在上一篇《从信号处理到数字化和数字化转型》中，我们提到，数字化转型是在业务数字化基础上，将旧有的业务处理方式转变为以“数据”处理为核心的业务处理方式的变革。
对于数字化转型的价值，各类专家、机构讲的最多的就是“降本增效”。这句话没错，但是具体是怎么实现的，往往含混不清，要么用“中台”、“大数据”、“人工智能”这些新名词或技术概念来回答业务疑问；要么只摆结果、摆案例，例如某互联网公司上了某平台某系统后实现了业务和盈利增长，而不讲底层逻辑。
今天，我们就来探讨“数字化转型”实现“降本增效”的底层逻辑。
按照《从信号处理到数字化和数字化转型》中的观点，我们把业务从数字化到数字化转型，合并为“步骤化”、“要素化”、“数据规格化”、“以数据为中心的业务变革”四个阶段。
一、“步骤化”——科学管理
“步骤化”的特征是将时间上连续的业务活动，根据管理需求，“抽样”成为离散的多个步骤，并将其固化，不同步骤间建立明确的业务接口，固化的步骤及业务接口支撑了最早的“标准化生产”，以管理大师温斯勒·泰勒20世纪初提出的“科学管理”（Scientific Management）为代表。数字化转型网www.szhzxw.cn
业务活动的“步骤化”推动了标准化生产和流水线，标准化生产减少了人工干预，降低了过程和质量管理成本；流水线提高了设备资产和人力资源的利用率。
二、“要素化”——精益生产
1985年美国麻省理工学院在对丰田公司生产管理方式研究基础上，开启了“国际汽车计划”（International Motor Vehicle Program，IMVP）研究项目，经过近10年，提出并完善了精益生产的理论基础。20世纪末，许多大企业将精益生产方式与本企业实际情况相结合，建立起适合本企业需要的精益管理体系。
精益管理就是用精益求精的思想对企业实施管理，以求实现效益最大化。相对于之前的管理模式，精益管理从价值和效益目标出发，将企业管理中各个具体业务环节的标准要求量化、要素化，明确每个环节的价值指标、参与角色、执行规则、外部约束等要素，对企业人力、物力和财力资源进行最大化的利用。数字化转型网www.szhzxw.cn
精益管理“要素化”的核心在于精，精简不必要的生产环节、销售环节、管理环节，最大程度减少各类资源消耗，是真正的“流程管理”。
三、“数据规格化”——管理自动化
20世纪末，随着IT技术的发展，将计算机及网络通信等技术运用于企业管理的需求催生了“管理自动化”。其特征是ERP系统在企业管理上的应用和计算机控制下的自动化生产线。
为了便于计算机对业务数据进行自动化处理，企业在“要素化”的基础上，对要素数据进行规格化、结构化改造，以适应二进制编码和计算机处理的需求。
管理自动化带来的效率提升主要体现在：（1）计算机相比人工处理带来的的运算效率提升；（2）网络通信相比传统通信手段带来的通信效率提升。
四、“以数据为中心的业务变革”
在管理自动化条件下，企业运行产生了大量的规格化和结构化数据。随着数据库、数据挖掘、大数据、数据智能等技术的发展，在精益管理和管理自动化的基础上更进一步，对数据进行高效利用以追求效益的需求催生了“以数据为中心的业务变革”。目前主要体现在三个层面：数字化转型网www.szhzxw.cn
一是通过现代数据库技术实现了数据的集中高效管理和按需取用，在企业各业务流程环节、各角色可获取任何对于本环节有价值的数据。例如采购计划管理部门可以实时获取生产消耗情况、库存和市场价格情况，以辅助决策；
二是以数字模型和仿真技术为基础，实现数字模型和物理实体的数字孪生，以缩短物理实体论证、设计、生产、测试周期，降低全生命周期成本。如制造业的“数字工程”是通过建立装备的数字模型，利用数字线索实现数字模型和物理实体之间的数据和控制指令交互，运用模型的仿真推演以替代物理实体的测试，以物理实体的运行实现数字模型和物理实体之间的双向验证并促进数字模型的进一步迭代完善；
三是在业务的部分数据密集环节，使用大数据和数据智能技术，获取超越业务规则的信息，以提供智能决策建议。
五、数字化转型“降本增效”总结
通过以上分析得出，数字化和数字化转型的“降本增效”体现在：“科学管理”+“精益管理”+“管理自动化”+“以数据为中心的业务变革”四个方面。这四个方面在数字化的程度是由浅到深，其降本增效的效果也是逐步递进，对应了业务数字化的“业务活动步骤化”、“步骤环节要素化”和“要素数据规格化”以及后续的数字化转型，其发展是连续递进、无法跨越的。
看清了数字化转型“降本增效”的底层逻辑后，CIO们在建议开展数字化建设前，就需要先理解本企业数字化的现状和所处的发展阶段，判断本企业“降本增效”的关键所在，向CEO提出合理的数字化转型路线和投资建议。下一节，我们探讨一下企业开展数字化建设的常见误区。数字化转型网www.szhzxw.cn
英文翻译：
In the previous article “From Signal Processing to Digitalization and Digital transformation”, we mentioned that digital transformation is the transformation of old business processing methods into business processing methods with “data” processing as the core on the basis of business digitalization.
For the value of digital transformation, the most talked about by various experts. And institutions is “reducing cost and increasing efficiency”. This sentence is true, but the specific how to achieve, often unclear, either with “middle”, “big data”, “artificial intelligence” these new terms or technical concepts to answer business questions; Or only pendulum results, pendulum cases, such as an Internet company on a platform after a system to achieve business and profit growth, without talking about the underlying logic.
Today, we will explore the underlying logic of “digital transformation” to achieve “cost reduction and efficiency”.
According to the view of “From Signal Processing to Digitalization and Digital transformation”. We combine the business from digitalization to digital transformation into four stages: “step”, “factor”, “data normalization” and “data-centric business transformation”.
First, “step” – scientific management
The feature of “stepization” is to “sample” continuous business activities into discrete steps according to management needs, and solidify them. Clear business interfaces are established between different steps. Solidified steps and business interfaces support the earliest “standardized production”. It is represented by the “Scientific Management” proposed by the management master Winsler Taylor in the early 20th century.
Scientific management
The “step” of business activities promotes standardized production and assembly line. And standardized production reduces manual intervention and process and quality management costs. The pipeline improves the utilization of equipment assets and human resources.数字化转型网www.szhzxw.cn
Business activities are phased
Second, “factor” – lean production
In 1985, the Massachusetts Institute of Technology launched the “International Motor Vehicle Program” (IMVP) research project on the basis of the research on the production management mode of Toyota. After nearly 10 years, it proposed and improved the theoretical basis of lean production. At the end of the 20th century, many large enterprises combined the lean production method with the actual situation of the enterprise to establish a lean management system suitable for the needs of the enterprise.
Lean management thought
Lean management is to use the idea of excellence to implement the management of enterprises in order to achieve the maximum benefit. Compared with the previous management model, lean management quantifies and factors the standard requirements of each specific business link in enterprise management from the goal of value and efficiency, clarifies the value index, participation role, implementation rules, external constraints and other elements of each link, and maximizes the utilization of human, material and financial resources of the enterprise.数字化转型网www.szhzxw.cn
Step element
The core of lean management “elementization” lies in precision, streamlining unnecessary production links, sales links, management links, and minimizing the consumption of various resources, which is the real “process management”.
Third, “data normalization” – management automation
At the end of the 20th century, with the development of IT technology, the need to apply computer and network communication technology to enterprise management gave birth to “management automation”. It is characterized by the application of ERP system in enterprise management and the automatic production line under computer control.
In order to facilitate the automatic processing of business data by computers, enterprises normalize and restructure the factor data on the basis of “factualization” to meet the needs of binary coding and computer processing.
Normalization of factor data
The efficiency improvement brought by management automation is mainly reflected in: (1) the computing efficiency improvement brought by computer compared with manual processing; (2) Improved communication efficiency brought by network communication compared with traditional communication means.数字化转型网www.szhzxw.cn
Under the condition of management automation, enterprise operation generates a large amount of normalized and structured data.
With the development of database, data mining, big data, data intelligence and other technologies, further on the basis of lean management and management automation, the need for efficient use of data to pursue benefits has spawned a “data-centric business change.” At present, it is mainly reflected in three levels:
First, through modern database technology to achieve centralized and efficient data management and on-demand access, in the enterprise business process links, roles can obtain any valuable data for this link. For example, the purchasing plan management department can obtain real-time production consumption, inventory and market price information to assist decision-making;
Second, based on digital model and simulation technology, the digital twin of digital model and physical entity is realized, so as to shorten the demonstration, design, production and testing cycle of physical entity, and reduce the cost of the whole life cycle. For example, the “digital engineering” of manufacturing industry is to establish the digital model of equipment, use digital clues to realize the data and control instruction interaction between the digital model and the physical entity, use the simulation of the model to replace the test of the physical entity, and use the operation of the physical entity to realize the bidirectional verification between the digital model and the physical entity, and promote the further iteration and improvement of the digital model.数字化转型网www.szhzxw.cn
The third is to use big data and data intelligence technologies in some data-intensive parts of the business to obtain information beyond business rules to provide intelligent decision-making recommendations.
Five, digital transformation “cost reduction and efficiency” summary
Digital transformation “cost reduction and efficiency” summary
Through the above analysis, the “cost reduction and efficiency increase” of digitalization and digital transformation is reflected in four aspects: “scientific management” + “lean management” + “management automation” + “data-centric business change”. The degree of digitization of these four aspects is from shallow to deep, and the effect of cost reduction and efficiency increase is also gradually progressive, corresponding to the “business activity step”, “step element” and “factor data normalization” of business digitization and subsequent digital transformation, and its development is continuous and cannot be leap-forward.
After seeing the underlying logic of “reducing cost and increasing efficiency” in digital transformation, CIOs need to first understand the current situation and development stage of the enterprise’s digitalization before proposing to carry out digital construction, judge the key to “reducing cost and increasing efficiency” of the enterprise, and propose reasonable digital transformation routes and investment suggestions to the CEO. In the next section, we will explore the common misconceptions that enterprises carry out digital construction.
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