What is digital transformation and how should it be done?

0 1 The Six Stages of Digital Transformation for Traditional Enterprises

　　The digital transformation of traditional enterprises can be roughly divided into six stages:Business dataization, data assetization, asset valuation, value serviceization, and service ecologicalization.These six stages are not a waterfall progression, and there may not be clear transition signs between each stage. These stages are likely to exist simultaneously, but at a specific time, one stage will dominate because data assets are a continuous process of accumulation, improvement, and optimization.

0 2 Business dataization

　　In the era of information technology, different business systems have gradually been built to meet the needs of business operations. IT systems revolve around business services and accumulate a large amount of data during the service process. Based on this data, analysis can be conducted, such as ERP, CRM, supply chain, online shopping mall, offline POS, master data and other systems.

0 3 Data assetization

　　Based on mobile internet, Internet of Things, cloud computing, and big data technologies, consumer information (fans, potential customers, new customers, old customers, loyal customers, etc.) is collected through digital means, and various tags are assigned to customers, such as demographic tags, behavioral tags, transaction tags, preference tags, and consumption trend tags. A data asset catalog is established to form a group portrait (such as high purchasing power, medium purchasing power, low purchasing power). Data that is isolated and decentralized, without cleaning and integration, has little value. Only data with integrity, uniqueness, consistency, accuracy, legality, and timeliness is a data asset that can truly create business value.

　　Data assetization requires the aggregation of fragmented data scattered across various platforms within and outside the enterprise, online and offline, to connect and enhance each other, and to promote the enterprise to become more intelligent. Enterprises are trying to use various technologies to process massive amounts of data of different types and formats, in order to accumulate and enhance the value of enterprise data assets.

0 4 Asset valuation

　　Data must be combined with business scenarios, artificial intelligence, and data operations in order to truly present value, change the way systems assist decision-making in the past, gradually use data decision-making as the core driving force, and achieve the goals of accumulating experience, improving efficiency and reducing burden, empowering business, and innovating through data reuse and secure sharing. On the basis of establishing and improving data assetization, fine tuned operations are carried out for consumers, and value is brought through data-driven scenario applications.

　　The accumulation of data and the development of artificial intelligence (AI) mutually promote and complement each other. Enterprises use intelligent means for prediction, warning, and recommendation, achieving thousands of people, thousands of stores, thousands of operations, more accurate and efficient reach and marketing, such as optimal audience recommendation, optimal SKU recommendation, and related product purchase prediction, and ultimately achieving business growth goals.

0 5 Value oriented service

　　Enterprises need to streamline their internal and external service capabilities, standardize their business capabilities, encapsulate them into services, plan and build reusable value service platforms through platform thinking, and connect the internal front-end and back-end of the enterprise with external ecological platforms. In the digital age, it is necessary to take data-driven approach as the starting point and operate data assets as strategic assets of enterprises, so as to increase the value of data assets and turn them into business value.

Value output platforms have also been popular in recent years, such as business platforms, data platforms, technology platforms, and organizational platforms. Enterprises empower each other through the middle platform, calling upon each other's strengths to make up for their own weaknesses, while also opening up their own strengths for others to call upon, and obtaining corresponding value returns based on the new value chain.

0 6 Ecological Service

　　In order for future enterprises to transform and upgrade, they need to be open and connected with the industry, requiring a symbiotic, coexisting, co building, and win-win mindset. They should vertically serve the front-end and back-end of the enterprise, and horizontally serve various business units and the upstream and downstream of the entire industry chain.

For leading enterprises in the industry or enterprises with core data, in addition to providing services and empowerment for various business formats within the enterprise, the service system can also be extended to the industrial ecosystem, and the internal platform can be extended to c2S2b2c (or c2B2b2c), where S refers to the supply platform. Xiao B uses the empowerment of the supply platform S to provide services to C.

0 7 生态产业化

　　数字化核心要点就是产业链上下游企业借助同一个数字化平台、企业赋能各自的核心能力和资源，来实现高效的分工和更合理的价值分配，改变过去“麻雀虽小、五脏俱全”的企业组织形式，把企业的边界和组织扩展到产业链层面，同时也规避了企业各自的短板。

企业边界模糊、产业边界模糊，将会直接导致垂直分工则更加明显，由于产业间横向整合使得横向链条变宽，产业内链条网状化使得产业内纵向链条平缩。这些都将会加剧产业间重新融合，并进化和演变成新的产业生态或产业联盟，甚至有可能，未来的产业形态，可能跟我们当前的产业形态完全不同。

企业如何正确落实数字化转型

首先，我们要明确，任何组织或机构做数字化转型，都是一个系统性的工作，整个任务下来，任何一个环节都不可以割裂做事。如图所示，主要有5个步骤：

1.诊断企业在数字化转型中所处的阶段

这里我们以数字科技的应用为纵坐标、业务为横坐标，可以将企业分为引领型、进取型、保守型、滞后型。

这里我们主要说下引领型，主要有4个特点，如图所示。如果做好了前3点，最后一点就能自然而然达到。因此亿信华辰希望无论企业处于哪个阶段，都希望企业能由保守型逐步进化到进取型，最终过渡到引领型。

但企业到底该如何判断自己处在哪个阶段呢？这里我们将数字化转型分为三个阶段：

（1）信息化或系统化阶段

重点在硬件建设和数据能力，比如90年代起盛行的ERP软件系统已成为众多企业的“标配”，极大地推动了企业信息化进程。这个阶段的内容包括数据的标准化、规范化，以及数据的打通和整合。

（2）数字化或智能化阶段

这个阶段重点在于业务、产品和服务优化以及协同共享，同时数据价值在企业管理决策、提升客户洞察、改善运营效率等诸多方面会发挥重要作用。

（3）转型与升级阶段

企业需要打造持续创新能力，包括产品与服务创新、商业和管理模式创新。从根本上打破烟囱式的业务和组织架构，构建横向、纵向体系，探索新赛道，逐渐向平台化与生态化发展。

总的来说，企业可以根据自己的实际情况和发展阶段，从下面几个落地领域入手：比如，完善企业信息化建设，提高现有业务流程和客户界面的数字化程度，以及提高整个价值链的数字化水平。

2.明确数字化转型的方向：客户价值

只有以创造客户价值为目标的商业模式，才可以形成可持续的ROI，这个底层逻辑是由今天较高的社会生产力水平和市场的供求关系决定的，无论是在中国还是其他国家，都是一样的。可以从以下3个方面来明确：

（1）无论数据还是技术，都要服务于业务，业务又要紧紧围绕客户价值；

（2）形成客户价值驱动的共识至关重要

（3）企业在转型过程中，需要很好地平衡客户体验和运营效率两个维度，不能过度追求客户体验。

3.数字化转型的三个领域（业务、技术、组织）

（1）业务转型

是指企业通过全价值链的数字化变革实现运营指标的提升，成功的业务转型需要认清方向，明确愿景，制定分阶段的清晰转型路线图；正如面前提到，要有一个大方向，又要一个分阶段的短跑，小型的项目与规划，同时关注全价值链环节，以“净利润价值”为驱动，以业务为驱动进行转型。

（2）技术转型

是指搭建企业数字化转型所需的架构和技术生态系统，成功的技术转型需要健全的架构，创造并引领主题明确的技术合作伙伴生态圈，为什么这么说呢，在当今这个世界，单打独斗，在现在的技术体系下，发展的进程下是很难完成的，促进企业借力合作，取长补短，共同发展。

例如，对工业制造领域来说，工业物联网架构是支撑数字化业务用例试点和推广的“骨骼”，而数据架构是确保“数据-信息-洞见-行动”能够付诸实践的“血液”，而整体架构的构建需要始终以数字化转型的终极目标为导向。

（3）组织转型

是指在组织架构、运行机制、人才培养和组织文化上的深刻变革。

成功的组织转型是一场自上而下推动的变革，需要企业高层明确目标，构建绩效基础架构，成为指导转型行动方向的“大脑”；形成转型举措和财务指标的映射，成为反映转型业务影响的“眼睛”；树立全组织一致的变革管理理念和行为，成为引领组织上下变革的“心脏”。另一方面，企业需要关注团队的构建，比如：

弥补员工的能力差距，建设数字化知识学习的文化并使之可持续发展；还需要推进数字化能力和人才梯队的建设，组成推动转型大规模推广的“肌肉”；构建敏捷型组织和团队，为又快又好地实施和优化转型举措提供支撑。

4.二个具体实施步骤与演进思路

（1）按照连接-数据-智能思路演进

当谈数字化演进路线的时候，实际上数字化转型的三个核心内容正是最基本的演进路线。即企业在进行数字化建设的时候优先还是要考虑解决连接和协同问题，这个过程有些是处理信息化阶段没有做完的事情，进行优化和整合。

其次是数据驱动运营，数据贯穿整个数字化建设生命周期，即业务和数据建设两条线是并行的。传统方式是IT系统建设完成后才考虑如何利用数据进行分析决策，而新的构建思路是数据建设配合业务建设和协同并行，数据不断的反哺业务，支撑业务运作。

最后是智能，智能不是简单基于预设规则的自动化，而是可以自适应地进行规则调整和优化，这个需要的是大数据的积累，不是一蹴而就的，但是前期要有这个意识。

（2）按照目标细分和短周期迭代

企业数字化转型要围绕企业战略和业务目标，将大目标分解为子目标，然后围绕每个子目标进行业务，组织，IT技术的改造和优化。先做基础框架的搭建，然后建设数据模型，最后再持续的优化。

这就要求相关的数字化公司拥有更强的企业运作经验，把数字化的系统架构先搭建完善，保证整个流程的通畅，后续升级优化才能更顺利。

5.沉淀组织与人才的数字化能力

任何企业要实现数字化转型，最终都需要回到人才和组织层面。通过塑造人，打造具备数字化能力的组织，建立能够引领数字化转型的文化。回到人、管理者、领导力和组织，从职能型组织到事业部型组织，从平台型组织到生态型组织，是一个不断迭代升级的组织转型过程。

信息来源：MES之家