Digital intelligence is a term that has emerged in recent years.
It is also a hot concept after digitalization.
So what exactly is digital intelligence?
Is it an IQ tax?
Isn't it a concept that fools people?
Was it invented by a company to cut leeks?
In order to answer your questions, we will introduce topics related to digital intelligence in several issues, such as what is digital intelligence, why the life science industry needs digital intelligence, how to develop and implement digital intelligence, what stages and steps are needed for digital intelligence, which companies are suitable for digital intelligence, and the practical case sharing of digital intelligence that everyone must be concerned about.
The number in digital intelligence is data; Intelligence stands for algorithm - digital intelligence, which is the combination of data and algorithms.
Compare it to digital, and we see it clearly:Digitalization is the online use of offline activities and processes.
The process of digitization, if properly arranged, can result in a large amount of data. But digitalization itself does not rely on this data to function, and it is of little significance for the continuous improvement of digital systems. The digital system solves the process of starting from scratch, realizes the online business process, comprehensively leaves traces, and produces a large amount of data, but the basis for design and improvement is still based on human-designed processes, business needs and business logic.
That is to say,Digitalization does not solve the problem of how to continuously use the accumulated data to improve efficiencyTherefore, when you use the digital system, you often feel that the system clearly "knows" a lot of information, but it is still stupid and rigid to use, because there is a key factor missing in itAlgorithm. Algorithms can be understood as the processing, understanding, and application of data.
With algorithms, this massive amount of data becomes valuable. The most well-known algorithm is certainly the now well-known artificial intelligence, such as ChatGPT.
But algorithms are much more complex than ChatGPT, some are more complex, and some are simpler.
Digital intelligence is data + algorithm = intelligent application.
Compared with the digital era, the efficiency improvement and experience optimization brought by digital intelligence are simply from quantitative change to qualitative change - on the basis of the massive data formed in the digital era, the power of algorithms is superimposed to bring a new experience.
Say a few quiteTypical digital systemCRM, or the content approval system familiar to colleagues in the medical department, and of course, various OA systems within the enterprise, including enterprise micro and so on. The large amount of data generated in the process of using these digital systems may be mainly used to form usage reports for management's reference. However, it does not play any role in improving user experience and improving work efficiency.
WhileTypical digital intelligence tools, such as the familiar tools with the ability of "thousands of people and thousands of faces": Toutiao, Xiaohongshu, ** and so on. Just the browsing behavior data of each person can bring personalized content presentation or product recommendation through the superposition of algorithms. This not only brings a new experience to users, but also greatly improves the usage rate and duration of digital products of enterprises.
Here I used GPTS to automatically generate a comparison chart of digitization and digital intelligence, which is quite interesting, and I will share it with you:
Finally, I would like to summarize the difference between digitalization and digital intelligence in one sentence:
Digitalization is to make the past management process online, emphasizing functions and ignoring experience;
Digital intelligence is intelligent and future-oriented.
Okay, now that we've figured out the difference between digital intelligence and digitalization, let's take a look at why the life sciences industry needs digital intelligence in the next issue.
Before that, you can take a look at a successful case of digital and intelligent marketing:In 2023, Pulse Insights will help a multinational pharmaceutical company increase the content open rate of digital channels by more than ten times with digital intelligence capabilities!
Please stamp: ContextInsight helps a European pharmaceutical company achieve "strategy execution integration".