Unlocking Potential of Machine Learning; it's about Humans

Natali Delic, CTO, VIP Mobile

Natali Delic, CTO, VIP Mobile

There is still some mystification going on around machine learning. It is proven to be much more than a buzzword, but it is too often regarded as just another IT technology which brings opportunity for fast reduction of operational costs, primarily through replacing human with digital labor. Although the latter can have significant financial positive short-term effects, it is one of the biggest misconceptions in the top management level and a hurdle to be crossed in order to unlock the full potential of machine learning for building a better future.

Machine learning is not just a new technology which IT department is responsible to implement to improve organizational efficiency. It is a paradigm shift for the way of work and business that transcends technology innovation. It is in the essence of business innovation, and it acts both as digital transformation enabler and digital transformation driver.

As a major digital transformation enabler, the aim of machine learning is to:

• digitalize customer experience through real time processing of customer, product, services and network data, thus personalizing all interactions with customers and addressing their needs when and where they happen, in the way it fits them perfectly;

• improve efficiency of internal business processes through process automation, robotization, minimizing manual and repetitive work, building smart processes where real time decisions are made based on collected data;

• extend portfolio, either by improving existing products and services or offering new products which have embedded machine learning algorithms which ensure adaptability to changing environment–for example many of IoT and security solutions;

• build new business models, which is especially relevant for industries where abundant data exist, such as telco industry, which is probably one of the most data abundant industries and has an opportunity to reinvent itself with emergence of IoT and 5G, where implementation of machine learning will be one of the determinant success factors.

What is often forgotten, but is vital for executing digital transformation is human component. If machine learning is enabling transformation, people are those who should embrace, learn and implement machine learning. Thus, machine learning becomes the driver of digital transformation for individuals and organizations.

Reluctance towards new technology is natural in most of the organizations because it is perceived as a threat to the existential needs of an individual

There are several hurdles to overcome on that journey:

• strategy understanding,
• organizational resistance,
• individual fear,
• addressing knowledge gap and
• transforming way of work.

Explaining strategic implications and opportunities of digital transformation and particularly machine learning, what are expectations as well as consequences both in terms of competences needed and way of work, is one of the major prerequisites for minimizing organizational resistance and individual fear.

Machine learning is associated with making manual and repetitive jobs obsolete, thus reluctance towards new technology is natural in most of the organizations because it is perceived as a threat to the existential needs of an individual. To overcome it, business leaders need to show where the opportunity for growth lies, to advocate machine learning as means to free time of employees to take more important roles in overall business, and to support retraining of employees and their inclusion in building organizational machine learning capabilities.

Machine learning requires abandoning traditional corporation structures where one has prescribed procedures to address problems in advance, and where there is a clear line between different departments. It promotes the breaking of silos in organizations and introducing of new ways of working where non-IT professionals collaborate with data-IT specialists. It requires the forming of autonomous teams addressing specific business problems, thinking more from the perspective of research and development, experimenting with different algorithms and accepting failure as another opportunity for learning.

Such competences as those of data engineers, data business architects and data scientists are becoming the most critical ones since they are hard to find and time consuming to build, so organizations need to work in two directions to overcome the knowledge gap–both by attracting external talent and retraining and retaining existing talent.

Artificial intelligence powered by machine learning algorithms will enhance human work and decisions to ensure survival and successof businesses. But there are unique skills like negotiations, empathy, problem solving, intellectual curiosity and creativity which will be needed in order to ensure that those algorithms serve the purpose in an ethical and secure way. That leads to the need for continuous enhancement of those algorithms by humans so the coexistence of human and this new type of labor, digital labor, will need to be ensured in organizations of the future. Hence, the new way of work requires significant organizational and cultural shifts in organizations.

The entire digital transformation rests on the ability of organizations to transform their systems and processes, to digitalize their interactions with customers, make them smart and intelligent through the application of new technologies. It is about using those new technologies where machine learning is a major power engine making it possible to continuously adapt to changing circumstances and thus ensure business sustainability.

But in the center of this transformation is a human being. Success of digital transformation will be determined by the ability of business leaders to create an environment in which individuals will be able to continuously adapt to changing circumstances and learn not to compete with machines but to coexist with them and thrive together.