Huawei is essentially a family service company

Talent is not the core competitiveness of Huawei, the ability to manage talents is the core competitiveness of the company.

In 1997, a professor of the drafting group was asked in the Drafting Group: "Is it the core competitiveness of Huawei?"

Ren a total answer is unexpected:

"Talent is not the core competitiveness of Huawei, the ability to manage talents is the core competitiveness of the enterprise."

Therefore, there is a sentence in the "Huawei Basic Law" called: "Serious and responsible, management effective employees are Huawei’s largest wealth." Instead of speaking, "employees are the most valuable wealth" as many companies.

In my eyes, Huawei is more than just a company operating a communications business, but also a company that has run talent, and then supports the long-term healthy development of the business.

In essence, Huawei is a family that operates.

01

Core indicator

human capitalROI

Operating talents is the core of Huawei. So, how is Huawei to continue to improve the ROI (return on investment) of human capital?

I think that from the perspective of talent lifecycle management, the following three initiatives are particularly critical.

1, Bottom management of the trial period employee

The proportion of personnel who have been eliminated or transferred should not be less than 20%., Because the upper limit of the international talent recruitment recognition rate is 80%.

If you don’t stick to this basic ratio, the return on investment in corporate human capital will definitely decrease, because there will be some adverse assets to flow into the company, and the loss it caused is not an individual cost, but the high cost of organizing performance.

2Top management of employees 1-3 years

Working for 1 year to 3 years, is the key stage of the return on the return of human capital investment (Huawei is about 2 years).

Generally speaking, the marketing staff is short, the R & D personnel are long, the small businesses are short, and large enterprises are long.

The employees in the first year to the third year have to force 30% of the top, because 1 to 3 years is the highest loss rate of corporate employees. As an active capital, we must calmly face the loss, but also Do your best to reduce 30% of the top 30% of high quality capital.

How can I not let this batch of quality talents lose a lot?

Through the objective evaluation method based on value contribution, 30% of the high-quality talents are evaluated and given differential treatment and differential growth opportunities.

Here, you must dare to pull the gap and dare to give different opportunities for different people, regardless of the contest, just college degree, only the consensus.

This is an employee choice of all enterprises. The object is gathered, and people can share the excellent people in order.

3Normalization of employee exiting mechanism

The three bodies in the management of Chinese corporate talents are: coming in, it is easy to go out, it is easy to get difficult, and the orderly rotation is also difficult.

This causes the talent "slab" or "fluidity deletion". I want to give a business manager of the business manager:

Talent liquidity is more important than capital’s liquidity, because human capital is more valuable than financial capital, and only makes talent to achieve the dynamic optimal configuration of talent, thus playing the maximum effectiveness of human capital.

In any position, Huawei’s default is that it is not more than three years. After 30 years of continuous evolution, Huawei’s exit mechanism and root mechanism are running with normal institutionalization.

Therefore, Huawei can be able to enter the capability, can enter, ordered. Confused other Chinese companies can do the above three points.

02

"Trinity" combination

Continue to create a competitive advantage

From the perspective of the business management system of the company, ROIs that continue to improve human capital are extremely difficult things. The human management model of Huawei "Trinity" is worth learning.

1. Precision-choice – selection and configuration of talents

The biggest cost of selecting people is not the cost of recruitment, but the opportunity cost of the company. A person who is a competent important position can make things, and another uncomfortable person will give the same thing.

This is what Welch said"The ancestors"– There is no suitable person (especially leading talents), and a good strategy cannot be implemented.

Liu Chuanzhi also proposed "Take a team, fixed strategy, with a team"The three-step rules, many people ask Liu’s total "Why isn’t it a strategy, take a team, bring a team?"

Liu always said that it must be "take the team, fixed strategy, with a team", this is the matter of the ancestors. Looking for someone is "something in humanity", and finding wrong people will "things". "

Therefore, the selection of people are precise. The data of the US Manager Association shows that the average talent recognition rate of American companies is 50%.

Welch is the highest CEO we have seen. He said that he used 30 years in "Win" to increase the talent recognition rate from 50% to 80%. The talent recognition rate of Chinese companies is around 35% – only one of the three positions is selected, this is the gap.

As a manager, the accurate people are a basic skill.So, how can I quickly improve talent recognition?

Huawei began using STAR rules since 1998:

S-Situationscene

T-Task Task

A-action How to act

R-RESULT result

Description of the key behavior in the past helps us accurately determine the quality and skills of the candidate.

STAR is a structured behavior interview method. After repeated tempering, after the interviewer masters this skill, it can effectively eliminate the factors that can take a head of the head, allowing the general enterprise’s talent recognition rate to more than 60%.

In addition, companies are not only to selection of individual talents, but also learn to form the best team – make the division of labor of core talents more reasonable.

Huawei began in the 1990s"Wolf Plan"That is to achieve this purpose, the two principles of team of teamal and deputy is:The core values ??are converged, and the ability to compensation is complementary.

2Accelerate the talent – talent growth mechanism

Ten years of trees, a hundred years of tree people. Under normal circumstances, the speed of enterprises will be faster than the speed of talent growth, especially in the transformation of the company’s change.

According to statistics, the return on investment in China’s business talent training (including training) is only 10% -20% of US companies. Huawei’s leading enterprises have huge investment in talents, so we must fully consider accelerating investment benefits of promoting talents.

First, one of the things that must be done is the accelerated development of employee capacity – career planning. Now is a human society, it is an enforcement enterprise organization, so we must pay special attention to employee development.

Huawei is the first Chinese company in China to introduce the "five-level dual channel" qualification system.(Note: It is now five-level three-way channel, which has added a horizontal position – project management).

Where is the problem with low talent training efficiency?

I think the cultivation of Chinese companies in two major misunderstandings – did not do "practice teaching" and "learning".

If the learning method is not based on effective growth, it is not based on the greater value for the company, I think this kind of study is a huge investment waste.

In Huawei, basic knowledge training, case teaching and action learning is no longer the most effective model, and replaced by the "training combination of training" advocated by the non-all.

Huawei cultivated talents must have the ability to "win". Huawei globalization layout, how to copy "General" talents in front?

Huawei is a convened of those most powerful national representatives (frontline), by them, as teachers.

These teachers Take the training class as a "pre-enemy operation headquarters"Lead the students to conduct all true practices.

3, High efficiency incentive – talent long-acting power mechanism

In fact, if there is money, no money and incentive mechanisms are effective in complete different concepts.

Many entrepreneurial companies don’t have much, they can attract and motivate outstanding employees; and a lot of money, a large, unprical, incentive, has a negative effect.

For example, the yield of Huawei employee is currently Wages, bonuses, TUP allocation and virtual contoursFour parts are composed. Before 2014, Huawei was three assignments, no TUP.

Over the past decade, the implementation of virtual restrictions, staged solves the "Who Wars" – the problem of long-term interest community.

But developing to today, its side effects are getting more and more obvious – forming a huge housekeeping class, these people are lying without working hard.

What should I do at this time? The essence of TUP allocation is a deferred distribution of bonuses, which is mainly assigned to young people with excellent contributions.

In this way, the amount of "Old Eight Road" virtual equity allocation is diluted, so Huawei "is fulfilled" with the struggle ".

Since the implementation of TUP, in addition to activating some "elderly", the biggest value is to enhance the abilities of Huawei to attract and retain outstanding young employees, so that Huawei will lose human capital advantage in the Internet’s new privileges.

Huawei believes that the essence of incentives is the expected value management– The employee is not an absolute value of the amount of compensation, but the gap between the absolute value and the individual expectation value.

Greed is a basic desire of people, Huawei’s greatest contribution is Let the employee’s expectation value returns to rationality.

So, how is Huawei manage the expectations of employees?

03

How to manage employee expectations?

First, Huawei insists on setting challenging goals – followed by cashing in the assessmentA10% / B account for 45% / D to account for 5% Basic ratio. It is easy to achieve the goal.

The requirements for A are beyond the goal, and the goals are challenging. So it is very difficult, the more the high level is getting more, and the Huawei has nearly half of the employee is the assessment result C.

When I started the assessment, many people will ask, why do I do so good?? I sayCIt is normal.

He said it is not normal, what do I say is normal? He said A is normal, I said NO, A is abnormal, A is extraordinary.

Huawei target value is very challenging, which means that even if the company’s target reachable rate is 70% -80%, the total reward package is also very large.

On the one hand, the employees of B, and the total number of employees are around 85% of the total number of employees, they have not completed their goals; on the other hand, they find that they have a lot of bonuses.

In this way, the employee will produce when they get money."负 疚": The boss is very good to us, we don’t want to do it, the company also gives so much money, embarrassing! Must do it next year.

Confused most Chinese companies, the target value is not to say, the proportion of the assessment A is still very large, resulting in mistakes that many employees are "great", and the company will give me too little. This will contribute to the "greed" side in human nature, so that more money can not be feeding.

Summary, the pattern of Huawei’s operating talents is not necessarily suitable for all companies, but its core concepts and operation methods can give many Chinese companies.

Let Chinese enterprises make better value for "value creation – value evaluation – value allocation".

Give people pricing? Establishing a talent evaluation criterion is a premise 2021-11-29

After Huawei continues to have a "ace", he only insisted on doing one thing 2021-11-25

Huawei changed the top ten cerams 2021-11-17

Every time you look at the driving force of our advancement

Next generation tumor immunization technology: Single-cell analysis and artificial intelligence from immunohistogenesis

Foreword

The huge progress of immunotherapy has changed the model of cancer treatment, however, in view of only a few patients have responding to the blocked the immunogenic examination and other immunotherapy strategies, more new technologies need to be used to decipher the micro-micro-microenvironment of tumor cells and tumors (TME The complex interaction between the ingredients.

Tumor immunougueology refers to a comprehensive study of TME using multi-synthetic data using immunologically, immunological proteomics, immunogenic information, etc. reflects tumor immunization state, depending on the rapid development of next-generation sequencing technology. The high-throughput genome and transcriptum data can be used to calculate the abundance of immunocytes and predict tumor antigens, however, due to batch sequencing represents the average characteristics of heterogeneous cell populations, different cell subtypes cannot be distinguished. Single-cell-based technology can better analyze TME through accurate immune cell subpopulations and spatial structures. In addition, the depth learning model based on radiographics and digital pathology has a large extent to the study of tumor immunity, which is well shown in predicting immunotherapy response. The progress and breakthroughs of these new technologies have far-reaching significance for cancer treatment.

Tumor immunization micro environment

In the past few years, the research progress of tumor immunity has made us fundamentally changed the understanding of tumors. The definition of tumors also evolved from a simple tumor cell to a complex organ pattern structure, consisting of tumor cells, immunocytes, fibroblasts, vascular endothelial cells, and other matrix cells. Various cells and components near tumors, such as structural, such as immunofuncing cells, blood vessels, extracellular matrices, etc., also known as tumor immunochemical, and have become one of the topics of tumors. TME has been proven to play a decisive role in cancer, tumor progression, metastasis and recurrence.

TME includes extremely diverse immune cells, including T lymphocytes, B lymphocytes, natural killing (NK) cells, macrophages, dendritic cells (DC), granulocytes and mycinoid inhibitory cells (MDSCs) Wait. Typically, T cells, B cells, NK cells and macrophages help inhibit tumor growth, while MDSC and regulatory T cells (Treg) tend to inhibit anti-tumor immunity. However, existing studies have confirmed that in view of the complex interaction with tumor cells, the specific role of immune cells may have changed, and even completely opposite.

In summary, various immune cell types, even different functional conditions of specific immune cell types may have an opposite effect against tumor immunity. Therefore, this requires the most advanced bioinformatics techniques to minimize the immunological characteristics of tumors to the greatest extent, and provide more information to enhance our understanding of tumor immunity.

Immune genomics in NGS era

Over the past twenty years, NGS, including all genome sequencing (WGS), full exon group sequencing (WES), and RNA sequencing (RNA SEQ) has been successfully developed and applied to acquire human genome information. NGS produces high-throughput genome and transcriptional data to lay the foundation for the study of multi-step immune responses.

Immune cells in TME

TME consists of a variety of immunocytes, for quantification of tumor immunocytocyte components, conventional methods, such as flow cytometry and immunohistochemistry (IHC), due to its high cost and low tissue availability, is not applicable to large scale analysis. With the rapid development of NGS, we can estimate the abundance of dozens of immune cell types through NGS data, which are also proven to be reliable. These analyzes are mainly DNA and RNA sequencing, especially the latter. Regarding RNA sequence data, the principle of calculation methods is mainly divided into gene set enrichment analysis (GSEA) and inverse volume.

Typically, the representative algorithm based on GSEA includes Estimate, XCell, and MCP counts. A common feature of a GSEA-based approach is to establish specific genomic sets for each of the immune cell subsets of interest. The inverse volume of the cellular component is the reverse process of cell subtype convolution in a body tissue based on gene expression characteristics. Tools based on reverse volume include Decornaseq, Pert, Cibersort, Timer, EPIC, QuantiseQ and Deconf.

Identification of tumor antigens

Body cell DNA mutation, including mononucleotide variation (SNV) and insertion and deletion (INDEL), is the main source of abnormal antigen. Currently, the Genome Analysis Toolkit (GATK) is the industry standard of SNV and Indel by analyzing WES, WGS and RNA sequence data. It is also expanded to encompass copy number variation (CNVS) and structural variation (SVS).

Furthermore, the abnormal peptide needs to be combined with HLA to assist the T cell receptor (TCR) to initiate an immune response. The prediction of HLA is essential to identify tumor antigens. HLA Miner and SEQ2HLA are two early tools for HLA typing from NGS data, Four, six and eight-bit resolutions in PHLAT, HLAREPORTER, SNP2HLA, HLA-HD, Optype, and HLA-VBSEQ in different cancers. The performance is quite good. In these tools, Polysolver is one of the recognized standard tools currently using low coverage WES data.

In addition to identifying an abnormal peptide and HLA type, antigen MHC binding pro and is the next focus of tumor antigen prediction. Many peptide-MHC-I (PMHC-I) affinity prediction tools are based on artificial neural network (ANN) training methods and position specific score matrices (PSSM), as currently widely used tools NetMHC and NetMHCPAN. Due to the diversity of MHCII binding peptide and "openness" of the binding zone, predicting PMHC II affinity is more challenging, the number of PMHC II affinity prediction methods is far less than PMHC-I.

Single cell age immunohistology

Although the study of tumor immunity is used to study NGS technology to greatly promote the development of tumors, batch sequencing may cause signals to be diluted below the detection limit and mask the reaction of individual cells. This may hide many important biological phenomena. Until recently, the technical breakthrough of single cell-related methods thoroughly changed our understanding of tumor immunity, and transitioned from regional levels from regional levels to a single cell level.

Multi-color flow cytometry

Multi-parameter analysis is functional and physically distinguished by different immune cell subsets. In addition, with the advancement of technology, the instrument design of more parameters can be measured, such as 30 parameters and 50 parameter flow cytometry. However, due to the lower parameter accuracy, or higher precision measuring parameters, especially due to overlap between fluorescent dye emission spectroscopy, these disadvantages limit the application of multi-color flow cytometry to a certain extent And further development.

Matrix flow cytometry

The mass spectrometry is a new innovation in the field, also known as flight time (CYTOF), combined with streaming cytometry with mass spectrometry. Compared to conventional flow cytometry, mass spectrometry is not a fluorom antibody with metal isotope, and then quantifies the signal using the flight time detector, the detector detects at least 40 parameters, and avoids spectral overlap. Cytof has been confirmed to be a precise tumor tissue high-dimensional analysis method for explorating immunoassays and biomarkers found.

Although in theory, mass spectrometry flow cytometry allows us to detect up to 100 parameters per cell, but the processing speed and flux are limited by ion flight. After atomization and ionization, the cells are completely destroyed during the pretreatment, resulting in the end of subsequent cell classification. In addition, Cytof may not be appropriate for the measurement of certain low expression molecular features.

Spectral flow cytometry

Spectrum flow cytometry is another latest technological advancement that promotes traditional flow cytometry. Unlike the mass spectrometer, spectral flow cytometry is still labeled antibodies with fluorescent dye, but a new detector with a dispersion optical and measuring full emission spectrum replaces conventional optical and detectors. Based on the same principle, traditional flow cytometry and spectral flow cytometry maintain considerable compatibility, particularly in terms of commercial antibodies, but can better eliminate confusion factors, such as spectral overlap to improve efficiency . With the development of compensation technology, spectral flow cytometry may replace multi-color flow cytometry.

Single cell RNA sequencing

Based on streaming cytometry combines a specific label with the corresponding cell subgroup and identifies the label, indicating that the target must be determined before the sample collection, and the initial goal limits the information obtained from these technologies, only these Technologies find "known unknown".

The emergence of single cell sequencing technology pushes a single cell sequence to a new height. Single cells can be sequenced using a standard NGS protocol for predetermined targets such as streaming cytometry.

At present, SCRNA-SEQ applications are more mature than other methods, and the re-tumor immunotherapeutic field provides us with a lot of very valuable discovery and revelation. However, the technical noise produced by trace substance is still the most significant challenge. How to separate a single cell and maintain its bioactivity, how to solve the enlarged huge technical noise and improve sensitivity, how to get the highest number of measurable genes at the lowest price, how to analyze data more effectively, these are greatly improved single cells The threshold for sequencing limits its wide application.

Immunohistology and artificial intelligence

Artificial intelligence in tumor immunization studies mainly involve the following aspects: (1) Alleviation of immunological infiltration on artificial identification of pathological sections; (2) Provide an alternative technology to identify immune cells that are difficult to identify in naked eye The subpopulation and spatial structure; (3) Provides a non-invasive method to predict the TME characteristics of a particular patient and the reaction of immunotherapy.

Tumor antigen prediction based on deep learning method

The first step in deciphering the tumor antigen is to predict the abnormal peptide. In addition to identifying a variety of algorithms of SNV, the recently designed CN learning tool is also designed to detect CNV and exhibit good performance. About HLA profiles, Bulik et al. Generated a large integrated data set, including various types of cancer tissue HLA types and HLA peptides, which announced data that can be used to train intact mass spectrum depth learning model EDGEs, which is already non-small Verification is obtained in patients with cell lung cancer (NSCLC). In addition, two very promising depth learning methods Maria and MixMHC2PRED have recently been developed, which greatly increases MHC-II prediction accuracy.

Application of radiology in tumor immunity

With the development of artificial intelligence in medical imaging, the image is not just a picture, but a large-scale digital data, the process of analyzing the imaging data using AI technology is the radiographic. Radiological techniques applied to tumor immunization are mainly used to identify biomarkers reflecting immunoff and predict the therapeutic response of ICB treated patients.

Calculation of tumor immunity

AI, or so-called digital pathology, by calculating analysis, providing new insights for exploring the interaction between immune cells and tumor cells and the key behavior of cancer biology.

Similar to radiology, digital patients combine deep learning from the image to excavate the invisible information, so that we can understand TME in cell or molecular level. Digital pathology may be a promising method for studying the relationship between TME structure and cancer biology and treatment.

Application of immunohistology in tumor immunotherapy

Identifying ICB biomarkers for patient layers

As a target of ICB, the PD-L1 expression level detected by IHC is the first predictive biomarker, but some clinical trials have shown that ICB has only slight effect on some PD-L1 high expression patients, and ICB also Will respond to PD-L1 low expression patients. Therefore, other biomarkers are urgently needed to fill this gap.

In 2014, the researchers were linked to the clinical survival rate of tumor mutation (TMB) with patients who were treated with CTLA-4 inhibitors by WES. Subsequently, other retrospective studies also prove that high TMB is related to lasting clinical benefits. Regarding the method used to evaluate TMB, due to the high cost and complexity of WES, the FDA approves two alternative NGS platforms, which is FoundationOndongOne CDX (F1CDX) and MSKCC operable cancer target integrated mutant (MSK-IMPACT), and passed Prospective study of multiple cancers has been verified.

On the other hand, immune cell infiltration, especially TIL, a key role in immune response. In order to find more desirable treatment and prognosis biomarkers, single-cell sequencing is used to identify more immune cells. TCF7 + memory T cells have been found to be related to clinical improvement in patients with melanoma after anti-PD1 treatment, while stem cell-like TCF1 + PD1 + T cells have been confirmed, which contributes to tumor control in ICB treatment. Thorbing T cell subpopulations and functional conditions associated with treatment and prognosis are determined by single-cell sequencing techniques.

Prediction of new antigen in ACT treatment

Overpounding Cell Therapy (ACT) is re-transferred to the patient by transgene or amplified autologous or allogeneic T cells to enhance anti-tumor immunity. Immunoatology is mainly used to identify the ideal tumor antigen in ACT treatment.

At present, the new antigen-specific TCR-T cell has not yet entered the clinical application. However, it is gratifying that some case reports show the neat colorectal cancer, breast cancer and cholangiocarcinoma patients with immunohistology, T cell recognition tumor new antigen Effectiveness. TRAN et al. WGS on the sample of metastatic cholangiocarcinoma patients, determined 26 species of cell mutation. The series microchrome composed of mutant genes was transcribed and transfected into autologous APC, and then the new antigen was presented with TIL of APC and the patient’s source of TIL, and finally identified antigen-specific CD4 + VB22 + T cell clones and induced epithelial cancer.

The conventional autologous APC and T cell co-cultured new antigen selection is limited due to its low flux, high cost and time consuming characteristics. In order to eliminate these obstacles, more high-throughput immunogenic new antigen detection techniques were developed. Li et al. Established a Trogocytosis-based platform where the TCR and PMHC were combined, the surface marker protein was transferred from the APC to T cells. Therefore, the ideal new antigen can be identified by analyzing labeling positive cells. In the future, these emerging immunologies will achieve high-throughput antigen selection.

Choose a new antigen for individual tumor vaccines

The immunohistological method has been widely used in vaccine development in clinical studies. In general, a new antigen for generating a personalized vaccine is identified by analyzing a tumor and normal tissue WES and RNA sequences, and is identified by an algorithm (such as NetMHCPAN).

Similar to ACT, key parameters for tumor vaccine development are ideal for new antigen identification. In order to improve the accuracy of the new antigen prediction and the new epitope selection of the immunogenicity, immunohistology technology has made unremitting efforts in these respects. In a recent study, Wells et al. Compiled all new antigen predictions and selection methods and provided a new candidate measurement pipe, including 14 immunogenic characteristics of MHC presence and T cell recognition. This study laid a solid foundation for improving the efficacy of tumor vaccine and the adverse cell therapy.

summary

In recent years, with the huge leap of emerging technologies in the field of immunohma, we can now analyze tumor immunity before.

In the bulk sequencing era, we can better explore the individual infiltration model of tumor immunocytes, and the prediction of abnormal peptides, HLA-based and tumor antigen MHC binding pro-and predictions, using immunogenics, predicting tumor antigens have been in front of it. It proves its reliable effect in clinical research.

In addition, with the development of single-cell immune related technologies, from multi-color flow cytometry to CYTOF, single-cell tumor immunization maps help us to classify the immune cell subtracitions to decide the TME component. The emergence of artificial intelligence also provides a new direction for the development of immunohistology.

With the booming of immunohistology, sustainable development needs several issues. First, although many methods of quality control and improvement algorithm have been implemented, the effectiveness of these technologies remains to be improved. Especially in tumor antigen prediction, single cell sequencing and space resolving transcriptional groups, technical noise and mixing factors have hindered subsequent analysis. Second, we look forward to the more cost-effective, easier to obtain and more automated techniques, thoroughly change the development of the discipline. Third, we also expect researchers to make full use of prior art to explore tumor immunity and promote clinical transformation.

Although there is still a lot of work to do, the immunohistology is likely to dominate the future in the future, and its clinical value will undoubtedly promote the development of the subject in the field of immunohistology, single cells and artificial intelligence.

references:

1.Technological Advances in Cancer Immunity: from Immunogenomics to Single-Cell Analysis and Artificial Intelligence. SignalTransduct Target Her. 2021; 6: 312.

Building a service closed loop map science and technology to help retail market digital upgrade

Computer vision has evolved from an artificial intelligent technical topic to create value for business. In China, many successful cases come from the scientific retail industry. In foreign countries, both semiconductor giants Intel or retailers GAP Inc., companies in different industries are increasingly striving to intelligently incorporate artificial intelligence into their operational techniques. But one of the potential pain points is how to extend the AI ??project from the idea, and the gestation period to the full integration of the business.

Digital Digital in the store requires a Digital Store Platform that can integrate sales systems and operations systems to enhance customer experience and operational efficiency. Computer vision is one of the key technologies that can achieve these goals. Through its perception, judgment, executive empowerment enterprises, thereby achieving the purpose of transformation experience and business efficiency.

Artificial Intelligent Technology Enterprise Scientific Technology AI digital business solution has a wide range of representative, which shows how computer vision technology is how to enable existing and new digital contacts of retail enterprises, helping companies achieve business objectives. .

Building 3D digital items by automatic identification and automatic 3D modeling technology, improving customer experience and operational efficiency.A IT retail head brand has always rely on the advertising company’s product propaganda shooting and combined with the marketing materials, but the product is much, the market characteristics of the iterative, and the material materials depending on the traditional way are difficult to keep up with the rhythm. Spectrum Technology AI digital commodity solutions will support this process, intelligent automation, and program support instant automation to create multiple categories 3D products, 3D product manuals, marketing scenarios, support customers to put 3D digital products into different scenarios. Digital live experience and real-time iterative analysis.

3D digital merchandise shopping, 3D digital experience hall, support real-time interaction.影 科技 technology and China’s home appliance leader Haier reached a strategic cooperation, jointly built a home appliance numerous business solution, expanding the visual presentation ability of the commodity multimode coexistence, and realizes interactive immersion shopping experience.

Optimize the shopping experience through 3D virtual customer service robots, and build service closed loops to help retail sales.The picture score technology intelligent service system can coordinate deployment to complete the exclusive digital virtual person, virtual store shopping guide patrol, virtual after-sales instructor, etc. Virtual store patrol robot can help store to reduce the shortage and product display errors, improve customer experience; virtual after-sales instructor maximize customer use interests, reduce misunderstanding chances; digital virtual people are reflected in various live, shopping guide, etc. Digitalize customer behavior, support business decisions by capturing customer interaction processes, and transforming them into relevant quantitative indicators to support business decisions.

In the retail scenario, the brand, retailer, and consumers are asymmetrical. This also leads to time and efficiency. In the past few years, the complexity of online retail growth has grown index. On the one hand, the retail brand is a change in sales. On the other hand, it lacks automation IT technology to enhance the digitization of goods and marketing materials.

For retail brand, cost, efficiency, experience seem to form an impossible triangle. In the face of continuous digital contacts, the retail brand must obtain a full range of visualization capabilities, data-related analysis, end-to-end digitization experience, and seamlessly integrate into the entire business digitized chain. With the reduction of traditional customer experience, it will help retailers to achieve cross-platform collaboration AI twins solution will determine who can stand out.

From the above-mentioned investural score technology, you can see that it constructs one-stop closed-loop service capability and advantage in the retail area. It is understood that the scientific technology has opened the computer vision AI generation technology and digital twin technology, providing end-to-end in the industry and enterprises, and retail solutions will operate through the real-time interaction 3D into the core. Transfer to visual data, help brand retail build 3D retail platform, analyze, track business decisions, and optimize market strategies including pricing, product delivery, promotion, effectively enhance corporate operation efficiency, Help the retail market to digitally upgrade.