Customer Reference
"Graduate Diploma in Digital Strategy and Leadership offers a first-rate training...”
Andrus Kuus and Jan-Henrik Svensson
Executives need to understand which emerging technologies will impact their business environment and how to lead digital transformation.
See programs Solutions for organizationsEverything related to digital transformation is somehow linked to technical know-how. It is a fact that traditional leadership skills are no longer enough in business management, nor in meeting future challenges. Everyone of us needs to understand and know more about different tools and the technology related to them. We cannot lead what we do not know.
Our training programs equip both senior decision-makers and specialists with the skills and competencies needed to build a more proactive digital strategy to utilize, develop, and commercialize digital technologies and data, and discover new ways to create value.
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At what level should every leader and expert understand the applications, data analytics and the possibilities of quantum computing, or the increasing robotization of AI in different organizational functions? Here at Aalto EE, we have outlined these different levels of learning as follows:
With the above breakdown, we have tried to signal that there is a point of development for each task and level. The need for skills in Python or R programming is not defined by how long you have been in a position, but by the leadership challenges you will begin to face as the use of code increases.
However, our perspective is always very business-oriented, looking forward from the perspectives of management and the opportunities for strategic level management. The network created by experts from Aalto University and other top universities enables the customer to connect with the results of cutting edge research in artificial intelligence, for example.
We have defined the different areas of expertise in technology and knowledge intensiveness as follows:
We have identified top experts in our network for each of the above-mentioned areas. In addition to the latest research information, we utilize the most up-to-date applied knowledge provided by the business network. We organize our programs in cooperation with the best experts in their field.
In the era of platform economy, data serves as the currency of the future on business-to-business platforms. The technology choices of the platform economy are therefore increasingly strategic and affect the ecosystems that are formed.
Aalto EE has access to Aalto University’s expertise in key AI technologies such as machine learning, computing logic, and data science. Aalto University is a key player at the Finnish Centre for Artificial Intelligence (FCAI) and in the AI projects launched by the Finnish government. We select the most suitable trainers for each program from this high-level group of experts. Aalto EE's programs include case and keynote speeches on Finland's leading companies and early adopters of the latest technologies.
We live by knowledge, quite concretely. According to traditional belief, people have five different senses and sensors that receive and transmit information at a tremendous rate. The brain receives 10 million bits of information every second, by conservative estimates. However, our brain can only handle about 30 bits per second! In other words, people have a built-in capacity to extract the most essential pieces from the information and make use of them. The same phenomenon is also taking place in society, organizations, and business in general. There are unimaginable amounts of information and data available, but we only utilize a fraction of it. We could do much better if we wanted to.
In analytics, utilization of data is typically divided into three categories: descriptive, predictive, and prescriptive analytics. Descriptive analytics aims to present what has happened based on the data. The general presentation method is different reports that classify and categorize data. Business Intelligence (BI) is a task often focused on descriptive analytics, typically reporting information from the enterprise resource planning system (ERP) and the customer relationship management system (CRM).
Predictive analytics aims to build models that try to predict the future and the likelihood of different scenarios based on data from past events. For example, a typical use is to predict future purchases based on the customer's previous purchase history.
The aim of guiding analytics is to make recommendations for the next step. These recommendations are often based on predictions and probability calculations for alternative choices. Optimization is often discussed in the context of guiding analytics. Optimization refers to the evaluation and selection of the best possible measure, especially when there are a large number of options available and they are difficult to compare. The factors related to production control, such as inventory turnover, are a characteristic example of optimization.
Data science specializes in handling the information age and large amounts of data. Data science studies the dependencies and regularities of data masses of different sizes and tries to create explanatory and predictive models. The aim is therefore to gain an understanding of the past, the current situation, and possibly the future.
Data science is a recent term for which, however, there is no single well-established definition. It is used to describe workplaces and degrees which include data collection and the aggregation, cleaning, interpretation, and visualization of this data. It has also sometimes been used to refer to a combination of statistics, programming, and industry expertise.
Decisions are made in every organization and job. Although the intuition provided by experience is useful, decisions will be based on data and knowledge more and more often in the future. Decisions based solely on one's own feelings are risky due to possible errors and various changing circumstances, so active data collection and analysis provide added value and certainty.
Aalto EE supports every expert's and manager's journey in adopting data skills. Data-based business does not mean outsourcing data and skills to the IT department, from which service is requested as needed. A sufficiently in-depth understanding of the prerequisites and possibilities for utilizing high-quality data must be internalized by each employee in order to achieve the culture required for data-based leadership and management. A typical and time-consuming problem is low-quality and inconsistent data, which significantly slows down or, in the worst case scenario, even prevents data from being utilized.
Data-controlled business is becoming the new standard in a rapidly changing world. At the same time, new industries, such as the mobile gaming industry, are already very data intensive. If you do not run your operations in the future with data, you risk becoming a prisoner of the past.
When talking about data masses that have grown exponentially and come from new sources, artificial intelligence will inevitably become a part of the discussion. Artificial intelligence will quickly transform all aspects of society, opening up new opportunities and creating new solutions. If an individual or an organization wants to succeed in the competitive environment of the future, he/she/it must acquire both new technology skills and a clear understanding of artificial intelligence.
The key features of artificial intelligence are, in particular, the ability to learn and adapt. According to traditional AI specifications, the definition of an AI’s “intelligence” is precisely its ability to act accordingly to each task and situation in a sensible manner. The definition of artificial intelligence is usually made by dividing it into two categories: narrow and strong artificial intelligence. Narrow AI works in limited tasks, but without awareness, will, or understanding of the world outside of the tasks assigned to it. Strong artificial intelligence, on the other hand, has a broad understanding and has a human-like consciousness. Narrow AI is already being utilized, for example, in the testimonial systems of various streaming services, in the analysis of long contract texts from law firms, and in the form of life-facilitating voice-controlled assistants (e.g., Apple's Siri, Microsoft's Cortana, and Google Assistant). Strong artificial intelligence only occurs in sci-fi films and in very long-term plans. People are an obstacle for the widespread use of artificial intelligence. Lack of regulation, growing security and privacy problems, and a lack of understanding of artificial intelligence limit the large-scale use of artificial intelligence. Aalto EE strives to contribute to the development of the artificial intelligence era, especially in the last one of these points: by correcting mysticism, fears, and misconceptions.
In addition to artificial intelligence, other new technologies such as blockchain technology, 5G, quantum computing, robotics, IoT, as well as AR, VR, and MR, i.e., virtual, augmented and combined reality,are here to stay and also affect the operations, results, efficiency, and reliability of organizations. New technologies are changing processes, work tasks, customer relationships, the environment, and society as a whole. Recent advances in sensors, algorithms, data processing, and artificial intelligence are shaping robots into more independent operators, which significantly increases their usability.
We need expertise and understanding of new technologies and their purpose, opportunities, and consequences at different levels of the organization. Aalto EE also utilizes Aalto University's world-class expertise as a developer of, expert in, and trainer for these new technologies. Through our new technology-focused programs, you will learn to better understand how technologies work and how the opportunities associated with them are revolutionizing the business environment in practice. Through our programs, you will also be better equipped to lead technology-enabled teams and make technology-related investment decisions. Through our training, we support organizations and companies in the translation of new technologies into concrete benefits for businesses, and in leading innovation more effectively, both now and in the future.