- Datumize CEO
The greek word katapeltes originally stood for “shield-piercer” (kata= “through,” + pelta = “light infantry shield”), and this was how the first catapult machines were used. Catapult was optimized based on data and information, although it’s worth mentioning that the instrument evolved over the centuries until it finally became very sophisticated. Eventually, though, it was defeated by powder and gunfire. Like it or not, weapons and wars have been (and continue to be) the primary source of fundings and inventions for information technologies. Let’s analyze why this is the case.
Within the discipline of History, the history of technology is one of least prolific branches, although there are excellent museums and institutions completely dedicated to the amazing development of technology that humanity has been encompassing throughout the centuries. The Deutsche Museum in Munich claims to be the largest in the world. As an engineer, I should confess that when I visited it for the last time, I was deeply impressed by the quantity and quality of its exhibitions. During my visit, my kids were the ones asking me to hurry up for lunch, while I was completely “abducted” by the history of computers.
There has always been a controversy in academia about the classification of technology historical ages. One of the classifications that I personally find quite accurate is the one depicted at the impressive “An Encyclopedia of the History of Technology” book edited by Ian McNeil in 2002. This classification is based on the existence of seven somehow overlapping ages:
- 1. Fire (nomadic hunters-gatherers craft tools and weapons from wood, bone, or stone; they generate and control fire);
- 2. Metal (emergence of farmers, blacksmith and wheel);
- 3. First machines (e.g., clock and printing press);
- 4. Early Steam Automation;
- 5. Full Industrialization;
- 6. Combustion Engine;
- 7. Electricity and Electronics.
The encyclopedia not only discusses these ages, but also describes in a great detail materials, power and engineering, transport, communication and calculation, as well as the close relationship between technology and society. Special attention should be paid to the chapters on weaponry and information technology: timekeeping, computing, telecommunications and audiovisuals.
According to McNeil, “information technologies ( including communications) may be regarded as extensions of human sensory-motor capabilities. In particular, sight, hearing, memory, speech, and manipulative skills, such as writing.”
The very first thought on the definition of information technologies is the one that encompasses human senses, especially, sight. Nowadays, when we refer to conclusions or understanding of a complex situation, we use the word “insight.” The first pictorial representation of a concept (hunting), to be perceived by sight, was discovered in Altamira caves, Spain, dated back to 8000-3000 BC. Information is highly related to the ability to communicate, or transmit a message. Memory, speech or writing are good examples too. As knowledge started relying not only on oral transmission for future generations, initial information technologies included paintings on the walls or stone.
When it comes to computing (or counting), I enjoy quite a lot tracing back current situations to the previous times, when the information was either not available or not used. Information has always been there. The fact is that counting, on a massive scale, is a relatively new discipline (original term “counting” gradually transformed to “computers”, that was a trigger for creating IBM). Traditionally, people and businesses counted everything they could on ten fingers (abacus), and, eventually, would keep all the information in the books. It was not until 1600 that Napier came with algorithms, and as early as in 1642 Pascal promoted a primitive mechanical calculator using gear wheels. A sort of punched cards was invented in 1805 by Jacquard as a language to instruct weaving machines. It was not until the 20th century that electrical calculating machines were developed. Since the introduction of electronics and transistors, as well as the observation of Moore’s Law, the level of complexity, sophistication and innovation unleashed through computer science has outpaced any forecast.
Even considering the huge improvements in computer science applied to many disciplines and aspects of human beings and activities, it turns out that the whole industry - the one that significantly changed our lifestyle across centuries, the one that apparently should be backed up by high-end technology, computers and data, the one that allowed humans to launch satellites and explore space - is still struggling to understand how most of the manufacturing machines are doing. According to Cisco, up to 92% of world machines are not network connected.
Let’s do a quick journey in time and place ourselves in one of the campaigns led by Alexander the Great, around 334 BC, in one of the many sieges that resulted in the cities’ conquest. Themistokles, the upper rank official, and Menelaos, one of the soldiers deployed to a catapult (or katapeltis), are having the following conversation:
- Themistokles: Menelaos, is everything ready?
- Menelaos: I think so.
- Themistokles: What does that “think so” exactly mean?
- Menelaos: It means that I had a look and all seems fine.
- Themistokles: How many hits did we get yesterday?
- Menelaos: The reporter has not yet counted the results. I told him this morning.
- Themistokles: And how much was that?
- Menelaos: I don’t remember, that’s why we have a reporter.
- Themistokles: (sigh) And when is the reporter providing the results?
- Menelaos: I don’t know either.
- Themistokles: (double sigh) Fine. (long pause) Let’s focus on today. Have you adjusted the katapeltis for what distance and stones?
- Menelaos: The specialist came over this morning, he said it was fine.
- Themistokles: (slightly anxious) It can not be fine because we have moved since yesterday.
- Menelaos: (looking aside) Listen to that. Seems that headquarters and calling officials in for reporting.
- Themistokles: (really anxious) I do not have any result to explain!
- Menelaos: (sitting down) Ask the counter.
Now, let’s do a quick jump of 2353 years into 2019. We are in a factory assembling power trains and gear shifts for the automotive industry, also in Greece. Dimitris, the official in charge of one of the lines, and Petros, one of the many operators in the line, are having this conversation:
- Dimitris: Petros, is everything ready?
- Petros: I think so.
- Dimitris: What does that “think so” exactly mean?
- Petros: It means that I had a look and all seems fine.
- Dimitris: How many products did we get yesterday?
- Petros: The computer has not yet calculated the results. I looked this morning.
- Dimitris: And how much was that?
- Petros: I don’t remember, that’s why we have a computer.
- Dimitris: (sigh) And when is the computer providing the results?
- Petros: I don’t know either.
- Dimitris: (double sigh) Fine. (long pause) Let’s focus on today. Have you adjusted the machine for the supplies?
- Petros: The specialist came over this morning, he said it was fine.
- Dimitris: (slightly anxious) It cannot be fine because we have reconfigured since yesterday.
- Petros: (looking aside) Listen to that. Seems that headquarters and calling managers in for reporting.
- Dimitris: (really anxious) I do not have any result to explain!
- Petros: (sitting down) Ask the computer.
More than three thousand years have passed on and we are still having arguments related to the lack of data. Although it is sort of a fun dialogue, the following legend shows why data is still the main blocker for an efficient factory:
- hits = products
- reporter = computer
- count(er) = calculate
- katapeltis = machine
- distance and stones = supplies
- official = manager
- move = reconfigured
According to the recent Forbes article on the levels of data in factories and the similarities between optimizing a catapult and a factory of today, it seems that we’re still finding the route to initial levels of efficient data capturing and sharing.
