How to Create an Intelligent Company

How to Create an Intelligent Company

Nowadays, companies are besieged by information and the possibilities of new IT solutions. With the rapid advancements in information technology and high speed Internet, companies now have access to huge amounts of information, processing and sharing systems regarding customers, their demographics, and their online behavior across all touchpoints on the buyer’s journey. The advantage of access to so much information is not just in the form of increased revenue and developing long-lasting customer relationships. It is also about developing sensitivity to warning signals, which would allow companies to prevent or mitigate disasters.

So far, companies have improved their practices with respect to capturing greater amounts of data. However, the prevalent norm is that company employees pass this data on to decision makers en masse, leaving it to them to sift through it and come up with relevant data upon which decisions could be taken or to a company process or person to do the same. Hence, although they’ve gotten good at collecting data, most companies have yet to develop the ability to process this data and generate actionable insights which they can share with decision makers, processors, and their clients. 

In a study conducted by the Hackett Group in 2006, finance organizations that were categorized as world-class generated reports that were far less and shorter (691 for every $1 billion U.S. in revenue), as compared to companies that were not considered world-class. These companies generated 1,474 reports for every $1 billion U.S. in revenue. The former category of companies took their time in developing their reports and ensuring that they contained information that was critical and relevant.

The idea is that there needs to be a focus on intelligently sifting through the massive amounts of information that are available to a given company, to retrieve knowledge that is actionable, and to use effective processes and tools to share and take the actions effectively. Hence, there needs to be an increased focus and knowledge on the analytics strength and new tooling of the average modern company.

The idea behind an “intelligent” company has evolved as a reaction to this Age of Information that we find ourselves in. On the one hand, there are massive amounts of data and rapidly evolving technology and on the other hand, there is the change in our mindsets that is not adapting to this availability of information with the same rapidity. Hence, it is appropriate to say that we are “drowning” in information. The intelligent company is the company that essentially ensures that the data it collects is translated into knowledge that can be acted on, as well as using the relevant technology to achieve this objective, organizing all into a new business model.

So how do we create an “Intelligent Company”? One that takes advantage of “all that is new”?

Key elements in making a company “intelligent”

For a company to shift towards becoming an intelligent company, it needs to have more than just the technology to enable the transformation. There is a need for significant changes in the way employees think about data and how it can be effectively processed and acted on. Following are business domains that van Loon and Monaci believe need to be considered. 

Design Thinking 

Design Thinking is one of the ways in which this change can be brought about. Design Thinking is part of a broad methodology that amalgamates elements of imagination, intuition, holistic reasoning, and logic to explore all the probable solutions for a given problem. It includes the identification of all unarticulated needs expressed by a consumer. After the identification of the needs, the team creates solutions that address all needs and end up creating the “wow” effect. The solutions are generated creatively and analytically as Design Thinking is more solution oriented than being problem oriented. 

Reaching a feasible conclusion is frequent in Design Thinking. The risk inherent within innovative solutions is minimized by transitioning users through numerous prototypical solutions that give leverage for learning, testing and completely refining the ultimate solution. Instead of going through historical information, insights of all unmet customer needs are collected through real time experiments. 

Data 

Data is frequently used by numerous organizations to find and extract information that can be used to assist or help in setting strategic plans. The efficiency and utility of these strategic plans goes on to define the future of the organization and how it fares among the challenges of the rising competition. Having understood the importance of data, the impact or setback that can be created through the use of low quality information is indeed intimidating and threatening to think of. In fact, it is believed that bad data ends up costing the U.S. more than $3 trillion per year. The data you are using should be flawless and should work in tandem with the Artificial Intelligence (human and Artificial Intelligence) mechanism. Both AI and good data work hand in hand to assure the success of your analytics. 

Successful organizations have been using data they gather from clients to follow them over multiple channels and to send them messages personalized for their attention. Current technologies and government policies allow this to take place, but after the enforcement of new laws in the European Union, consumers will have control over their data. 

Technology

 The past few years have seen an increase in the technology that can be implemented by an intelligent company. Monaci and van Loon believe that the following factors or advancements in technology promise enhanced performance to those companies that adopt them in the right way. 

IoT: IoT or the Internet of Things combines all the technology and sensors gathering useful information from the “field”, analyzing and storing it at the edge (locally) or centrally, to help in the optimization of the business processes, and model. IoT can change industrial production and how it works for the coming years, as it will have a big impact on processes across many industries. 

Big Data Management and Analytics: Managing the data that organizations have is an integral part of the recent digital transformation domains. Only after sifting through the hype and recognizing nuggets of insight and core understanding of the new business model will organizations be able to leverage these new competencies to their advantage. 

Machine Learning and AI: Artificial Intelligence (AI) is a technology that works similarly to the concept and functionality of our brain, and tries to automate reasoning within certain boundaries. It augments humans and supports our capabilities to process a lot more data that we can imagine to process at a given moment in time. 

Data Governance: Data Governance is a concept similar to that of data management. With the rise in the concept of hybrid data management, the accessibility of data for repeated usage has significantly increased. Data quality and communication gaps can hinder the decisions taken as data flows through the organization. 

Blockchain: Initiated through the concept of cryptocurrencies, blockchain is indeed the future of how information is distributed between parties. Smart contracts are one interesting innovation that they bring. Smart contracts can enhance the utility and feasibility of real life contracts, through the benefits that they offer. 

Business Models 

Source: SAP on HPE.com

There are countless innovative global trends that have signaled changes in the way that companies create their business model and operate their businesses. Instant gratification is anticipated, hyper personalized products are leading the way, companies and the individuals working with them are operating 24/7 in a more authentic manner, and machine to machine artificial communication is becoming accepted and widely adopted. These changes, coupled with a few other trends, are driving companies to rethink their business model and how they do business.  

The new business model is based on: 

  • Outcomes and results 
  • Expanding into new markets and industries
  • Shared economy 
  • Networks 
  • Digital platforms 
  • Digitization of “all” products and services 
  • Competing as a whole ecosystem 

Innovations in the business model require a completely new way of contemplation, based on the digital strategy, talent, people, and technology. Regardless of where every company stands in adopting the model, the digital transformation is the future that just cannot be avoided. 

About the Authors 


Andrea Monaci is the Marketing Director for Cloud and Service Providers at HPE and a founder of Cloud28+, the B2B Eco System for Digital Transformation. 

Connect with Andrea on Linkedin and Twitter to learn more about B2B Eco systems. Follow Cloud28+ on Twitter and Linkedin



If you would like to read more from Ronald van Loon on the possibilities of Big Data and the Internet of Things (IoT), please click “Follow” and connect on LinkedIn, Twitter and YouTube.

Vijay Gunti

Building SAP Generative AI , SAP Knowledge Graph | Single and Multiple Agents for Enterprises | Mentor | Agentic AI expert | Advisor | Gen AI Lead/Architect

7 年

In the technology Stack Augment Reality/Virtual Reality/ mixed Reality also plays a vital role

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David S. N.

Cursor ai|C#|Web API|Python|Powershell|SQL|Flutter|OpenAI|LangChain|AI Agents|Dart|Chroma|Pinecone

7 年

Rule number 1 : value the customers time rule 2: don't waste the customers time on error or lack of respect of their time. Provide value and reduce waste of time

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In our society we are making massive progress on the tooling part. We also see big evolution on today's society in general. What we are neglecting is on how we are organising ourselves around the scale of change. We do still have this "dogma" that people need to be "controlled" and "guided" in their professional lifes. We have implemented so much rules and procedures that this becomes a burden to creativity, and creativity might be sourced out of having insight on data. These insights do not come from the blue sky but do come from identifying the relations between the data (which, for me, is more important than the data itself, but that is a separate subject on it's own). And how do you see relations between data elements? In short it is by building relations with other people who might give you other perspectives. This requires that you, as a person, do have the environment where you are allowed to be creative and not only following rules.

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David S. N.

Cursor ai|C#|Web API|Python|Powershell|SQL|Flutter|OpenAI|LangChain|AI Agents|Dart|Chroma|Pinecone

7 年

The socratic method of questioning is Aporia thought processes essential to the organization. The new thesis is program everything. Asynchronous state programming, state based languages, and passive parallel processing are making everything connectable. What is relevant is solving the right problem. How is this possible without thinking about processes happening in the system. It is critical to form thoughts or frameworks about the data and looking for trend, classification, and meaning. Data supports the ideas. Just collecting data is worthless because The empirical method of thought is often without context. Mountains of data can be collected and produce zero value without a context. Without context the data is meaningless. Therefore, data analysis is about the process of thought or discovery and that is call philosophy. More programmer need to become philosophers of data

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Didem Gurdur Broo

Assistant Professor in Cyber-physical Systems | Future Strategist

7 年

This is a great article Ronald. Thank you!

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