digital transformation, a long-term phenomenon
Digital transformation is defined as the use of available digital technologies to improve business performance and make our daily lives easier.
Since the pandemic, digital transformation is said to be on the rise. But the phenomenon is not so recent. Let's remember the spread of the personal computer in the early 80's, the explosion of internet use in companies thanks to broadband from the 2000's or the birth of social networks, which have totally transformed our social and professional life since 2010.
Finally, the COVID crisis in 2020 has only put a piece in the machine and accelerated an already well established trend.
digital transformation: from a forward-looking strategy to a survival strategy?
It is a certainty, the world is changing! In order to keep up with this change, we must give significance to the words "transformation" and "digital" since "digital" alone, without the focus on transformation, could quickly lead to failure.
So, it is not a matter of digitizing a company to follow the trend. Instead, we need to start asking ourselves a few questions: "How can I make my company evolve to keep up with the market direction and meet my customers' requirements?", "Why is digital essential to develop my business?", "Beyond deploying the latest technologies in my company, how can I get more profit?"
what are the challenges of digital transformation for companies?
Digital transformation raises a series of issues around human, technological, economic and social responsibility that should be expected. As we have recently experienced, digital transformation is a real vector for the development of organizations, and a symbol of agility and resilience in case of crisis. Far from being just a theory, the numbers speak for themselves:
The World Economic Forum estimates that the digital transformation of companies and industries around the world will be worth more than $100 trillion by 2025.
But the big question is how to manage this digital transformation and what are the key success factors. New technologies such as artificial intelligence, data, RPA, robotics, etc. are considered the pillars of digital transformation, contributing positively to organizational productivity and economic growth of companies.
data, an essential pillar of the digital transformation strategy...and not only
Large companies that will use Big Data will record an additional annual gain of 1.2 billion dollars compared to those who do not use it
So, much more than technology, data is a goldmine for companies and must be put at the heart of their digital transformation strategy.
Collecting accurate and detailed information in compliance with the law will be one of the major challenges in the years to come. While respecting the GDPR, it is imperative not to delay the implementation of data mining projects, but on the contrary, to make the data capital bear fruit and use it to better develop your company.
There are many sources of information on how to focus on the diversity and relevance of the information collected within the company. First, all company information systems have exponential amounts of data generated by ERP, CRM and other software.
According to the McKinsey Global Institute, the amount of data in the world doubles every three years. Faced with this fact and this challenge, companies will have to evolve in new ecosystems and integrate new dimensions that integrate the diversity of sources, origins of data, different uses and tools, and associated algorithms. Today's companies must process, manage and protect data continuously and in real-time before exploiting and sharing it. To better leverage this data and turn it into value, companies need the right tools and skills. Collecting and storing data is not enough. To further improve the value generated, optimize processes, etc., you need to know how to use it, interpret it and extract the maximum amount of information.
Big data allows companies to process huge amounts of data and extract very sophisticated statistics. Data from disparate systems can be processed together and linked to reveal previously unseen information. Analysis becomes more granular and is linked to very specific areas, from mastering all the systems that make up the business, to knowing exactly what the customer's habits and needs are. All these analyses, which can also be done in real-time during data collection, allow you to improve the functioning of your company.
Accompanying the digital transformation of your workforce is essential to achieve this because commitment counts. New jobs are emerging in the company, and it is imperative to put the different actors at the center of this transformation.
artificial intelligence: a structuring technology for efficient decision-making systems and task automation
Artificial intelligence is one of the most promising fields of research, but it is also one of the most complex. Each discovery is intended to help salespeople, managers, etc. in specialized, time-consuming tasks, but also opens up new horizons. According to a study by HUB Institute: "Today, 29% of workplace tasks are performed by machines or algorithms, but by 2025, AI will influence more than half of employees' actions”.
Also, employees need to be trained for this revolution. This means rethinking the content of work with AI as the main focus of productivity. People within a company can work together to think about what to replace and what to do with AI. The more involved they are in organizing and reorganizing the technology, the more important and constructive the human-machine connection is seen as.
Far from the image portrayed in science fiction movies, artificial intelligence is a creation of human intelligence to shape machines with human thinking capabilities. Through AI, machines are equipped with many capabilities, such as perception, understanding and action. The information provided allows companies to (1) build effective decision-making systems and (2) automate tasks to optimize quality and service delivery.
1. decision-making system
By definition, a decision-making system is a system that uses past activity to derive lessons that will be applied to future activity. To be useful, a decision-making system must have four objectives: to better understand the environment, to focus on objectives, to organize or reorganize and to implement appropriate action plans.
The data collected by your company will allow you to better analyze the competitive landscape thanks to Machine Learning algorithms. The objective of this line of research in AI is to give computing machines the ability to understand data. It is this metadata that allows tasks to be solved after processing, notably through automation. Machine learning thus enables the design, analysis, optimization, development and implementation of operational work methods.
2. task automation
Applying artificial intelligence to your business can automate repetitive tasks that are typically performed manually. Analytics and CRM platforms actually incorporate machine learning algorithms that search for useful information for their customers.
Automating tasks improves the productivity of a company. It saves about 30% of time and allows different teams to focus on higher value-added tasks that require the mobilization of human intelligence alone.
The automation of tasks is not only based on AI but also on RPA.
rpa: a technology in the intelligent automation toolbox
Many companies have already implemented RPA - Robotic Process Automation - solutions to optimize existing processes.
The automation market is expected to reach $12 billion by 2023.
Smart automation is the most popular concept. Integrate all intelligent technologies to automate processes, including robotic process automation (RPA), digital process automation (DPA), intelligent process management (iBPM) and artificial intelligence.
It is important to consider RPA as one of the technologies in the intelligent automation toolbox. In the short term, it allows for the automation of tasks performed manually by employees. In the long term, implementing RPA allows you to approach the process from a completely different technical perspective. So, considering a different approach like RPA allows, among other things, to standardize, simplify and improve all processes within the company.
In conclusion, RPA has become a major player in the field of intelligent automation. However, it should not be used alone. It is important to proceed step by step and ensure that your intelligent automation projects are well supported by the company's digital transformation strategy. The path to effective digital transformation requires the right set of tools that not only connect systems, but also infuse them with intelligence and rethink entire processes to revitalize them and make them even more relevant. This transformation can be implemented via low-code platforms that allow organizations to go beyond traditional automation. More and more companies are leveraging the potential of low-code to implement intelligent automation capabilities. This enables rapid transformation of critical processes while meeting IT requirements for security, architecture, testing and maintenance.