Time Tracking in the 21st Century – Part II

(the screenshots and terminals in this article come from the KELIO systems that we distribute)

In the first part, we looked at how analytics works, what it actually means and how the information can be collected into the time tracking system. In this part, through a few concrete examples, we examine the practical application.

Case study 1

The company in our first example is a metalworking firm engaged in manufacturing, with blue-collar workers in the plant and a few office employees. Management wanted to see when the employees arrive at and leave their workplace, and also what tasks they work on in between. There are tasks that require more highly skilled workers, while for others one or two semi-skilled workers – with a significantly lower wage cost – may be enough. The goal was to plan the shifts more efficiently and to match the ratio of skilled and semi-skilled workers to the nature of the task to be performed. It was also a requirement that the system could not be “cheated” – i.e. time data or tasks could not be recorded in someone else's name. The system had to be very simple and user-friendly, taking into account the needs of blue-collar workers. In addition, of course, the terminals placed in the plant had to withstand the working conditions: for example the cold and the heat, the dust and even the paint dust.

Smart terminals were placed in the plant, where after identification the employees only had to touch an icon to select the symbol of the given work process and the project. This all takes a few seconds, and since the icons are large and colourful, the selection is extremely simple and requires no IT skills whatsoever.

After the initial reluctance, the employees quickly got used to using the terminals. In the first weeks, we refined the interface based on their feedback, and after a few weeks we were already able to prepare very detailed analyses.

Evaluating the results

First of all, we needed information on which employee spent how much time for which client on which work process. All this can be easily extracted from the system and compared with the original schedule. After evaluating the results, the planning for the next period can be adjusted or fine-tuned.

The next extracted data set shows the total working hours by customer and their distribution by task. What stands out at first glance is that for customer 4, the “idle time” of the employees (which here accrues into a so-called overhead hour) is almost the same as for customer 1, even though significantly less time was devoted to this client.

Further analysis of the data revealed that for this customer not all the raw materials were available for producing the end product, which is why the idle time increased. This can be remedied with better work organisation.

Case study 2

The company in our second example is a firm offering accounting services. In this case the environment is considerably simpler: there is no need for terminals because every colleague works on a computer.

The owner asked us to make it measurable for them how much their employees work for which companies. This data is important so that they can compare it with the amount they invoice to their clients. In several cases it had come up that the invoiced amount was smaller – or not much larger – than the cost of the time devoted to the given client. But these were only gut feelings until concrete statistics were prepared about it. There are clients who send their documents on paper, which are therefore often incomplete and arrive late. In addition, other requests occasionally come from them that tie up significant resources of the firm's colleagues. Another important piece of information is that previously the monthly fees were mostly determined on the basis of the number of invoices. Now let us see how analytics helped in this case.

The accountants do not simply record when they started the day and when they finished it; they click on a predefined button in the time tracking system, which may mean, for example, “I am entering invoices for company A into the accounting system”. Once they finish this task and start another one, they simply click on another button (“I am analysing the transfers for company B”). This starts the measurement of the time spent on the new task, while the measurement of the previous task is automatically closed. The owner predefined the tasks that the firm can perform; the colleagues can choose from this list.

It is also possible to record a workflow that was not predefined – in that case the accountant types in themselves what task they worked on.

Let us review the analyses of the first month:

The first chart compares the cost of the colleagues working with the clients with the revenue received from the given company:

Here DBAC Zrt. deserves attention, since a very large amount of time – and with it, cost – is devoted to them, while the revenue is only minimally higher than in the case of BCDA Kft.:

Let us compare the work devoted to the two companies and its cost.

The following charts show the analyses of the two companies mentioned above.

BCDA Kft. shows a healthy ratio with adequate profit:

Analysing the second chart, an activity stands out that was only 2% of the time spent in the case of the previous company: the telephone consultation.

Analysing the tasks, it can be established that the telephone consultation was carried out by a colleague with tax expertise, whose hourly rate is therefore higher than that of another accountant colleague. For this client, the number of invoices cannot be the basis for billing, so individual pricing must be applied in order to achieve adequate profit. The information extracted from the software can be saved in PDF format at any time and can even be used as an attachment to the invoice.