Digital Transformation and the Future of Work

Digital Transformation and the Future of Work
A digital and agile organization can organize much more effectively – engaging the innovative talents of employees and improving their morale.

Digital transformation is impacting all aspects of our lives. A recent survey by Intel revealed 63% of employees have no longer a traditional office “fixed desk” work environment. About 43% worked from home several days a week. Digital technology is transforming the very nature of work itself: the way we innovate, connect, interact and produce.

There are three trends that are having a profound impact on the future of work.

  1. Internet of Things and The Future of Work: As connected devices are becoming more and more pervasive, the relationship between humans and connected machines is going to profoundly affect the working environment. There are two reasons for this. As smarter devices get connected to the Internet (aka IoT, IoE, M2M, IIoT, etc.) they can start to assist workers in accomplishing their objectives. This is an important phase in automation – that started with the industrial revolution. Thus we will have humans and intelligent connected devices, including robots, working harmoniously to accomplish business objectives. The smarter these devices get, the more proactive they will be in helping us carry out our tasks. Robots are already replacing humans in predictive and repetitive tasks – such as distributing mail in an office.

  2. Big Data Analytics and the Future of Work: The second reason has to do with data - or more specially the intelligence that is extracted from the data. We are witnessing an explosion in the amount of information that we are generating. But that does not mean we are getting wiser or acquiring “knowledge.” Connected devices will only accentuate this trend. There are other sources of vast amounts of data, such as Social Networking sites or the transaction data within enterprises. Through proven as well as modern analytics techniques, we can now extract the hidden knowledge of the data: mine it, learn from it, and then use it to adapt accordingly. This will be – and already is – one of the most promising trends that will transform our working environment. Thus we can combine the knowledge of the experts with the knowledge gained from data – including those that are generated by connected devices – to improve and transform the work environment. This approach could be used to assist workers with knowledge, proactively helping them carry out their tasks efficiently, intelligently, and on-time.

  3. Transforming the Digital Enterprise Organization for the Future of Work: The third trend is the most promising but also the most difficult to realize. It is organizational and cultural transformation. The traditional top-down pyramid and functional unit organization structures are tired and passé. They do not inspire innovation or digital transformation. Emerging models include holacracy (vs. bureaucracy – and we know how well that functions!). Challenging traditional management around circles for specific projects and objectives is both liberating and transformational. Employee empowerment has been elusive and hard to achieve within a rigid hierarchical organization. A digital and agile organization can organize much more effectively – engaging the innovative talents of employees and improving their morale. The idea of challenging hierarchical structures, removing bosses (or replacing them with “mentors”) has been around for a while. The need to quickly change and adapt in digital enterprises is compelling them to re-consider their rigid structures. It is already happening in several Silicon Valley companies.

All this needs a context. Business software itself needs to become much more adaptive to change to support workers. In particular, this refers to how more complex tasks are automated and improved using a digital innovation platform that includes intelligent business process management, Dynamic Case Management (DCM), and Analytics for Next-Best-Actions, including Big Data analytics.

This piece was previously published on LinkedIn.


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