To operate, a company needs to create profits. There are two macro factors on which we can work to improve this: the increase in revenues and the reduction of costs. In both cases, I need to know the details of the current situation, compare it with the goals I have set, and define what actions will lead to their achievement. To obtain this purpose, KPIs play a fundamental role. Let’s see what they are and how to make the most of them for improving business results.
Measuring for improving
KPI stands for Key Performance Indicators. These are numbers that I measure, not more-or-less subjective judgments. I want to quote Lord Kelvin (nineteenth-century scientist and engineer) “If you can’t measure something, you can’t improve it.” Certainly, this statement is very strong, but it contains a truth. The first step for improvement is to have objective values ??that show the state of a process, otherwise, the risk is to have the feeling that things are in a certain way when in reality it is not so. And the numbers above all let me know for sure if I’m improving and how much. This does not mean that these indicators are the solution to all problems or the magic wand that makes things better. People’s intuitions and ideas remain the key to improvement, but with targeted and well-made measures, you have at your disposal a very powerful tool to stimulate ideas and measure the goodness of the changes that are taking place.
A method to be more efficient
A KPI can be any measurable parameter, which gives me useful information on the performance of a business area. In most cases, it is not a thing in itself, but is part of a method. Below we outline the fundamental points, which we will then analyse one by one.
- Define the area to be monitored and improved (e.g. finance, marketing, production, logistics, quality, sourcing, etc.).
- Choose the objectives and the indicators that best describe them.
- Measure the state of the art and quantify the objectives.
- Define a frequency for comparing the indicators with the objectives.
- Maintain and implement a list of practical actions to bridge the gap between measured and desired values.
1. Define the area to be monitored and improved
Surely the first step is to decide where I want to take action. In case of a start from scratch, it is better to begin with only one business area and focus on that until you master the method and start seeing the first results. Starting too many things all together is confusing and normally you cannot follow them all effectively. If there is an area clearly more in difficulty than others, you can start from there. Otherwise, it is advisable to first choose an area where there are more skills, or where there are people who manage it who have more aptitude for change. This will lead to have earlier results and stimulate change in other areas. If I can put a positive example in my pocket quickly, it will be easier to convince those who are more reluctant to take this path.
2. Choose the objectives and the indicators that best describe them
The direction we often take is to do our best to improve something as much as possible. Although it seems a very positive approach, it hides a problem: the lack of a clear goal. In its absence, it is easy to get lost and go in different directions without hitting the target. In addition, you may have the feeling that you have done a lot, but the concrete results may be small or even absent. This is why it is important to define from the start where you want to go and define it objectively, with numbers, so you are sure that it will be clear for anyone. Furthermore, a goal should not be too complex unless it is really necessary.
Practical examples of objectives and related indicators
Let’s try to give practical examples of possible objectives. In the production field, I could set the goal to be more efficient, therefore reducing costs. But as we said before, I have to find measurable and easy-to-obtain indicators. One can be the ratio between the hours sold (used to cost the product) and the hours actually spent. Or the ratio between the productive hours and the hours of the presence of operators. In the first case, I see if I am taking more time than the budget and I can react by looking in detail at the production process. I might discover that I was wrong in budgeting, but there is no guarantee that I can sell my product at a higher price, so, I have to understand how to reduce the time cycle. Or I could see that the estimate was correct, but there is a problem in the process that slows it down and, consequently, I act to remove it. On the other hand, in the case of the ratio between productive hours and presence hours, I might notice that the work is not well organized and the operators spend a lot of time around looking for what they need, taking time away from production.
Let’s move on to another example in a different area, sales. In this area, I could opt for three macro objectives: the annual sales, that might be divided by geographical areas; the minimum margin on orders, and the number of new customers in the year. In this case, in addition to having indicators that measure these three values, I can decide to add some more to better identify possible problems. An example would be the ratio between the number of orders and the number of offers, broken down by geographical areas. This would help me understand if in some countries they are interested in my products, but maybe my pieces are not competitive enough. I could take aimed actions or decide to drop one country to put more focus on another.
Every company and every business sector has its features. It would be ineffective to try to define standard objectives that can be suitable for everyone. Except for the more general ones, such as production efficiency, percentage of scrap, value of sales, stock value, up to the economic and financial ones. But to be really effective you need to be well-aimed, a good approach is to look at your company in a detached way, trying to ask yourself as many questions as possible about all the improvement areas and always questioning habits. One of the best approaches is to ask the opinion of someone external. Not because he or she is more competent than we are, but simply because we no longer see many things that have become normal. A person who sees the factory for the first time notices many more things and helps us to see them, as well as bringing a different point of view that almost certainly contains positive ideas.
The combination of indicators
There are two reasons to combine indicators, the first is to aggregate micro objectives and make them become a single higher-level objective. In this way, we can adapt the monitoring to all company levels (this topic will be further explored later). The second reason is to obtain reliable indicators. Let’s take the example of production. If the operator does not record the productive hours correctly, we could see a budget hours / actual hours indicator fairly high. But the reason could be that the hours recorded are less than the ones actually spent. In the same way, I could see the indicator productive hours / presence hours high, but, as happened before, because the productive hours have not been recorded correctly, in this case in excess. However, if I create a third indicator which is the product of the previous twos, the result will always tell me if there is a problem, even if it is “hidden” by one of the two indicators. As we have seen, in the first case the error is the productive hours lower than reality, instead, in the second case, the productive hours are higher than reality. This means that if one of the two indicators erroneously (or unfortunately, sometimes voluntarily) becomes better, the other will get worse, therefore in the third (the combination of the twos) the error is canceled out and I see a reliable value. Keep in mind that this method works if I have only one potentially unreliable parameter.
Making measurements automatic
In cases where the potentially incorrect parameters may be more than one or in cases where I cannot apply the combination of indicators to cancel the errors out, a solution is to switch from manual to automatic detections. Today, technology allows for automatic measurements and data management at very low costs. These systems can potentially be applied to all machines and lines, even the most obsolete ones, by equipping them with the missing sensors. In this way, not only I always have reliable values ??without the errors or manual system forgetfulness, but I eliminate the cost of hours spent by employees to collect data, enter it into a computer, create reports, and so on. They also allow the detection and processing of an amount of data that would not be possible to process manually. This last feature is causing a real revolution in the way companies are managed and, as computers did in the 80s, it is taking us into a new era.
The use of moving averages
Sometimes, the single collected values are too variable or lack information to be meaningful when read individually. For example, if every end of the day we detect the productivity of a machine that works 8h a day, we can have days when it is low because the machine could have not finished the last piece within the day. If the pieces had a long cycle time, e.g. 3h, the machine would finish 2 pieces in an 8h-shift. Therefore, the productive hours recorded at the end of the shift would be: 2pcs x 3h = 6h and the productivity would become 6h / 8h = 75 %, but in the last 2h the machine worked. There are two ways to overcome this problem: not measuring the productivity on the basis of the number of produced pieces, but on the number of effective productive hours of the machine (also for this, the automatic data collection systems come in help), or calculate the moving average of a reasonable period, which in this case could be a week. The average filters the single anomalies, giving us more reliable values.
The moving average is nothing but an average that is recalculated at each new incoming value over the period I have chosen. Going back to the example above, at each end of the shift, in addition to recording the value of the day, the average of the last 5 values ?is calculated and recorded ?(assuming to work 5 days a week). This is done every day, so we will have two sets of numbers: one of the daily values ??and the other of the averages of the last 5 days. If we imagine it on a graph, we can see the moving average as a smooth curve compared to the “sawtooth” curve of the single-day values.
3. Measure the state of the art and quantify the objectives
To quantify future goals, we must first know what the current situation is. A key feature of a goal is that it must be achievable. Otherwise, it would not give us a big added value, we would only be frustrated by the fact that we cannot get there and at some point, we would let it go. A future goal must be a reasonable percentage increase in today’s values. For example, if today I have the production hours / presence hours indicator at 78%, it does not make sense to set the goal at 100% to be reached in six months. First, because it will never be 100%, I have to count people’s breaks; secondly, because things do not change overnight, but are processes that require time and perseverance. It would be much more reasonable to target a 5% increase, which, in six months, could already be challenging. A small constant increase over time is better than trying to climb Everest and giving up because it is too hard.
4. Define a frequency for comparing the indicators with the objectives.
KPIs are very useful tools for identifying problems and helping us to improve. But we must avoid falling into the trap of turning them into numbers that I collect when I have time and, after they are collected, I throw them in a drawer to look at them one day that will never come. The best method is to schedule periodic reviews, involving people who have a responsibility for those goals. If we want to achieve results, the two priority and strictly necessary characteristics are determination and perseverance. Sometimes we see situations where the method is not exactly the best, the skills might be higher and the ideas are definitely not outstanding, nevertheless, the result has come. Normally in those cases, determination and perseverance were so strong that they made up for those shortcomings. Don’t get me wrong, I don’t think that these two characteristics alone are sufficient (skills, method, and good ideas are very important), but I mean that they are an ingredient that cannot lack if we want to reach the result and to get there in a reasonable time.
5. Keep and implement a list of practical actions to bridge the gap between measured and desired values.
During these periodic reviews, we need to check where there are gaps between indicators and targets. Whenever we find an indicator that is not going as we expected, we must try to list the possible causes. Let’s go back to the previous example, the productive hours / presence hours. If this indicator is lower than what we have set, some of the possible causes may be a lack of raw material for the machines, malfunctions of the machines that cause too many stops, operators doing unnecessary activities, etc. To list the causes, there is nothing better than carefully observing the workstations for a while, at least until the main problems have been identified. Then, with automatic detection systems, we can have constant and precise control, but in the early stages, a direct presence is always preferable.
The second step is defining actions that will lead to improvement. These actions must be short-term. If we think of something in the medium or long term, better to divide it into short actions, which we can do and verify within the next revision. They must be practical. We must always stay grounded and do concrete things that we know how to do. They must bring a substantial advantage. At least at the beginning, let’s focus on actions that bring a sizeable result and leave the details for a second phase. For each action, we must always define one person in charge and a deadline. In most cases, defining two or more persons is equivalent to defining no one and there is a high risk that the action will not be completed on time. Lastly, let’s never forget to write down everything we define to do, with the features we have just listed, and to share it with everyone involved. This will avoid any misunderstanding or forgetfulness.
How to aggregate KPIs to obtain different levels of detail
According to the size and structure of the company, it can be necessary to make a sort of KPI tree. The managers of specific areas will use specific indicators, but as we go up into the company structure, more aggregate indicators are needed. They must give an overview of the area to the upper level, this up to the general manager. Assuming that all indicators are ratios (therefore dimensionless percentages), we can aggregate them by calculating the average. It is always better to also define a weight for each indicator, because not all of them have the same impact. For example, if productive hours / presence hours = 78%, production budget hours / production actual hours = 89% and packaging budget hours / packaging actual hours = 86% and I estimate that the impact of the packaging is small compared to production, I can decide to give it less weight. In this way, in the aggregate I give more importance to the other two indicators. The calculation could be: (0.78 x 1 + 0.89 x 1 + 0.86 x 0.3) / (1 + 1 + 0.3) = 0.84. In this case, we decided that the packaging weighs 30% and the others 100%.
Another method that can be applied is to directly multiply the ratios (as we did above, even if the purpose was different). In this way, the negative effects are not mediated, but added together and the aggregate indicator becomes more sensitive to inefficiencies. Again it might make sense to use different weights for different indicators, but being a product and not an average, we have to do it differently. Suppose that, as before, I want to give a weight of 0.3 to the third indicator. First, we have to find the coefficient “C” of this weight, to be multiplied by the third ratio “R” (packaging budget hours / packaging actual hours). It will not simply be equal to 0.3 as in the weighted average, but to obtain it we must apply the following formula: C = P x (R – 1) / R + 1 / R, where “P” is the weight I want to give to that KPI. Therefore in our specific case it will become: C = 0.3 x (0.86 – 1) / 0.86 + 1 / 0.86 = 1.114 and this is the coefficient to be multiplied by the third indicator in the aggregation formula: 0, 78 * 0.89 * 0.86 * 1.114 = 0.67. The result is an aggregate KPI equal to 67%. As you can see, it is significantly lower than the same indicator calculated with the weighted average, which was 84%. You can choose the method you prefer, as long as you use the same method also to aggregate the respective objectives, otherwise, we would compare apples and oranges.