Data Analysis and Generating Insights

Transcript

Idit: Welcome everyone, on today's episode we'll be talking about data analysis and insights. The whole world of control and feedback. We'll learn some basic concepts, and we'll discover why it's not enough just to deliver the service, but we also need to measure, monitor, and reflect it all back to the customer. On all of this and more we will be talking with our guest today Einav Tsabari.
Einav is a customer manager on an integrated project in the group. Einav has extensive experience in the field, and he has undergone countless trainings and is familiar with all the content areas of IFM, especially the areas of measurement and control. Einav and I have known each other for about five years, and we worked together in the past. Einav is someone who I knew could contribute a lot to the group with his knowledge and experience when I added him to my IFM team. So Einav, how are you? Thank you for joining us.

Einav: Hello everyone, I'm glad to be here.

Idit: Great, great to have you. So, before we start, as we normally go about it, what quote did you prepare for our listeners?

Einav: There is a very interesting quote that we actually bring from our sources. There is a quote that says "There is nothing to the judge, but what his eyes see." This is something that we really connect with, as we manage our daily routine with various decisions based on information we receive from our surroundings, from our family, and that is how we make decisions. And we really need to understand the issue of how to make a decision and based on what information is received.

Idit: Excellent, excellent. So, what is the concept of control in service metrics?

Einav: Yes, in fact, this is a world that talks about the interface or the language between the environment we manage and our customers. In fact, we come and say that in order for us to manage the assets or the service in a better way, we actually know how to come and draw information from the entire business environment, analyze it, and actually bring it to the point where we can work with this information and extract a lot of things we don't see.

Idit: Without a doubt, I think knowledge is power. I heard, we encounter the term KPIs a lot. What are KPIs?

Einav: KPI is a concept that we absorbed from the global business. These are very clear indicators that explain to both the customer and us how we are measured and when. This is a language agreed upon by both parties that we manage the business according to.

Idit: So, this is something that we define together with the customer. We decide on some set of parameters or set of indicators that will accompany the scope of the service that we provide to the customer? Or is it something that the customer decides for us? Does it change?

Einav: The ideal thing in all of this is to actually connect a set of metrics that is suitable for both parties and that can be implemented. Usually, this does not always happen, but usually the customer is the one who sets the tone and explains exactly what he wants and how. And sometimes they also ask for our professional opinion, and there are really times when we see that there are metrics that are put more emphasis on and on others less. And not always do we think that this is really right to do so.

Idit: I understand, in fact, from what you said that the whole issue of control and measurement is very important in order for us to be able to streamline processes, be able to extract any insights from the data we want, and the level of our performance. But I think about the teams of ours, the service providers in the field. For example, how do they feel about the whole thing that they know that we are monitoring their performance, and we also reflect it to them in one way or another? And on the other hand, also to the customer? After all, we can also be in a situation where we reflect to our customer data that is low-performance. How do we deal with this?

Einav: Yes, first of all, it's important to say that the analyzed information and data we finally get after professional processing, we have a duty to present and show it to our teams as well in order to engage them in the process. If we don't do this, they won't be engaged in the process and won't understand or know where they are or in what environment they are working. If they are doing the job properly or if they are performing their tasks and duties well and accurately. Therefore, I emphasize again, we also have a duty to present it to them and explain it to them. And that's the essence of data measurement, to close this loop between the teams and the data received from the field. And thus, we can truly do something with this data and not just measure ourselves.

Idit: It also makes sense because data is something that truly reflects performance, not just feelings. I mean, you could have an employee on the team who says, "Listen, I work from morning to night and handle a thousand calls," but we have a system that monitors and checks and actually sees their daily performance. So I think it's very difficult to argue with data when you see some data coming out of the system versus feelings or statements made by the teams. In my opinion, the data is much stronger, much more tangible.

Einav: Absolutely, it's very difficult to argue with data. The trick here is what additional data to add and how to analyze it and also how to present it.

Idit: How to present it, exactly.

Einav: I'll give you an example. Most companies always look for the red metrics that show dissatisfaction, non-compliance with SLAs, and so on... But I always say that you should always first, also look at the things that are working because there are a lot and all the time. And that's a mindset!

Idit: Absolutely. A mindset and also an approach, I think it's like we come with the approach of transparency to our client as our partner, also our low performance, the lack of performance is in a place where we need to come and improve, so here we reflect, we do some kind of lesson learned, we extract our insights and we improve accordingly. Therefore, it is a constructive tool. It's kind of a traffic light that how I see it is a very helpful tool in the service.

Einav: Absolutely, even when there are underperformance situations and we present it to the client or even within our own company, it means that we know how to measure the underperformance, it means that we are tracking the underperformance, and it means that we also have conclusions and insights on how not to be underperforming, to take ourselves to a better place. It sounds and looks completely different from the second option where people talk about feelings and talk about what we do know or don't know or let's check or all those types of answers. Today it doesn't work like that anymore. Customers today really know exactly what they want and when. And we need to meet those standards and when we get to a point where we are underperforming or dissatisfied, we immediately know how to come and say, okay, we are in a place that is less desirable and we are doing A, B, C, D, to bring us to a place much, much better. It sounds different, it looks different, and that's how a professional organization works.

Idit: It's a very focused response, not like putting out fires when we see an event and then come and deal with it, but we already anticipated it because the data really helped us to read the situation correctly. So, now, in terms of the technology or platforms that you know of that are used to perform all the measurement and monitoring, what are they?

Einav: That's a great question. In fact, anything that is connected to a network or any machine or any application that is connected to an asset, equipment, or team performance, we can extract a lot of valuable information from it, analyze it, and draw conclusions and insights for how to work with it. It's an art.

Idit: Is this a platform that is sometimes the customer's? Will we have to adapt to their system, or in some cases, can we add our own supporting system?

Einav: Definitely. The answer is both. Sometimes we have to use systems or extract data from existing systems. And sometimes we are required to bring our own technology with us or develop something specifically for that customer or work space. And again, it's an art, it's a specialty. We want and know how to take all this data, put it in a central location, process it with our experts. Everyone comes and takes the aspects that they understand better, and then we take all of these insights and create a work environment that is much more accurate and provides an uncompromising response to the customer.

Idit: Nice, nice. So, you know, there's no end to measurement. You can measure over a thousand parameters and countless things. So, what is actually the boundary between effective measurement and over-measurement?

Einav: That's also a great question. This is the topic that everyone in the industry is talking about. Where are we more, where are we less? So, it should work in several stages. The first step is to really define what I want to measure, when, and how. Together with the customer, together with our professional experts. And after that, after we build the first layer, we actually start working with it. And then we slowly see what we use more and what we use less.

And then we take more data that accumulates in the work environment from the customer, do a cross-check, and say if I am in a certain place in a very good way…

Idit: So, we put less focus on that, and more in another place. Working by ear.

Einav: We always have to come and challenge the system, challenge the thinking, challenge the measurement. It's not something that you just plug and play, you go out on the way and you're done, that's how you work. It doesn't work that way, we always have to challenge the method, how we measure, when, how much, and why. What is right today will not be right tomorrow, and that's the art.

Idit: And finally, we've been encountering the concept of AI a lot lately. How can artificial intelligence actually help us in this area of control?

Einav: In fact, this is a groundbreaking field. In fact, artificial intelligence and machine learning systems are trying to replace human thinking and inference.

Idit: There is a huge difference between human intelligence and something that is artificial.

Einav: Here we are trying to come and teach the machine or teach the environment, the interface, the machine, how to think in place of an expert or professional, and actually do the thinking work behind the scenes and already draw conclusions and insights during the measurement of the data. It's not an easy task, it's done in other parts of the industry. And today we do know how to come and take these capabilities and integrate them into systems, integrate them into the company's intelligence, and actually take the whole issue of measurement and control not one step, but ten steps forward, and transform from being in defense and response to an attack. And to be in the place we need to be in or before it happens.

Idit: Totally. To prepare ourselves for the new reality. Wow, that was amazing. Thank you very much, very enriching. Thank you for being here with us.

Einav: Thank you all and I was happy to be here. I am sure that this field will lead the organization to better and higher quality areas.

Idit: Definitely. Thank you, Einav.