Digital transformation is a very popular word in recent years. Although "digitalization" is very hot, the core of understanding digitalization, knowing what enterprises are turning and how to transform and upgrade is to understand what is the opposite of digitalization. Only by clarifying the opposite side of a thing can the value of this thing be clarified.
As far as "digitalization" is concerned, personally, its opposite is "experience".
As far as enterprises are concerned, although there were systems in enterprise management in the past, no matter how the system was determined or how it fell, the core was people, with the focus on middle-level managers. Therefore, our expectations for managers are often people who have been in business for many years and have seen the world, because only with more experience and knowledge can we have a more accurate judgment on some difficult things and know what to do when encountering big waves. This is the value that personal experience brings to the enterprise.
But the problem is that the business environment in the industrial age changed very slowly in the past, so it is feasible to manage enterprises through human experience. However, with the advent of the Internet era, especially the popularity of the mobile Internet, the speed of business model evolution has suddenly accelerated. The rise and fall of an enterprise may only be a few years, and some experiences that were right in the past may be wrong today. In particular, the new track, new tuyere and new blue ocean that we admire are difficult to judge simply by experience.
This involves a very critical issue, that is, although the experience is good, the experience is lagging behind, and the business model under the Internet attaches great importance to foresight. This "series connection" reveals the difference between the two ways of thinking.
The advantage of digitalization is that it can tell us which business models are worthy of attention and which areas can be tapped through data. For example, multi-dimensional analysis, transaction attribution and other methods in big data all give us early warning through data at the first time when some signs appear. Through the interpretation of data analysts, we can know whether this is an opportunity or a disaster for the first time, and we won't wait for the window to pass for a long time before we know.
But experience is not important? No, experience is equally important. Digitalization is not an "either-or" relationship, but allows enterprises to have two abilities at the same time, sum up the past through experience and embrace the future through data.
Therefore, we can sum up the core view of "enterprise digitalization", that is, "describing enterprises through data and guiding business through data". To put it bluntly, enterprises can know their current situation and where their optimization points are through data, and at the same time clearly see what is happening and what will happen in their business.
| 0x00 1 What should be done in enterprise digitalization?
Although the forms of enterprises vary widely, such as ToB, ToC, ToG and so on. The essence of business has not changed, one is called "value added" and the other is called "reducing costs and improving efficiency". Therefore, two problems can be clarified through the data: one is what our current business is like, whether there is room for growth in this field, whether it is competitive compared with competition, and so on; One is whether the data is helpful to our current business, such as identifying high-cost and inefficient departments, or detecting whether the cost expenditure is wasted.
Of course, many enterprises will say that we also have a data analysis team based on the current ERP system of the enterprise, but this is a shallow digital work, which can only be partially improved and cannot be qualitatively changed. So what is deep digitalization depends on whether the enterprise has a digital operation system, which can guide the development of the business through the change of data detection business, whether the data between different institutions and businesses of the enterprise has been opened, whether it is still isolated from the data, and whether there are people who understand digitalization who are managing the enterprise. The so-called "command the old body with a new mind" and establish a reasonable development concept through data, which is roughly what it means.
Ali's internal data culture can be summarized as: "There is data, talk about data; No data, tell the case; No case, go to investigate. " We should use data to communicate and discuss as much as possible, so as to ensure the scientificity of guiding business, rather than just guiding future business based on personal subjective experience in the past.
However, it is also wrong to talk only about data. Different industries have different basic principles, industry knowledge, application tools and business processes. These decades of industry experience cannot be broken with the emergence of data. Instead, we should think about how to deposit these experiences on the digital platform and integrate them with new technologies to produce powerful chemical effects.
For example, industrial digitalization ≠ digital technology+products, but industrial digitalization = industry+digital technology. For example, in the field of industrial manufacturing, a finished product may have dozens of manufacturing links. In the past, these links were not connected with each other, so the production efficiency, yield and inventory rate all depended on people's experience. Now these links can be presented on the digital platform in the form of data, so can we find the problems in the production links in real time and predict the future sales through platforms such as Taobao, so as to improve the yield and reduce the inventory rate?
Enterprises that do well in digitalization are basically enterprises that can clearly put forward and define problems by fully combining their own application scenarios.
|0x02 Problems in the Digitization Process
Even if we know what digitalization is and what digitalization should do, it is still not an easy task to put digitalization on the ground. Among them, the gap is mainly reflected in two aspects, one is the gap between enterprise strategy and technical products, and the other is the gap between digital scheme and digital implementation.
Although we often call some things of the scheme "fudge", it is very important for enterprises to make the scheme clear. Enterprises are not innovative businesses, and they can have opportunities for quick trial and error. The top-level design of the enterprise is not good, and a lot of work cannot be carried out. Moreover, once the original plan is changed, it will be tantamount to a "chemotherapy" for enterprises with complex organizations.
Although the existing digital experience of enterprises can achieve good results in the current industry, it is still two parallel worlds for new industries, with different technologies, performance and business models, which leads to the situation that traditional enterprises distrust new technologies and new technologies despise traditional enterprises.
Many experts with technical background usually describe themselves with three "cows" when talking about their own schemes: how awesome our company is, how awesome our products are, and how awesome our case is. No matter who the customer is, a truth comes out and gives the enterprise an impression: we are the best practice, you don't have to think about it, just do it.
Although the Internet is running fast on the road of digitalization, and even many enterprises are digital enterprises, we also need to see that in the process of moving from C-end digitalization to B-end digitalization, the complexity of many fields could not be considered before, and many professional knowledge has been deposited for decades, and we are not familiar with this knowledge. A simple action can be fast for the C end, but not for the B end.
Therefore, if you want to use your own technical products, you should go to the enterprise's strategy, understand its past and problems, and put forward practical solutions to the problems, rather than the performance of technical products and the indicators of digital products.
From this perspective, reasonable consultation and investigation procedures are indispensable.
Just like KPI and OKR, they often overlap, but KPI is for data indicators, while OKR is for team goals. It looks very similar, but the core concept is actually different.
The process of digitalization will not be smooth sailing, so enterprises should learn from the Big Four, not Internet companies.
|0xFF Digital Talent Literacy
We often satirize some words of the internet: get through, close the loop, grasp the hand ... but in the face of the complex objective world, these words still have its significance. Take the digital capability of an enterprise as an example, the principle is to seek truth from facts, and to tap the potential infinitely in everything.
I still remember a story: a new employee of a consulting company wants to sell a plan to the target customer, but the boss of the target customer is very busy and needs to explain his plan clearly within 1 minute. Finally, when communicating with the boss of the target customer, I explained my plan in one sentence in the elevator: according to my research, your company can increase its income by 30% within one year.
I forgot the details, but this highly abstract ability is still needed.
So what should the "retreat" ability of digital talents be? Simply put, there are four points:
The first is the ability to visualize abstract problems. For example, a customer asks you: What do you think we should do to digitize enterprises? This is a very open question, but it needs a very specific explanation, so it is difficult to visualize the abstract question without studying the customer industry in advance.
The second is the ability to see the essence according to the phenomenon. For example, there are many conflicts of interest between so many departments in a customer's enterprise. How to solve them? In fact, we should consider it from the perspective of getting through, closing the loop, grasping and refining the essential problems, and solving the essential problems can solve the customer problems.
Thirdly, the ability of systematic thinking, the real scheme is not necessarily how tall, but more trivial but specific details, so how to put forward a systematic scheme like painting architecture is the ability of systematization.
Finally, the ability to learn quickly is similar to the requirements of funds, investment banks and other industries. Not all the companies you come into contact with every day are familiar to you, but most of them are unfamiliar industries, such as chemical industry, biology or aerospace. In the past, it was an era of "interlacing like a mountain", but under today's information internet and knowledge platform, cross-disciplinary fast learning is actually possible.
So digital talents are not necessarily from digital companies, because only solving problems is the goal of the industry, so it is more reliable to select talents from consulting companies.
Sometimes, enterprises will have doubts about digitalization: isn't this a platform with goods? Every moment, digitalization is being questioned, but from beginning to end, digitalization is being valued.
I have always believed that data research and development work is all about industry solutions, so it is not only necessary to know more about business problems other than technology, but also helpful for career planning in the next twenty or thirty years.