deliver contextualized products, recommendations or support – by the use of bots, that use natural language processing to help customers effortlessly navigate questions (“is this size or color available?”; “Can I ship back home the products while I am going to watch a movie?” — improving the customer experience.
  • e-commerce: providing a mobile app is not enough, actually, there is being sensed that there is a point of saturation about using apps because all of them do exactly the same which most of the time is a simplified version of the web site with a different form format. The next wave of innovation is related with prescription and recommendation engines. The customer will see the products and the offers that really matter to him based on the customer profile and combining other sources of external data which he expresses his needs and wants. Recognizing customers and customizing the e-retail experience to reflect their current context, previous purchases and shopping behavior. As customers look to build confidence in a purchase decision, automated assistants can help narrow down the selection by recommending products based on customers needs, preferences and lifestyle.




Capture II

The data focused organization


The art of mastering data in the retail sector will be dependent on the collection of in-store data , product data , and customer data new data sources coming from experiences expanded by the art of the possible using artificial intelligence.
Other key challenge is how to create and expand an ecosystem, a business ecosystem [2], like its biological counterpart, gradually moves from a random collection of elements to a more structured community, adding more partners, more products, more offers and enlarging the customer base. In a business ecosystem, companies coevolve capabilities around a new innovation: they work cooperatively and competitively to support new products, satisfy customer needs, and eventually incorporate the next round of innovations [2]. Of one key success of Amazon is how they grow in terms of product offerings. They started as book store. Today, they sell virtually anything.
In business ecosystems, a smart company manages information and its flows. In terms of data, this is not about our view of customer, that can be expanded how each partner that belongs to ecosystem increases that view of the customer and how it detects new opportunities by having access to a much more bigger customer and customer profile, alone or even partnering with other companies together. Retailers by being the anchor of such immense data lake, will monetize from each transaction occurred as all the other connected partners, the more the customer buys, the ecosystem grows as the business opportunities. On the other hand this will allow to evolve business capabilities. If a highly efficient logistics company joins the ecosystem, all the merchants can if they want benefit from the new innovative added capability, if a Retailer attract a fintech company to support new ways of doing payments, they will drive new interactions with millennials or digital savvy customers.

[1] – The great retail bifurcation – Deloitte Consulting 2018

[2] – Predators and Prey A New Ecology of Competition – James F. Moore – Harvard Business Review


The man and the machine manifesto – Part II


In the man and the machine original ramblings, I alluded to the to the discerning challenge between humans and powered Artificial Intelligence machines will work together, against the “tangled recursion” [14] as an example of machine intelligence. This log entry expands deeper the doubts and wonders about man and machine co-existence.

Cybernetics the need of adopting other forms of intelligence

Cybernetics become popular when the works of the first generation of cyberneticians like Norbert Wiener and Ross Ashby grow reputation from the lectures of Stafford Beer [10] and the works of Gordon Pask on training and teaching machines [11]. Applying the laws and principles of cybernetics, especially the law of requisite variety – control can be obtained only if the variety of the controller is at least as great as the variety of the situation to be controlled [8] – to the design of effective organizations, Stafford Beer formulated the Viable System Model (VSM) [9] as a method for designing organizations that are able to survive and thrive in a changing environment [9]. The VSM was then a vision of the organization in the image of the human species. Functions of management and control were envisioned on the lines of the human brain and nervous system. The brain and nervous system, were simulated by a combination of information technologies and human interaction. The VSM is probably one of the most elaborated representations of the fusion of the man and the machine [12] and the primacy of the role played by information in control systems and decision making. The fusion or combination of man-machine can be considered in form as a cyborg – that has certain physiological and intellectual processes aided or controlled by mechanical, electronic, or computational devices [13].

The limitations or the utopia of singularity



The achievement of singularity is perceived or motivated by advocators that show fear of death or want to reach a stage of immortality and therefore are irrational, combined with the fact of the looming of the ubiquitous computing, which, computing is made to appear everywhere and anywhere [6] with possible endless workloads combinations, omnipresent, making computing an embedded, invisible part of today’s life. Singularity is perpetually 15 to 25 years in the near future and that future keep being delayed [5]. Singularity supporters, tend to forget about the computing limitations on some of the use cases that are just about to become a reality, like for example, brain simulation. To simulate 10 seconds of real brain time would require about one year of computer simulation [7] in the current most powerful existing supercomputer.

Do we want machines to feel or do we foster a future which humans will augment their natural born capabilities?



Feelings can only be won by creatures who already have a mind and you can only have a mind if you have a nervous system [1], which in the case of machines, is absent. In the past decade, there an intense debate about if machines can or will feel. Emotions are considered as a non-detachable part of intelligence. Emotions be catalogued as rage, fear, panic, love, happiness and it can drive to take actions. Humans classify emotions and assign them some other emotional value [2]. Such value changes taking into consideration the societal environment humans live or are surrounded by. What can be condemned in one society can be accepted in other. The meaning of the the emotional values is the basis for conscious experience. Therefore, understanding the cartography of the interaction the human and the environment is critical for understanding the nature of consciousness [2]. Our universal individuality is cannot separated by the sacred, profane and spirituality [3]. The flow of other people, nature, environment and ancestor influence that provided us the life principle guidelines we adopt or tend to ignore that is a consequence of what surround us and make us unique individuals. Because machines do not and most likely will not possess consciousness, they are incapable of having free will and intentionality, something that is an essential criteria for moral agency [4].



[1] António Damásio – In The Strange Order of Things: Life, Feeling, and the Making of Cultures – ISBN – 9780307908759

[2] Mark Solms – The Brain and the Inner World: An Introduction to the Neuroscience of the Subjective Experience – ISBN – 9781590510179

[3] Elizabeth Tunstall – Decolonizing Design Innovation: Design Anthropology, Critical Anthropology and Indigenous Knowledge in Design Anthropology Theory and Practice – ISBN – 9780857853691

[4] Kenneth Einar Himma – Artificial agency, consciousness, and the criteria for moral agency: What properties must an artificial agent have to be a moral agent?. Ethics and Information Technology, 11(1), 19–29 – ISSN: 13881957

[5] Stuart Armstrong, Kaj Sotala – How We’re Predicting AI or Failing To – In Beyond AI: Artificial Dreams, edited by Jan Romportl, PavelIrcing, Eva Zackova, Michal Polak, and Radek Schuster, 52–75. Pilsen: University of West Bohemia.

[6] Dietmar Möller – Guide to Computing Fundamentals in Cyber-Physical Systems Concepts, Design Methods, and Applications – ISBN – 9783319251769

[7] Arlindo Oliveira – The Digital Mind: How Science is Redefining Humanity – ISBN – 9780262036030

[8] W. R. Ashby, An introduction to cybernetics – ISBN – 9781614277651

[9] Stafford Beer, Brain of the Firm – The Managerial Cybernetics of Organization – ISBN – 9780471948391

[10] Roger Harnden and Allenna Leonard – How Many Grapes Went into the Wine: Stafford Beer on the Art and Science of Holistic Management – ISBN – 978-0471942962

[11] Andrew Pickering – The Cybernetic Brain: Sketches of Another Future – ISBN – 9780226667904

[12] Stafford Beer – Diagnosing the systems for organizations – ISBN – 9780471951360

[13] Woodrow Barfield – Cyber-Humans – Our Future with Machines – ISBN – 9783319250489

[14] Gödel, Escher, Bach: An Eternal Golden Braid – ISBN – 9780465026562


BPM Blogs worth reading 2017

Here it is the list of BPM blogs which I normally consume on a random basis for research purposes.

On BPM at large:

  • Bp-3 – Scott Francis’s blog brings a balanced viewpoint on BPM trends and challenges and entrepreneurship.
  • Cape Gemini blog – A good source to look for trends on digital transformation.
  • Column 2 – Independent source on BPM systems review by Sandy Kemsley.
  • IEEE Spectrum – Future technologies brought by IEEE.
  • Improving Enterprise BPMS – A great blog to look for frameworks by Alexander Samarin.
  • Jim Sinur – Good insights about BPM future trends.
  • PeterVan – A 1.0 version type of blog that curates interesting articles from Peter Vander Auwera.
  • On Web Strategy – Dion Hinchcliffe writes about social business.

On Analytics:

On Complexity:

On Enterprise Architecture:

  • Found In Design –Nigel Green writes about advanced Enterprise Architecture.


If you are interested in 2016 list click here.

From Know Your Customer to Know Your Tax Payer

I have been working with a tax authority on developing some scenarios that were translated into a transformation roadmap with the objective of increasing tax and non-tax revenue.

One of the challenges is to predict active debt management before arrears occur. The idea is using advanced analytics by modelling the risk that company will fail to pay their taxes, by creating clusters of potentially high-risk debtors, based on available information regarding the annual, quarterly and monthly returns filling. One of challenges that exists in this approach, despite being proven that is more effective that discover “after the fact” the existence of a tax debt, is by the constant change in business models, companies makes new investments or shift to new business models that drags quickly the company to a position it cannot comply with its tax payment obligations.

Know Your Customer (KYC), is an approach that is being used, mostly in financial institutions, in terms of opening a bank account, require trading operations or process payments. Some banks are enhancing the concept of KYC to a point that they rely on information that is not related with transactions between the customer and the bank. As I pointed in this previous post, about creating a Banking Platform as a Service, that goes beyond on implementing a new IT capability that can spark new business opportunities and expand the traditional bank value chain, banks today can have a very precise view of a profile of an individual or enterprise. In some KYC scenarios and because of the magnifying effect of such profile. As an example, if you are an individual, instead of asking what was the brand of your first car, they will start asking questions on which part of the globe you were 2 months ago, where you stayed, what brands did you spend money with and what kind of affiliation you have with a 3rd party loyalty program or even if you have contracted loans with other institutions and which under what circumstances such loans were requested.

From a government perspective, using a shared and expanded Know Your Tax Payer (KYTP) is a valuable approach not only to prevent tax arrears or unrecoverable tax debt, as well as uncover misreporting and non-compliance related with the structure of income flows or unreported income or even claiming subsidies or tax deductions regardless of the source. Despite there is a convergence of government data interchange effort, as well as, trying to overcome some legal constraints in terms of sharing tax information across multiple government agencies that own the responsibility of collecting different non-tax revenue sources, it is still clear that there are missed opportunities in terms of securing tax collection.

One of the events that is being used to detect failure on future tax payment, is when is flagged by bank that a customer is missing payments regarding a loan or its ratting was put with a negative outlook. That event can be used by the government agency to start working with the individual or enterprise in order that will not exist missed tax revenue. The Know Your Tax Payer (KYTP), can be also used by all the entities that feed knowledge base, e.g. other banks that belong to the system (Telecom’s, Utilities, Insurance Companies) will also be alerted by a missed loan payment contributing to decrease their risk exposure, when debt carousel schemes are implemented. There are other scenarios that such an approach can also be beneficial, not only related with tax compliance. In terms of investment programs, related with shared responsibilities on entitlement of government funds, which access is granted by a government subsidy, as well as, by banks, even under a syndicated loan approach, using a KYTP will contribute access to grants or subsidies to entities that deserves such access and in better terms and change tax payer behavior.

The man and the machine manifesto

“Self-organised systems, lie all around us. There are quagmires, the fish in the sea, or intractable systems like clouds. Surely, we can make these work things out for us, act as our control mechanisms, perhaps most important of all, we can couple these seemingly uncontrollable entities together so that they can control each other. Why not, for example, couple the traffic chaos in Chicago to the traffic chaos in New York in order to obtain an acceptably self-organising whole? Why not associate brains to achieve a group intelligence?”

Gordon Pask, The natural history of networks


Today there is a shadow or sense of doubt if we as humans want machines to think or to do – some people already argue they do think, detached from the consciousness bond – and it would replace humanity soon, as many others advocate singularity is near with systems that can adapt themselves, command, control other systems, something as Douglas Hofstadter referred to “tangled recursion” as an example of machine intelligence.
I ultimately believe that humans and powered AI machines will work together, not compete against each other. Humans will be much more empowered by the symbiotic combination of machine work, meaning that we will need to continuous to adapt to rather than become indispensables, we increase our own capabilities.
However, there are many untamed challenges in terms of such man and machine symbiosis, as we the human species, have the responsibility to define by which rules we want to live, as machines progress in new areas, changing the foundations on our society is organized, as per bellow.

Much has been discussed how to define machine design rules and relevant regulation. Some experts believe that is the hands of humans to define such rules and while machines are tightly controlled by humans we can define how machines should be engineered. However, some examples related with war machines, demonstrate that Isaac Asimov’s laws do not apply anymore, once the potential for harm is increasing rapidly.
Hence the challenge stands. Consider the scenario of an intelligent medical system that provides counselling and advisory, induces a medical doctor with error. Who is responsible? The Doctor? The system? The entity that conceived the system? The trainer that trained the system to make decisions, based on a knowledge base? How do we deal with human life loss? Regulatory bodies for the engineering profession or other domain expertise, have clearly defined rules for design or professional act decisions, made by humans, however, in terms of machines endowed with any kind of intelligence, governance appears missing and there is no common broad agreement.

Societal impact, innovation and economy growth
There is no doubt that technology was always the common denominator that sparked economic growth, the press, steam engines and lastly the internet, created in three different moments in time tectonic shifts. However, prosperity also contributes to unemployment. Technology tends to automate at scale and replace repetitive tasks, but the last wave of technological developments is already targeting knowledge workers as well. Hence, the challenge is not related with low income workers only. The balancing act should be how the use of technology can contribute to higher living standards, diminish inequality and drive inclusion.

Human and Machine Interface
Mixed reality is becoming a popular interface in human-computer interaction for combining virtual and real-world environments, and it has recently been a common technique for human-robot interaction, it price is however a barrier for adoption and creates digital imparity. Natural language processing is becoming another de-facto interface, applied for example on business to consumer interactions, but some questions are still not addressed in terms of humans that speak a language blending influence of their own culture that a machine is not aware of. Despite the advance interacting with devices like smartphones, as technology progresses, it is relevant do involve interface designers to make a reflection how machines affect human to human interactions and human to machine interactions.

Tackling the trade-off between privacy and security is today already a challenge, related to the fundamental but complex separation between what constitutes the private and the public space of an individual. The definition of a concept, a domain, is a consequence of the surroundings, of the environment we live and the multitude of human principles and beliefs. What in a society can be accepted as a practice, in another can be condemned. The concept of privacy is constantly being redefined to a point that can be transform into a matter of transparency, for example, sharing publicly your taxes declarations if you are a politician. How we deal with ethics in terms of a machine that have access and share our medical records that will make decisions in terms of triage or sense of urgency related with medical treatment? It’s in ethical that a machine can make judgment about predicting future crimes or provide a credit risk score based on data that is related with our profiles?

Would you consider ethical to create a system that reproduces an nonexistence life form in other medium?

Wired published a story about a son that knew that he was just about to lose his father and created a BOT, called DadBot, to preserve his existence. The story can be found here.

As I finished reading the article two, above many other questions came to my mind:

  1. It is ethical to preserve the existence of a living being after his death? The definition of a concept, a domain, is a consequence of the surroundings, of the environment we live and the multitude of human principles and beliefs. What in a society can be accepted as a practice, in another can be condemned. Now, I believe because this is a foundational universe functioning rule, that what is born it will die. We all know that we want to preserve the life of our beloved ones and definitively there are scientific studies that demonstrate how positive it is to create other ways of engagement with a person that does not inhabit our world. However, is my belief that recognizing that someone died, implies we cannot recreate interaction. One can argue that browse pictures or watch videos is another way of interacting. Would you consider ethical to create a system that reproduces an nonexistence life form in other medium?
  2. How fast the system is going to become obsolete? James Vlhaos, refers that he collected information from his father in a way that the BOT could later share stories and past experiences with the interlocutor. He provides an example how the system is context aware and interacts with the user remembering past stories that were lived together, “Remember that big barbecue dinner they hosted for us at the taverna?” – he writes – nevertheless, what happens when there are no more stories to tell? Are we interested in repeat the experience until exhaustion is reached? One can argue that is the precise function of the system and immortality is reached. If you want to know about a person, particularly younger generations that never met that person, they can get acquainted without facing the risk of facts distortion or even loss, as it happens when the elder generations die and the memories are washed away with the dead. On the other hand, this is another way to preserve the bond, the ties and the affection, like it happens in real life and people like to repeat the same stories over and over to create that sense of collective existence. Last, how do you as a solution architect, a designer, choose the content? Image that your relative committed war crimes, something that second world war generations need to deal with in Germany, would you recreate the life of your siblings, your grandfather if you knew he committed such crimes, would you hide those facts or would you expose it?

How banks are missing the Banking As a Service platform opportunity to unusual challengers

Oil & Gas companies are reinventing the customer journey at the service station and it is not focused anymore on enhancing the non-fuel business business at the retail store. What was a trend in terms of disinvestment in the downstream business is picking up as a new business opportunity to increase revenue and customer stickiness. On the other hand, some banks are loosing opportunities in terms expanding their value chain and services to a combination of joint ventures between Oil companies and Telecom’s.

We see Amazon going to brick and mortar grocery stores; we see Oil & Gas industries enter into renewable energy, we see Utilities companies entering in mobility business, we see Energy and Construction also entering in renewable energy. Hence, there is going to be fierce competition among the mature industries, between incumbents and new entrants and disruptors.

Digital transformation fades the value chain separation and starts an intersection, meaning that if Engineering and Construction companies enters into the mobility business by providing services related with electric car charging stations, soon will be working together in partnerships will gas station retailers, convenience stores retailers, banks, telecoms, mobile money providers and together, the ecosystem of companies working in the same space interacting with the consumer as one.

The case of the Smart Service Station

The book The Digital Transformation Playbook Rethink Your Business for the Digital Age [1] , provides a simple framework on how to access your position “vis-a-vis” challengers that by the power of technology start to intersect business models inside of competitors value chain. What I like about the framework is how easy it is to organize some ideas to spark digital transformation.

Telecom’s instead of banks see 3 different kind of customers:

  • The car driver;
  • The retail store;
  • The 3rd party provider – a company that does not operate at the station. It can be an insurance company, an online retailer, GPS technology provider, the car manufacturer;
  • The car manufacturer, if the car is connected, like some of the new generation models.

The Bank, only sees the car driver.

The Telecom wants to provide the following value proposition:

  • The car driver – pay on customer terms; product offerings and promotions that are related with the real customer needs and wants; access to extended valuable services, like journey management, integrated road assistance.

The Bank only offers cashless payment to the car driver.

In terms of value network, the Telecom offers to the car owner:


  • Integration, with the payment providers, retail stores;
  • Customization, the Telecom is able to tailor offerings based on any data coming from interactions with the partner ecosystem;
  • Simplicity, the car driver can pay using a mobile phone only.


  • Customers, 4 customer categories instead of the car driver only;
  • Partners, endless partners connected with the platform, letting the car driver add or select the partners that we likes to engage with;
  • Complementary products or services, by the effect of partnership, beyond the typical cross-sell, up-sell;
  • Cost structure, lower. Customers are sensitive to fees and levies that banks charge using cards;
  • Data assets, a much higher precise of the customer profile that is not based on the transactions that occur at the station, but across all the connected partners.

The Bank only offers :


  • Simplicity. Customer do not need to use cash;


  • Brand.

Banks could for example expanding value chain and services: connect the customers with other service providers – e.g. wellness providers, retail companies – becoming part of customers’ needs and lifestyles. The more the customer interacts with the customer ecosystem, the more the ecosystem benefits in terms of shared customer profile data and business transactions. However, as some banks are still focused on putting their customer’s to transact with the bank, they forgot that Telecoms and Oil & Gas companies, or even non-usual players are shifting customers to transact with banks at gas stations.



[1] The Digital Transformation Playbook Rethink Your Business for the Digital Age –  David Rogers, ISBN – 978-0231175449