Electronic Distribution Requirements
Two effects on the organization of markets emerge against the background of electronic distribution.
The first has to do with the type of testing that the transaction creates and how it relates to the way markets are coordinated and organized. At one extreme, we would have a situation where information is scarce, goods characteristics are clear and few in number, customer relationships are weak in information content and are rare or intermittent.
We then find ourselves in the context of a transactional market. The transaction or price is determined a priori for the characteristics of the goods and the actors with defined clear preferences and utility functions.
The market itself has little memory and moves slowly. The consumer is the result of a sum of all their buying behavior. The feedback of consumption on production takes place in slow time and according to long socio-technical chains.
At the other extreme, we would have a situation where information is rich and abundant, product descriptions are complex, and information-rich, frequent and interactive testing and transactions.
The market then became definitional. The transaction and the price at which it is carried out are frozen and confirm the description of the products, their usefulness and the preferences of the consumer.
This market is changing rapidly. Goods have a career, and their properties change over the course of exchanges, as well as consumers’ preferences and utility functions.
Variations are fast. Historicity and memory play an important role in this form of market organization. Feedback on the definition of the offer from consumption apps is fast in a short loop.
The faster and cheaper this feedback, the more co-produced the transaction and the object, the supply and the demand. That is, it develops towards the coordination characteristic of service contracts.
Within this mode of coordination, services can be effectively compared, as in standardized service contracts.
On the contrary, it will be necessary to distinguish the way in which it is very difficult to compare, since they are linked by implied and informal contracts. There should be codable aspects of the interactions of actors promoting the effects of opacity in the organization of markets and partnerships.
Therefore, our field analysis of the electronic distribution of tangible goods by mass distribution players shows the possibility of a transition from the coordinating feature of a transactional and anonymous market to a defined and personalized market.
Now, taking a broader view and relying on the few studies presented in this issue, we can attempt to sketch an ideal type of market coordination specific to electronic distribution in a universe structured by dense information networks.
Therefore, it can be summarized in four important points.
— It is the transition from commercial rationality based on economies of scale to commercial rationality based on economies of scope. The problem of selling products to as many customers as possible has been replaced by the problem of selling all the services he needs to the same customer.
— There is a highly diversified structure of sectors and partnership forms, which makes it possible to increase the cost of leaving. It is an inseparable packaging of combined products and services (Separation destroys the investments made to establish the necessary harmony of supply and demand). These economies of scope largely correspond to the strategies of aggregated portals.
— The opposite of the commercial ideal where anonymous and knowledgeable actors exchange in a memoryless market. It is heavily equipped with connectivity and feedback tools, where instant coordination is essentially price-based.
— A personalized service that associates a tailored set of products and services around a particular customer. Prices may then depend on the singularity and the nature of the service as a whole. This may be affected by the overall value of the customer. This is defined beyond the commercial realm of individual transactions and includes both relational and expectation dimensions.
Each of these points, taken separately, is likely to fall within the usual industrial or commercial frameworks.
For example, price differentiation can be observed in an industrial context that is both flexible and oriented towards volume and production. This is the case of yield management. But it does not necessarily see the obvious effects of customer personalization or intensification.
Or, the diversification of services for the general public can be observed outside of the Internet, through the strategy of large retailers to offer financial, insurance or travel services.
It is therefore the unification of these disparate elements into a coherent whole that raises the question of a new form of coordination.
To arrive at the hypothesis of a radically innovative model of economic profitability of the Internet involved in the articulation of the commercial and non-commercial Web, there is the “3Cs rule” in the media.
Put more strictly in economic terms, it is necessary to combine the four terms of the ideal type formed above.
In such an ideal typical market, professional competition is aimed at capturing a well-known customer for all of his needs, not buying a generally known customer.
Therefore, it is important to capture a target audience, maintain an individual and personalized relationship with each member, anticipate meeting future needs.
Building loyalty through all free and paid services offered electronically and according to a system is also an important issue.
Chatbots & Enterprise Artificial Intelligence
References to artificial intelligence are becoming more and more frequent in our professional circle. Among the chatbots that will gradually replace the HR manager in key decisions such as employee responses, there are existing robotic systems.
Robotic Process Automation (RPA) empowering robots and replacing more than 80% of them can take place at every stage of the production chain of a vehicle in the Automotive industry. It is important to recognize that these new ways of working can have a positive impact on teams and therefore management.
Indeed, in terms of HR, archiving documents, managing sick leaves, developing employment contracts, managing peaks in activities are tasks that are now possible thanks to artificial intelligence.
But AI can go much further in recruiting processes. For example, it can improve predictive recruitment by traversing data from LinkedIn or any other social network.
Or internally, it identifies employees who are likely to seek positions at another company and therefore tracks the traces left in those networks. Of course, in this particular context, the question of ethics is as important as individual freedoms.
In turn, artificial intelligence also affects consumer relationship management. This should prompt us to reflect on the arrival of the digital twin, which will literally change the paradigm of creativity as we see it.
First we created the product, then we tested it and made the necessary changes. According to a pwc study, today, thanks to artificial intelligence and digital twin, it enables the gradual visualization of construction on a digital model. It also makes it possible to compare digital development with the end goal in real time and helps in decision making.
But if these robots offer a tremendous opportunity for management in terms of foresight and decision-making, two points remain crucial if we want human-machine coexistence to work and become profitable. This should go through a rigorous collection as well as a better collection.
Artificial Intelligence Today
The problem of artificial intelligence, used as a tool for advancement in the business world, is a central issue of competition, efficiency and service quality today. To be convinced of this, it is enough to look at the data on artificial intelligence.
Private and public players have increased their investments tenfold over the past five years to master this future technology and promise returns. For the HR function, it is now a problem to qualify as augmented HR, among other things.
The use of a chatbot, assigned to answer recurring and general questions, and during this time implies a certain progress.
Customers can benefit from more reliable proximity matching, among other things. It raises the question of how the company can use artificial intelligence to advance in the noble sense of the term. Humans must ensure the ethical use and legal safeguards of the tools inherent in artificial intelligence.
First of all, a task does not need to be automated systematically as it can be automated. It is the company’s responsibility to use AI for certain relevant tasks in accordance with its policy and culture. In addition, it is unthinkable that no human eye should look at the decisions made by artificial intelligence regarding a recruitment interview.
Finally, the amounts of data collected must protect the individual freedoms of customers and employees. As a result, success in the implementation and dissemination of AI tools depends on thinking and implementing a training policy for employees, initiated by working groups.
Leveraging Human Intelligence
Artificial intelligence is first and foremost a technology like any other. For example, today performs basic, routine and repetitive cognitive tasks.
And if AI can be a source of progress in terms of employee or customer experience, it all depends on how it’s implemented and the goals pursued.
Experiences developed in different fields show that it is more important than putting artificial intelligence at the service of people and their intelligence in order to better satisfy, inform and offer new services to the customer or make the job easier.
Therefore, it is essential that the implementation of artificial intelligence applications is based on the experience and perspectives of its users, who can enrich the services it will offer at least as much as the experts.
Finally, technologies should be designed to maximize their potential, not reduce human intervention.
Enterprise Artificial Intelligence
Artificial intelligence combines computer technologies that make it possible to mimic intelligent behavior in terms of sensing, reasoning or generating knowledge.
It is now available in all sectors of healthcare, transportation, e-commerce, industries. It is known by some widely promoted applications such as medical imaging, GPS, profiling of Internet users.
In medicine, as elsewhere, its purpose is to make the invisible visible to anticipate, prevent, read out the symptoms of a possible malfunction, and adapt the intervention or treatment as quickly as possible.
Its predictive nature, made possible by the computing power of its algorithms, by better visualization of the undetectable, depends on the perspective.
Artificial intelligence is sometimes presented as the initiator of the disappearance of human labor in favor of robots, a hyper-rational world that sometimes becomes a binary adorned with a thousand virtues.
In this latest perception, AI infused with virtues has become the key to reducing costs and improving business performance, assisting primarily in strategic decision making, but also in all management actions.
Cyber Security of Companies
The news of recent years has undeniably shown that the problem of companies IT assets can no longer be limited to the protection of infrastructures and data only against actions by malicious actors, of young people who only need approval.
Today, however, we only have fragmentary data on the status and level of the digital threat. Therefore, as highlighted in the cybercrime report, statistics from complaints about crimes or torts of a digital nature affecting companies, particularly theft of digital data or phishing, are very incomplete.
One of the explanatory factors is that they often refrain from filing a complaint when they are victims of crimes or crimes, as long as the legal process is lengthy and often creates publicity that is against the interests of companies.
For the latter, it’s important to first manage a crisis caused by a major computer incident. In addition, digital risk no longer takes the form of attacks that target only the digital assets of the targets (information systems, data).
It can also happen through actions aimed at the reputation or image of companies. It may even be the result of internal attacks that question the company’s information assets, whether voluntary or not.
Digital Threat Actors
Cybercrime has changed profoundly since the mid-2000s, both in terms of actors and methods. The actors of the digital threat to companies have become more professional and their forms of action have diversified.
In the 1990s, malicious digital acts were mostly perpetrated by computer professionals who wanted to demonstrate their skills by hacking into highly protected sites or servers, often owned by security or defense agencies.
The explosion of the role and place of information and communication systems in societies and economies (global and local) has whetted the appetite of criminals who anticipate the potential gains from these new fields.
The exploitation of hackers’ technical skills for glory has thus led to digital, professional and specialized crimes.
Cybercrime was initially demonstrated by the emergence and subsequent increase in cases of blackmail and the sale of counterfeit products on commercial Internet sites. The pirates thus gathered in a cell and shared duties.
Each of them, taken together, has certain skills that make it possible to infiltrate an information system.
Detection of open ports, leaking servers, bypassing firewalls, detecting new security vulnerabilities are some of them.
This is why criminal organizations call groups based on existing characteristics to meet specific needs. Tools used for cybercriminal activities are now on the black market.
Built over the years, it is governed by the law of supply and demand. As an example, strong competition opposes actors to master networks of zombie machines.
These can be rented at special sites on the Internet to carry out certain denial-of-service or espionage operations. The price of a thousand infected machines will range from $5 to $100 on some platforms, depending on the country.
However, higher prices may be applied within the framework of targeted operations and may be established by intermediaries who purchase machines at wholesale price. As with this market, more specialized skills or knowledge may be available, such as accessing certain machines or creating malware.
The professionalization and specialization of pirates is considered certainty. It is regarded as the evolution of its initially technical goals towards the pursuit of profit.
There is also a paradigm shift between a virtuoso but isolated pirate population and organized groups acting to enrich themselves.
The example of the Conficker worm, which emerged in 2008, illustrates the trend of increasing sophistication in malware. It is indeed very elaborate software designed.
However, this worm could have been developed not to cause harm, but rather as a stealthier and more effective demonstrator, announcing a new generation of more advanced malware. The Flameworm case, discovered in 2012, seems to confirm this hypothesis.
Parallel to the metamorphosis of computer crime towards profit-seeking, the evolution of the Internet, networks and connected digital tools show their position in web 2.0 in particular.
If malicious use of software is part of the arsenal of tools they distribute, they also use the sites they operate or participate in (blogs, forums, etc.) to disseminate their ideas.
As the Internet offers a global forum to warn and persuade consumers and citizens, sites are brought online to destabilize companies’ brand image or to misinform the markets.
Since 2010, a new mode of intervention has been developed, with the systematic posting of protected and even classified documents online.
In addition to identity theft, the goal of cyberspace attacks is no longer simply to destroy or render inoperable an information system for a certain period of time, but to undermine the credibility, legitimacy and reputation of a company or individual.
Humanized Artificial Experience
On March 14, 2019, a woman talks to a white humanoid robot. This scene may look like something out of a science fiction short novel or a vision from the future, but it wasn’t.
The intelligence of this new breed, whether in physical or internet bot form, grows exponentially as it becomes a learner (machine learning). Knowledge is accumulated through people’s contacts, wishes, desires, reactions and behaviors.
This indicates that the machine can effectively replace the receptionist today. The current role of artificial intelligence (AI) is to facilitate the buying or consumption experience.
It also participates in the multi-sensory staging of experience. Thanks to the sensors it has, it collects aggregate data about the location, behavior, sensations and even expressions of emotion of the visitor or customer.
These data are processed immediately to respond to the interlocutors. But it also yields highly detailed customer information that no conventional study can offer at equivalent cost.
Data is stored for use by analysts. In this scenario, the employee must learn to work with the AI, not against it.
Artificial Intelligence and Compensation Management
Many hopes and worries show that we know very little about the true progress of artificial intelligence.
There is computing power that integrates automated or deep learning and has never been available before from the ever-increasing volume of data.
The promise of cognitive probabilistic systems allows us to imagine the scope of innovations that can advance and improve the company.
This computing power is of particular interest for fee management. Artificial intelligence is used to respond as closely as possible to the needs of companies, taking into account the characteristics of each employee.
It should allow the development of remuneration systems towards greater internal and external justice.
It can also encourage payroll optimization by making it possible to evaluate the performance and return on investment of these systems. This is also a hyper-specialized start-up positioning that relies on artificial intelligence to advance compensation management.
However, these capacities for advancement still seem to depend heavily on advances in academic research.
For example, we know almost nothing about the best way to set up a compensation system that uses all of the individual’s motivational factors. To gain the upper hand over humans, robots will have to wait for research to progress.
Artificial Intelligence Experience
The concept of experience has become very important for every company, whether you are a customer or an employee.
It should create a set of emotions for its customers that builds trust and loyalty in multiple interactions with them before, during and after the purchase.
For their employees, it’s a matter of providing opportunities throughout their careers to attract, motivate and retain them. Because a satisfied customer or a dedicated employee is a source of added value for the company.
If this statement is not new in itself, its implementation methods, with the contribution of new technologies and especially artificial intelligence, proves that the customer experience is a real source of enrichment.
Artificial intelligence makes it possible to automate simple and repetitive activities that are still necessary for the smooth functioning of the relationship with customers, employees.
This enhances support by processing requests, for example, through virtual assistants or by a permanent presence on certain topics.
Artificial intelligence also makes customers and employees better known. The ability to collect and process data is the source of better understanding their requests, continually improving experience, and even anticipating questions and problems through predictive modeling.
Finally, AI allows for greater personalization of the offer to the customer and employee. The power and speed of computation and algorithmic techniques pave the way for more relevant individualization and greater adaptation to expressed needs.
But above all, it allows human interlocutors to dedicate themselves to more complex support and thus move up the value chain. In summary, artificial intelligence is one of the biggest projects of business transformation.
It will play a very important role in developing and enriching the customer-employee relationship. With this in mind, human resources, marketing and information systems departments have a definite challenge to overcome.
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