When considering economic sectors, we usually refer to five main zones. The first sector includes natural resource industries such as mining and farming. The secondary sector includes manufacturing, construction, and engineering. Retail, entertainment, and financial institutions fall under the third sector, education and research makes up the fourth, and, finally, the fifth sector is government, regulation, and industry high-level management.

When it comes to investment sectors, the categories are communications, energy, technology, and health care. Understanding the unique features of each sector is key to making smart decisions regarding market movement and investment.

What do we mean by Sectors?

Sectors are parts of interlocking systems. They may share goals and even similar processes, but their actual methods will be different. When trying to succeed in a certain sector, it’s imperative to achieve a balance with all the different components functioning in that sector. It’s like winding a grandfather clock-both weights must be adjusted for it to keep accurate time. Consequently, if you are trying to overhaul and improve a particular sector, you need to understand the basic structure of the system-how all the processes work with and against each other and what reciprocal effects can result from changes within the sector. This is known as a traditional one-sector approach.

Unfortunately, the one-sector approach is no longer practical for the modern world. One-sector approaches fail because they don’t consider that inputs from other sectors are constantly changing. Not recognizing involuntary inputs from other sectors means that any plans are left vulnerable to unknown overall effects. 

Many organizations are starting to recognize the need for dynamic inputs, so multi-faceted approaches to sector analysis are the new philosophy. This method means examining lots of various inputs in several contexts, giving your organization the ability to plan for many possible scenarios and anticipate challenges in advance. This new approach has worked successfully for many international companies and allowed them to survive the sectoral competition. And, unfortunately, many companies that didn’t adapt have ended up failing or downsizing significantly.

Kodak, the king of photography, is a great example of this. Since they were concerned with only their sector, they failed to see a threat developing from the mobile phone markets. Now cameras on mobile phones are the primary photographic tool on the market, and Kodak’s influence is severely diminished.

Many international companies managed to escape unpleasant “surprises”, and so they successfully tolerated sectoral competition. As for those who failed to consider the influential rise in inputs from other sectors, they either disappeared or, at best, failed to compete and declined.

Nokia is another example. It used to control the mobile phone sector but failed to meet the challenge of Apple’s new smartphones and quickly fell into relative obscurity.

Both these companies, titans in their specific sectors and seemingly untouchable, failed by not taking into account the influences from other sectors. Subsequently, they lost the competition because they didn’t see where the competition was actually coming from. Kodak failed to see intersectionality, and Nokia failed to see a crucial shift in its own sector.

Full awareness of not only your own sector but all other, connected sectors has become essential to functioning in a global market. At RSRS we use the latest data collection resources and tools to see as much as we can of the Big Picture.

The need for a comprehensive Cross-Sectoral Approach armored with modern technologies

Working with a cross-sectional approach, one that is comprehensive in its scope and vast in its data reach, is not merely a fancy trend. It’s answering an urgent need in the world markets for data analysis that utilizes social and economic factors to anticipate influences and interrelationships. With a panoramic, holistic approach like this, we can design an implementation strategy that sees sector outputs as dynamic, instead of devising mono-sector outputs that are simplistic and often inaccurate. After all, in the future of globalization, we do not exist as islands. Other fields and industries affect our futures on both a macro and micro scale, and the potential effects are only accelerating as the world becomes more integrated.

It used to be hard to get real information on sectors outside your particular scope without seeking out a specialist or combing through trade magazines. The advent of social media and the internet, along with its almost omniscient control over cultural status, has made data collection an entirely new game. Almost anyone can learn about anything—immediately and without limit. Not only has this changed culture forever, but it’s also shaped a generation that thinks in terms of networks and easily connects various concepts.

One of the characteristics of a village is that the whole population of the village knows every member very well. This can be beneficial when you’re creating bonds and building communication between members. But it also leaves members open for harsh, direct judgment. The world is indeed one village now, and we know more than we ever did that our social, economic, and environmental interests are inextricably tied together. What happens to one person happens to all. This interdependence is the key feature of globalization.

In today’s digital age, where the part is affected by the whole and the whole is dependent on the part, no event is local. Every event takes place in a circle of mutual and accelerating effects. Possession of information is no longer a luxury-it’s an essential part of survival and a key factor for sustainability. And it isn’t just about who has the data—it’s about who uses the data. Understanding data and using it correctly is the cornerstone of strategies that succeed and have the potential to grow.

Any expert today can tell you that the exponential proliferation of data – the wealth of information available for any field or industry – has thrown the predictions off. No matter how talented your planners are or how diversified the inputs they plug into potential scenarios, they can’t possibly utilize the most current set of changes; all the unexpected events that can throw off the progress and implementation of planned strategies. We see this not as a structural fault in the plans but a consequence of attempting to simulate multiple output scenarios while lacking what we call dynamic inputs.

Then, how do we design strategically? First, you must be constantly using the most up-to-date information at any given moment; making real-time inputs to your scenarios. This crafts your static plans into highly flexible, dynamic ones instead. And that helps you see the corrective steps needed to stay competitive in your field, whether that’s selling shoes globally or mapping food deserts.

Luckily, the technology that helps to make that happen currently exists. These emerging technologies have been developed to create dynamic inputs worthy of the Digital Age/Globalization fast track. This includes data mining, machine learning, and artificial intelligence. All of these are designed with the capability to handle exponentially growing data sets of information, quickly and efficiently; delivering you plans grown from proactive reactions—plans that can be modified quickly to meet the changing data.

There is an urgent call to obtain deep, comprehensive insights into the connected environments that feed into any field. But collecting cross-sectional data is useless if we fail to use the emerging technologies we mentioned above to turn that data into a full, complete picture. Our goal is to create sustainable solutions and stay competitive in an increasingly interactive world. This requires not just the ingenuity to see a wider view of the landscape, but the foresight to use technology that can optimally turn that data into useful strategies.