What are Efficiency and Effectiveness in simple terms? For many people, they could mean the same thing as both are based on ROI (output/input). However, there is a slight difference.
Every business starts with an investment ( Capex ) with a regular cost being incurred ( Opex) before they realize revenue ( Topline ) with the purpose to make a profit ( Bottomline).
Efficiency is focused on optimizing resource(s) (Capex+Opex) utilization.
The Basic assumption, as per financial books is that all the inventory is assets. The inventory which is not sold may have to be written off in financial books until the revenue is realized and it needs to be perceived as a liability.
Whereas, Effectiveness is focused on improving the bottom line considering Inventory as a liability.
Still unclear? Here's a simple example. Tata Nano is a prestigious project in India with an objective to sell affordable, low-cost cars. The project failed miserably. Keeping the reasons apart; the Gujarat manufacturing plant was In line with the latest world-class manufacturing practices, the Gujarat ( Sanand ) plant had been equipped with state-of-the-art equipment. They included sophisticated robotics and high-speed production lines. The plant had energy-efficient motors, variable frequency drives, and systems to measure and monitor carbon levels. These were supplemented with extensive tree plantation, sustainable water sourcing through water harvesting, and groundwater recharging, and using solar energy for illumination; all of this helped the plant to be more sustainable. It was completely Efficiency focussed. They had to pay the price down the line when the goods are not sold. Like Tata Nano, many companies (including software) and teams are efficiency focussed.
Local efficiencies don't yield global effectiveness. It is time to get away from efficiency.
A glimpse through the Manufacturing industry revolutions along with critical events which have revolutionized and act as a platform and are what it will take for the Manufacturing Industry to get into 5.0.
The Financial (including Insurance) and Software Industry are like platforms (Non-physical Products) to the Manufacturing Industry (Physical Products) and I am generalizing everything by calling it an Industry.
Industry 1.0 ( ~ 1780 ) - Mechanization
Water and steam-powered machines were developed to aid workers. Little to nothing of that mechanism remains a key role in our lives today.
But it was the one made possible by its successors also ( The income tax )
As production capabilities increased, businesses also grew from individual cottage owners taking care of their own — and maybe their neighbors’ — needs to the needs of the organization with owners, managers, and employees serving customers.
Industry 2.0 ( ~1870 ) - Electrification and Mass Production
Electricity became the primary source of power. Eventually, machines were designed with their own power sources, making them more portable.
This period also saw the development of a number of management programs that made it possible to increase the efficiency and effectiveness of manufacturing facilities. Division of labor was done, where each worker did a part of the total job, and thereby increased productivity. Mass production of goods using assembly lines became common practice.
Principles of Scientific Management
Frederick Winslow Taylor (March 20, 1856 – March 21, 1915) was an American mechanical engineer who sought to improve industrial efficiency. Taylor was one of the intellectual leaders of the Efficiency Movement, and his ideas were broadly conceived and were highly influential in the Progressive Era (1890s–1920s). In 1911, Taylor summed up his efficiency techniques in his book The Principles of Scientific Management. This is known as Taylorism.
Fordism - Push model ( built-to-stock )
Ford introduced methods for large-scale manufacturing of cars and large-scale management of an industrial workforce using elaborately engineered manufacturing sequences typified by moving assembly lines. By 1914, these methods were known around the world as Fordism. It is a push model (built-to-stock) of manufacturing and volume-driven with a lack of variety.
The objective was to focus on efficiency and produce as much as they can, such that product cost can be cheap (Economies of scale).
TPS - Pull model
Insights relating to value streams, efficiency (reduction of "waste"), continuous improvement, and standardized products can most likely be traced back to the beginning of mankind. However, Fredrick Taylor and Henry Ford documented their observations relating to these topics, and Shigeo Shingo and Taiichi Ohno applied their enhanced thoughts on the subject at Toyota in the 1930s. Ohno at Toyota brought the concepts together, and built on the existing internal schools of thought, and spread their breadth and use into what has become the Toyota Production System (TPS).
Levels of demand in the postwar economy of Japan were low; as a result, the focus of mass production on the lowest cost per item via economies of scale had little application. Having visited and seen supermarkets in the United States, Ohno recognized that scheduling of work should not be driven by sales or production targets but by actual sales.
Given the financial situation during this period, over-production had to be avoided, and thus the notion of "pull" (or "build-to-order" rather than target-driven "push") came to underpin production scheduling.
Industry 3.0 ( ~1970 ) - Automation ( Electronics and Computers ) and Globalization
Electronic devices, such as the transistor and, later, integrated circuit chips, made it possible to more fully automate individual machines to supplement or replace operators. In parallel, software systems have evolved.
The theory of constraints (TOC) is an overall management philosophy introduced by Eliyahu M. Goldratt in his 1984 book titled The Goal, which is geared to help organizations continually achieve their goals. TOC is a management paradigm that views any manageable system as being limited in achieving more of its goals by a very small number of constraints. There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization around it.
TOC adopts the common idiom "a chain is no stronger than its weakest link".
This means that processes, organizations, etc., are vulnerable because the weakest person or part can always damage or break them or at least adversely affect the outcome.
The underlying premise of the theory of constraints is that organizations can be measured and controlled by variations on three measures: throughput, operational expense, and inventory. Inventory is all the money that the system has invested in purchasing things that it intends to sell. Operational expense is all the money the system spends in order to turn inventory into throughput. Throughput is the rate at which the system generates money through sales.
TPS is translated into "Lean" 1988 by John Krafcik when he coined the term "Lean" in his 1988 article, "Triumph of the Lean Production System". The article states: (a) Lean manufacturing plants have higher levels of productivity/quality than non-Lean and (b) "The level of plant technology seems to have little effect on operating performance". According to the article, risks with implementing Lean can be reduced by: "developing a well-trained, flexible workforce, product designs that are easy to build with high quality, and a supportive, high-performance supplier network"
In the late 1970s and early 1980s, the developed countries of North America and Western Europe suffered economically in the face of stiff competition from Japan's ability to produce high-quality goods at a competitive cost. For the first time since the start of the Industrial Revolution, the United Kingdom became a net importer of finished goods. In the United States as part of its soul-searching, companies began reexamining the techniques of quality control invented over the past 50 years and how those techniques had been so successfully employed by the Japanese. It was in the midst of this economic turmoil that TQM took root.
Six Sigma (6σ) is a set of techniques and tools for process improvement. It was introduced by American engineer Bill Smith while working at Motorola in 1986. Jack Welch made it central to his business strategy at General Electric in 1995.
A six sigma process is one in which 99.99966% of all opportunities to produce some feature of a part are statistically expected to be free of defects.
Six Sigma strategies seek to improve the quality of the output of a process by identifying and removing the causes of defects and minimizing impact variability in manufacturing and business processes. It uses a set of quality management methods, mainly empirical, statistical methods, and creates a special infrastructure of people within the organization who are experts in these methods. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has specific value targets, for example: reduce process cycle time, reduce pollution, reduce costs, increase customer satisfaction, and increase profits.
Pressure to reduce costs caused many manufacturers to move component and assembly operations to low-cost countries.<
The extended geographic dispersion resulted in the formalization of the concept of supply chain management.
WWW and the internet helped Globalization which has enabled outsourcing of workforce and Funding offshore (FDI). Many jobs from developed nations started bangalored. China and India certainly have taken advantage of this in Manufacturing and IT sectors respectively.
China’s emergence as a manufacturing powerhouse has been astonishing. It was in seventh place, trailing Italy, as recently as 1980. But by 2011 China not only overtook the United States but also became the world’s largest producer of manufactured goods.
India’s IT revolution saw export from IT services grow from a paltry $3.5m in 1980 to over $100 billion.
After the Y2K bubble, ERP, PLM, and CRM IT systems rolled out and have accelerated in bringing cost control measures and certainly started eliminating some white-collar jobs. During the end of the era, Robotics, Automation in the manufacturing line started replacing blue-collar jobs as well.
These enabled humans to plan, schedule, and track product flows through the factory.
Industry 4.0 ( ~2010 ) - Digitalization
IoT (Internet of things) is being used along with manufacturing techniques to enable systems to share information, analyze it and use it to guide intelligent actions.
It also incorporates cutting-edge technologies including additive manufacturing, advanced materials, 3D Printing, Robotics, AI, ML, AR/VR, and other cognitive technologies.
During this era, the Software Industry itself is going through a technology revolution especially driven by AI. Apart from that technologies like Mobile, Cloud Computing, Collaboration platforms, ALM and DevOps and Blockchain have evolved significantly.
Change in Consumer Behavior
Internet brokers ( software platforms as a business marketplace ) like Amazon, Uber, Netflix have grown tremendously.
"Data is the king" ( or key ) is the new mantra for businesses.
All technology giants like Google, Facebook, Amazon, Microsoft, Apple are striving to collect user data and to derive consumer behavior which has drastically changed businesses.
Consumers have moved to mobile-first, habituated to virtual shopping and quick door delivery, moved from wants to desires ( brands ), explore for variety with a low-cost buying option, and don't expect salespeople.
Every company is now technically a digital company. In order to differentiate, businesses ( including commodities ) started trying to provide personalization. Internet brokers already started this with the help of digital marketing and generating personalized content.
Every business started and went or going through a digital transformation journey which is a necessity for business sustenance.
Industry 5.0 ( ~2030??) - Personalization
It is not very clear whether 5.0 has already started or if it is yet to start.
It is evident that the future will be targeted for personalization. To achieve that, businesses will go for variety more than volume.
At the same time, it can’t become service ( Engg-to-order ) as that will increase manufacturing lead time. Customers don't have the patience to wait. Hence what is required is Volume and Variety. It is time to move from Economies of Scale to Economies of scope or coexist.
Dealing with Volume and Variety?
Global effectiveness can be achieved only with Integrated digital systems implementation.
At present, the R&D cycle for products is quite long with some exceptions. Agility to design along with component design; shall be available as part of the integrated digital system. Customers should be able to place orders through mobile or distributor channel partners and have to be sent to CRM ⇒ PLM ⇒ ERP with tighter Supply Chain integrations.
Assuming that currently, fully automated or semi-automated plants are positioned to produce volume at low cost, optimization of the production is not for the volume but for volume+variety (Assemble-to-Order).
First, the Lean implementation for manufacturing plants or production lines shall be a must. Quality shouldn't be a goal. It should be in the DNA.
Software systems shall evolve to map manufacturing production lines digitally; with the capability/potential of production for different processing centers by using value stream techniques and node/graphic representations. The theory of computation deterministic models and finite automata needs to be applied. ML algorithms will not only be limited to determine predictions but shall also be able to send production scheduling instructions (balance supply and demand).
Two big brands certainly come to my mind. DELL and ZARA. Both deal with high volume and variety.
Technologies like IoT, AIML, Cloud, AR/VR, Mobile, 5G/6G, 3D Printing, and Cognitive science along with Integrated IT systems (CRM+PLM+ERP) together are going to change a lot of things from efficiency to effectiveness.
A significant reduction of blue-collar jobs and a decent reduction of white-collar jobs might be inevitable. Countries, especially developed nations, will try to promote localization considering the rise of unemployment problems.
What are your thoughts?
Note: The content from Industry 1.0 to 4.0 is consolidated from different sources based on the headings that I have chosen.