Three Digital Drivers and Their Impact on Business Resilience
STORY INLINE POST
Digital transformation is a fundamental element in the DNA of companies. No matter where they are in their transformation, they are aware of the change that digitalization is creating in their industry and on the perspectives of partners and employees.
In fact, digital transformation is taking place at the point where people and technology intersect to give way to a better, smarter and more agile business that can anticipate customer needs, market changes and global events.
From artificial intelligence (AI) and machine learning, to the cloud and the Internet of Things (IoT), organizations leverage these innovations and apply them according to their reality and needs, and also based on their mission, vision and business objectives.
We are in the midst of an era where business leaders need to communicate and collaborate at all levels to ensure that they are aligned and engaged. CMOs, CIOs, CFOs and the CEO must work together to determine where the company is headed, why, and what is the best route.
One of the three key factors driving digital transformation is the change in the way employees interact with each other, and the roles they play in creating digital intelligence. The work of the CFO, the CMO and the CIO is changing as companies realize the collective value of shared insights.
At the same time, new roles are created, such as the Chief Data Officer, the Chief Analytics Officer, the Chief Digital Officer or the Chief Talent Officer, who work hand in hand with the C-suite in the digital transformation process.
Digital transformation is also based on an intelligent platform that integrates key technological components. This second driver for digital transformation combines different innovations, which are grouped into four areas to define the best route that an organization can take.
- Data management is an essential component of any digital intelligence platform that allows you to have a reliable strategy and methods to access, integrate, clean, store and prepare data for analysis.
- Analytics, including predictive analytics, helps to give purpose to the huge numbers of words and numbers that are collected.
- For example, they can handle a few hundred words at a time, while artificial intelligence can handle hundreds of thousands and process millions of interactions per minute.
- Make decisions in real time. Digitally intelligent companies are making decisions supported by artificial intelligence and hyperintelligence. When they allow machines to decide or process, decisions are made much faster from real data.
Meanwhile, the COVID-19 pandemic, the third driver, boosted digital transformation in virtually every industry. In a matter of days, organizations had to accelerate the adoption of technology resources, such as the cloud, collaboration tools, cybersecurity, video conferencing, and virtual workspaces, which allowed them to continue operating and be profitable.
They also strengthened their e-commerce initiatives and developed applications and portals that were intuitive for their customers, and coordinated with virtually every component of their supply and distribution chains.
Resilience to Face the Present and the Future
As a result of a disruptive event, such as the pandemic, and the resulting digital transformation, organizations also developed better resilience.
Resilience allows them to be better prepared for the future, whatever direction it takes. Traditionally, organizations strengthen their resilience by creating business continuity and disaster recovery plans. While these may vary in scope and complexity, they are the main mechanism to keep the organization operating until the crisis passes.
In today's context, to be truly resilient, an organization needs to have the ability and capabilities to move forward despite unpredictable events. Bad things are going to happen, no doubt, but the difference lies in how it reacts to them.
Resilience adds the ability to move with speed and agility and take advantage of human talent, operational processes and organizational infrastructure. To overcome a crisis, it is also critical to integrate data and analytics into companies' decision-making processes, so that they become an integral part of building resilience.
A relevant attribute of a resilient organization is understanding normal fluctuations, growth and contraction, as well as demand, whether it is in government, healthcare, retail or manufacturing. In this sense, artificial intelligence models embedded within machine learning algorithms can set off alarms to help identify impending crises, or at least in their early stages.
Therefore, determining how best to prepare for the next crisis is high on the agendas of business leaders. And some of the definitive answers will be found in data because that is what all digital processes produce. With tools to clean, govern, and protect data for analytical processes, every strategic or tactical decision can be made with the confidence that resilience gives the organization.
Resilience and digital transformation are consolidated as a determining factor for companies to emerge stronger and more competitive from an unprecedented crisis, and to continue to prosper in the future.