Jan 20, 2010 | Change, OE, Operations
It is generally accepted that Henry Ford was the first to automate production along a line, dramatically increasing productivity and reducing costs as a result.
Not the case.
There were remarkable instances of mass production much earlier, the most interesting and perhaps least known is the Venetian Arsenal, in the 1300’s, as well as Guttenbergs printing presses, and Springfield rifle manufacturing in Virginia in the 1860’s. All are well documented, classic examples of production line techniques, specifically, one-piece flow, that emerged well before Henry arrived to take the credit.
Shows again, that there are very few genuinely new ideas, and there is much to be gained by understanding where we came from, as well as where we are going.
Jan 17, 2010 | Management, OE, Operations
Machine utilisation and machine efficiency are probably the most commonly used KPI’s used to measure the performance of factory management. Both serve a purpose, but they do not by any means describe the “whole”.
The factor that completes the picture is “flow”, the state where product “flows” uninterrupted from one process to another, at a rate dictated by demand from the market.
Most factory managers know instinctively, if not by data, that their factories run best when there is uninterrupted flow through the processes, but if they are measured on machine efficiency, (production units/time) as they often are, they will be pushed to maximise the efficiency of individual machine points, building up inventory elsewhere, and interrupting the flow, and compromising the productivity of the factory.
The measurement of efficiency of individual points of a production process is ingrained, it is a fundamental part of the cost accounting and investment disciplines we all take for granted, but badly needs to be re-thought and taught to emerging operations and general management.
Jan 4, 2010 | Change, Management, OE, Operations
Over many years, the best marketers I have come across have been trained as scientists, in a wide range of disciplines, many had no formal marketing training.
Took me a long time to figure it out, the scientifically trained people had as a part of their automatic response, a systematic process of collecting data, forming a hypothesis based on the data, testing it and looking for inconsistencies in the results, then forming a further hypothesis based on the better data to test. Kaizen or “continuous improvement” by another name.
It was an automatic, built in response that works really well in a marketing environment, particularly where many marketing people are inclined to see a problem and jump straight to a conclusion based on what has worked in the past, rather than a detailed examination of the root causes of the problem.
As I write this post, I am reflecting on the role of the “automatic” response being one that seeks to understand the cause and effect relationships underlying a problem, and how little we know about how to make our businesses embrace it across all functions and all challenges.
That would lead to systemic Kaizen, and should prove to be a potent competitive tool.
Nov 4, 2009 | Management, OE, Operations
It is a truism that if you can’t measure it, you can’t manage it.
Largely those who have practiced measuring and then managing for improvement have done well, Toyota with their TPS have taken over the world auto industry, and 6 Sigma, first embraced by GE has driven huge benefits to many.
However, it can be taken too far, the measurement mania that I have seen taking hold can be counter productive.
Two rules:
Measure only what ,matters
Use the measurement to improve .
Too many measure everything as a routine, but with no improvement strategy, nothing really matters as no improvement takes place, others measure stuff that is irrelevant in the scheme of things because it is easy, leaving unmeasured and unimproved the drivers of value.
Oct 20, 2009 | Leadership, Management, OE, Operations, Small business
Yesterday, I wrote about the process jig-saw that supports an implemented ERP system as it works to drive efficiency, but deliberately left out the hardest bit.
The most challenging changes necessary to make an ERP implementation deliver the value promised are the behavioural ones.
You can buy all the software in the world, but junk-in still generates junk-out.
Most ERP systems I have seen, if you take a wide view of what constitutes “ERP” is done on Excel. I have developed simple routines for SME clients using Excel, that whilst not fancy, automate parts of the operations planning processes, and generate substantial benefits.
Most sophisticated systems from the well known SAP to less fancied packages all have large chunks of data delivered by to them by a range of means, mostly spreadsheets, and the temptation for the individual is to leave well enough alone, and resist the dropping of their routines in favor of the expensive ERP package. Allowing this parallel system to survive beyond a short validation phase is always a mistake, as people revert to what they know as soon as there is an issue. When you jump in, you need to go all the way.
Oct 19, 2009 | Management, OE, Operations, Sales
Talking to a client last week about his S&OP processes, (or lack of them despite the software) I realised that we were both using English, but were talking a different language. This is often a challenge in S&OP implementations, and even amongst those who have successfully implemented in different businesses, as a local jargon usually emerges to accommodate the vagaries particular to the organisation, product type, and culture.
Following is a simplified list I gave to him as a basis from which the conversations could be translated, in the common order of S&OP preparation.
- Demand planning. A compilation of data (past sales, orders received & delivered, orders received and undelivered) and qualitative data from the marketplace (competitive activity, accounts won & lost, distribution changes, seasonal influence, and so on). This is not a forecast of what will be sold, it is a quantification of the influences on demand. This data is assembled in a huge variety of ways, often collated by the “Master Scheduler”, but not ideally to avoid capacity bias emerging too early, and the sales/customer management function, and operations management.
- Forecasts. A suite of forecasts for product families rolled into a consensus outlook based on the output of the demand planning process. At this stage it is unconstrained by questions of capacity & input availability. This is usually a specific role held by an individual, often titled “Master Scheduler” and is an ongoing responsibility, but signed off weekly for submission to the Capacity & planning meeting.
- Capacity & supply planning meeting, normally weekly. Puts the acid test of reality on the sales forecasts by adding the capacity and input availability constraints. The output is the daily/weekly production schedule to be executed based on the requirements and trade-offs/compromises that emerge from the more senior SOP processes.
- Pre-SOP. A meeting (normally bi-weekly) of the implementation level of management that makes the trade-offs and decisions that emerge from the Pre-SOP, ready for implementation, and identifies strategic resource allocation issues for resolution. This is the key meeting, and provides input to the senior S&OP meetings, and the capacity & supply planning meetings
- S&OP sign-off by senior management, normally monthly. Over time in successful implementations this becomes a rubber stamp on most occasions, but it retains the control of major decisions that need to be made that have more of a long term and capital utilisation impact than is available to the Pre-SOP management level. Things like new equipment, outsourcing, choices between major customers, contractual compliance, shift additions, and so on are usually signed off at this level.
