108: Fireside with Chris Taylor

Charlotte Ward 0:13
Hello, and welcome to Episode 108 of the customer support leaders podcast. I’m Charlotte Ward.

Today I welcome back Chris Taylor for a fireside chat. I’d like to welcome back to the podcast today Chris Taylor. Chris, welcome back. You’re joining me today for a fireside and I believe, keep don’t have one in the room or even the building that you’re in. But you are doing me the grace of moving to a building with a fireside very soon, right?

Chris Taylor 0:50
This is correct. Yeah. I mean, I live in this old Victorian flat block right now. So there was a fireplace but it’s not in my house. And yeah, the new one. I’m moving to It’s blocked up, but I can make it work. You know, fake fire in there something.

Charlotte Ward 1:05
Awesome. We’ll come back for another fire. Another actual fire. I did some next to that one. So, with my fireside guests, they bring a topic to talk about. And I think you’ve got something you want to talk about today, right?

Chris Taylor 1:19
Yeah. So I think we can talk about planning for scale. What metrics you use, what numbers you look how I sort of approach it

Charlotte Ward 1:28
would be a good one. That’d be awesome. scaling is always difficult. So how early stage Do you want to begin? Where Where should we start? We start in the very beginning.

Chris Taylor 1:38
Yeah, I guess so. I’ll explain a bit about where we’re at in the business I work in now. So I work for tike. We’re in a management company. And we’re in our scale up phase. So growing out of being a little startup with 20 people, we’ve now got 270 staff, and I think by the end of next year, okay, and well, we’ll be at about 200 people in the business which is really awesome. Customer Service, luckily is one of the more predictable areas in my opinion. That means it’s slightly easier to scale. So I’ll go back into my history a little bit, I worked a big call centre. I used to have to plan and Manage Accounts and every year you have to refresh your budget to scale up or scale down. And what do you predict that on? How do you how do you forecast it? So in that environment, it was quite simple. We had marketing got sent out on certain dates, we knew when our peaks would be we knew when we would have lows, we could reasonably predict out of what marketing went out how many people would call in and compare. And then we knew roughly how long those calls were taking. So using all of that data, you can go the amount of calls times by how long they take, that gives you a figure and hours and you cut that down to say I need this amount of people at these times of day. But you might say you need say that example we used to get a lot was the first two days of our peak season, it would say we need 150 people, we’ve got a maximum staff of like, I want to say about 75 people. So on those days, were you really over what do you do with your staffing you bank hours and get people to work them back, you get overtime and stuff. But the initial part of planning for scale is how many people do I need? When? What contracts Do we need them on? Blah, blah, blah. So that’s kind of the call centre experience. Yeah,

Charlotte Ward 3:33
yeah, there’s a lot of variables there isn’t there you describe the seasonality and actually just dealing with the people side of this as well. Something you touched on was the scheduling around that because you can, you can plan all you want with lines on a spreadsheet, but if people can’t work the hours you need them to work when you need them to work them when you know when they’re on your payroll to deal with this, that seasonality and we’re stressed straying a little bit into season ality here and let’s go with it for now. That actually coping with seasonality as a as a, as a pattern in your business is hard and it’s a it’s potentially a sort of small, almost a microcosm of what you experienced as you scale up organizationally at a fast rate as well, isn’t it?

Chris Taylor 4:20
I would always recommend to look at the seasonality. There’s this concept called volatility, which is from your average customer service baseline, how, what percentage up or down versus that, can you go and that’s how volatile your demand is. So in travel, you’ve got two big buying seasons a year which lasts about three weeks each. And you know, in those times you’re going to be hammered. So yeah, and like you say the scheduling is a massive part of it, moving people’s hours around but in terms of managing agents and speaking and dealing with people in that front is a backscratcher size really that’s what I find about working as a board I used to plan and shift all these people is very much out of your favour. You do me one back, I’ll give you a month off in the winter. So you can go on a big holiday and you can come work 40 hours a week for me in the peak season, you know? Yeah,

Charlotte Ward 5:09
yeah, absolutely. Yeah. And, and, you know, similarly, I mean, again, straying into another kind of scheduling commonality and sport, just shuffling people around or getting people who are willing to make personal swaps to adjust for personal circumstances as well as another aspect that isn’t there just really shift by shift almost managing it. So so let’s get back to the scaling up then dealing with seasonality is the first part of that, because being able to forecast for seasonality is, is a big stage being able to forecast for the future, I think, although it’s more volatile, it comes and goes much quicker. It gives you a bit of practice in the forecasting, spreadsheet, and you can start to actually I guess, use it to build a sense of accuracy of your model or in terms of forecasting, right. Yeah, so What happens next vanish as you scale up for organizationally. And you know that, I guess first of all, we’re looking at sales pipeline, we know how many customers we’re going to get. We know because we know our forecasting model works roughly what that translates to in terms of potential support load right. There there, is there anything that you think is worth bearing in mind or what comes next?

Chris Taylor 6:26
Yeah, so I’m kind of right in the middle of this process right now. And the way I’m handling it and approaching it is, first of all, I get my baseline forecast, I look at what, how many customers do we have now? What products do they use, I split them, segment them like that. I segment them by where in the world they are, how much they’re spending with us whether they’ve bought an SLA or not. And that gives me a good few profiles to sort of play with. Then I will try and build up some sort of profile of what these customers look like when they Raise a ticket. What’s that journey? So if a customer in the year long contract raises 20 tickets 50 tickets, when do they raise them? So they’re onboarding in the first three months to 50% of their tickets come in there. That’s a really useful bit of information to have. Because if I look and see Oh, look in November, we’ve got 10 deals signed. And that means we’re going to get an extra 300 tickets, I know recruitment needed that over time, support overflow, whatever we need to use. So that would always be my first port of call is trying to build out some kind of profile of your customers how your tickets come in. And then working with commercial teams is absolutely key. So I have monthly sometimes fortnightly calls with our commercial teams, I’m looking at their pipelines, what’s coming up, what’s the value of the deals? What type of deployments are these customers using? What skill level Do they have, what region are they in, these are all factors that implement affect the amount of work coming in versus a sales pipeline, I can roughly forecast now the problem you can sort of get are not every ticket you get is going to be exactly the same. In fact, a lot of people can roughly categorised. Like, for us, I might say it’s component based. So we’ve got a gateway, a dashboard and these type of things. And you can get a lot more technical complexity, which means your resolution times can vary wildly. They can also vary by the member of staff or the region. So building in a really good average is something that’s super important there as well.

Charlotte Ward 8:33
Yeah, yeah. I’m so comforted by everything you’re saying. Because I did this exact exercise about two months ago, I went back and looked at the last year’s worth of deals. So I’m in a new role right now. And there’s been no historic support forecasting done and we’re scaling up as well. And it’s exactly the process you just described. It’s go back look at the last year’s worth deals, build a spreadsheet, look at month by month when those customers raise tickets, and more The behaviours were around when they signed and you know, before and after, and knowing your product that could be low before and after, right? So and then you touched on something else there, which is that not all tickets are creating created equal and there are so many variables and I think our software product much like yours your software product much like you’re offering is a pretty complex one. And that does make this a really, I think you have to be really comfortable with inaccurate data.

Unknown Speaker 9:29
Yeah. Right.

Charlotte Ward 9:32
Yeah. recognise the chuckle This is as good as it’s gonna get right now. The number of times number of times a week I hear myself say that this is what we’ve got right now. And it will refine as we, you know, basically test it for accuracy right going forward. And I think that that’s, that’s what you have to do you have those frequent meetings because you’re probably constantly adjusting as well.

Chris Taylor 9:56
Yeah, absolutely. And you know what, you make a really good point because Not everyone would scale the same. There’s not a uniform kind of pattern to it, I think, where we are in very technical environments, some tactics won’t work. So our users, for example, minor, very much back end, super, super intelligent developers, they really know what they’re doing. So the guys in my team are that as well. They are way more technically adept than me. Very, very

Charlotte Ward 10:25
ditto!.

Chris Taylor 10:26
And yeah, for right, but that’s the point. You need quality quality stuff, but anyway, so they scaled differently. And the thing about a technical product like this is what we tactics we might deploy while we’re scaling up, like reduction in a ticket deflection strategy, probably isn’t gonna work as well as in a holidays call centre or something like that, you know. So, that’s another aspect to consider and scale you. One really good thing I like to measure is how efficient we are. So if my customer baseline is this, and it grows by 50%, but my ticket is broken. 75% Then we’ve got an inefficiency somewhere. Where is that? Trying to figure that out? But yeah, I think once you’ve got those baseline numbers, us in a technical environment, we might try and deploy some self service strategies, we might improve our knowledge bases, but I think it will be less effective overall. And in a business to business environment. Part of your scale plan needs to be relationship management, the success sign of them as well.

Charlotte Ward 11:27
Yeah, very true. Very true. What you just said there about, you know, our technology scaling different from other industries is super important. And I think that although you think as a support leader, I know how to forecast I’ve done it before. You have to kind of get comfortable with the fact that it’s the volume not only are the volumes different, the customer behaviours are different. The work patterns are different and You know, the work comes in in a different way as well. And all these things have to be taken into account. And we’re not just talking about average handle times we’re talking about figuring out what your channels are and everything you just said about self service as well. The other thing I think is perhaps important in a scale up is that the volume of data is different as well, compared to those big call centre environments. Even if the big call centres are scaling. I think they’re, they have enough of a sample to be able to scale much more, to be able to forecast much more predictably. I think, you know, where suddenly my customer base right now is, you know, the customer behaviours in terms of ticket numbers aren’t that great, because tickets are complex and long running. So, that actually means the amount of data points that I have to forecast from a quite low so there is an inherent inaccuracy there because because of all of the other influences on those tickets that you just said, you know, the complexity and Like how one ticket can be very different from the next, you actually have all of these variables make that data quite clunky, quite chunky, don’t they? Yeah, and

Chris Taylor 13:10
I’ve got similar problems. So like my resolution times, I can barely get a handle on it because they’re so wide ranging. There’s so many different types of query. But it’s one of those things where you just have to kind of use some intuition and your and your, your gut on what you know from what’s happened before, and your knowledge of the business industry. And one really other point into this is aligning yourself to the business strategy. So it shouldn’t just be support work. Now, isolation, that’s where you bring in the commercial team to tell you what the pipeline looks like. But you can go a further level on and say, okay, so our pipeline looks like this right now. What does it look like in two years time? Working with commercial leaders to say okay, in two years, if we’re going to have this many customers, we’re gonna have this many tickets, these many issues. So we need this many people. We need to deploy these type of strategies, and I think that’s super important as well.

Charlotte Ward 14:00
Yeah, one thing I’m doing now on that front is is meeting regularly with finance, just just working through like long term projections, we have almost what we call, we’ve put a finger to it and called it our ambition plan, you know, if growth if growth goes this way, if we scale in this way, if our if we hit our targets in this way, what could that look like a year and a half from now because that when volumes are low is quite interesting, particularly and I know we’re gonna touch on this a lot. I feel particularly complex products and services like yours or mine. The lead time on getting good engineers is really long. When I join hands. Yeah, when I joined this company, it was a apocryphally six months, I can now shoehorn that down to four like I can so I can get some like early level one work covered by about two months. Just to give you a baseline I’m getting realistically realistic independence is six months, you know And I think that that’s just really hard to you’re working with very few data points on data that’s very chunky, with very low, long lead times on staffing for that model. I mean, it sounds like scary territory. But clearly you and I are kind of doing it and I hope what at least one of us is doing it successfully.

Chris Taylor 15:20
Yeah, I think I think you touched on something interesting. And that’s that we’re probably divergent and our strategy. They’re slightly so we’re snowplough we’re looking at, if this happens, we can do this. We’re working on the assumption that this is going to happen. So make a plan for it. Right. So my recruitment and hiring and stuff will follow whatever our strategic plan is because we are pretty confident we’re going to hit that. So that’s just Yeah,

Charlotte Ward 15:46
yeah, I think yeah, maybe that maybe the spin I put on that. It’s slightly slightly more conservative. Yeah, we’re slightly more conservative than Yeah, I mean, it’s it’s we are definitely on that trajectory. But you know, you always have to have a sort of, kind of, I guess it’s almost a contingency, you know, like, what if we do above that? And what if we go below that, and that this is the actual target, and you wait, and you aim for the target, you know, but but I guess what I’m saying is that actually even even the best financial and commercial wizards out there can’t really strategically strategically plan accurately two years out that particularly in this business, and in these times, right, so you have to kind of or you have to kind of call it a target or an ambition, you kind of you’re definitely working towards that strategically and that and that included support you have to because of those lead times, right, but but I guess the point I’m making is it’s because of that long lead time you have to get comfortable with the what ifs in that scenario,

Chris Taylor 16:52
right? And that’s the thing in support, you have to just be comfortable being uncomfortable, right? Like the whole the whole industry is Whoa, it’s an unpredictable road, you don’t have control over when customers are talking to you. So that’s an instant level of unpredictability. And you’ve just got to kind of roll with it. But what you can do is just make yourself as informed as you possibly can get all the data points, you can learn as much as you can about the business direction and strategy. And the one last point, I guess I put on this is, don’t forget your people while you scale. Because suddenly, if my team is like two people right now, and they’re both great, if I get to 10, and I’m not catching up with them as frequently, and I start to drop the ball on their professional development and personal development and stuff, then that will have a negative impact on all of that data that you spend time building out your resolution times and it could affect performance. So my last point would be make sure you bring your team with you and your scale make it a collaborative process. Yeah,

Charlotte Ward 17:50
very true. Very true. I must admit, I’m a bit guilty of kind of whooshing off down the corridor with a spreadsheet you know, it’s easily done. When you get when you You feel like things are coming together. And you do have to stop and take stock every now and then and say, You know what, I just need to tell you these are this is kind of what I’ve, you know, it’s almost like presenting your own internal vision for support, isn’t it? Like, get them excited about the data as well, because the data is what empowers them and empowers you as a team to succeed, right? And I think just being able to say, you know, what, I’m sorry, I’ve had my head stuck in in the Google Sheet for three weeks. And you haven’t seen much of me, but I think I’ve got this figured out, what do you think? And you know, can you tell me you know, about this, and I’ve looked at this in detail, you know, it starts conversations with them as well, actually, which I think is kind of weird, because

Chris Taylor 18:43
it’s important to show them the output of your own work, right. You can see like, we can see our engineers up. Instantly, we can see that and it’s important to show them we’re working as equally harder. So, but yeah, I like to do the same kind of thing. Take them through a data sheet or a pack or something and say, here’s what I’m thinking. What do you think comments will over, refine, refine? Get them bought into it? And that really helps as well. Because you’ve got to bring the team with you when you scale pain down the road, for sure.

Charlotte Ward 19:10
Yeah, absolutely. Absolutely. Yeah, that that thing you were describing there about, you know, taking your team with you, as I just said, kind of, I do have this propensity to get my head in a spreadsheet. And I’ll just give you an example of that. I woke up this this morning, at quarter to five in what I can only describe as a data sweat. And when I sat bolt upright in bed, and I just had one of those kind of moments. Something fell into my into place in my head while I was asleep, to do with my forecast to do with this spreadsheet that I’ve had in my head for four months now on and off And I just realised two numbers could relate to each other in a different way. And it was a real aha moment. But I think just sharing those little stories as well with your team is another way to kind of tell them, you know, just just demonstrate to them that you are invested in this and you know that, like you said, showing them the output of all of those little Aha, little aha moments, whether they come at two o’clock on a Tuesday afternoon or course five in the morning. I mean,

Chris Taylor 20:31
it’s a such a good feeling, though, isn’t it when you crack something like that? Yeah, like that’s one of my favourite things is what I’ve been buried in the spreadsheet for months, and then it just comes to you overnight.

Charlotte Ward 20:40
Yeah, yeah, absolutely. And I can’t tell if that’s a good thing or a waste of four months with your head buried in it. I haven’t quite decided that yet. Or whether one is necessary. Yeah. I don’t know whether one is necessary for the other. Maybe you have to bury yourself in the spreadsheets. You get the aha moment. Isn’t that painful?

Chris Taylor 20:58
You’ll have learned a lot of stuff. While being buried in that spreadsheet as well, so there’s definitely benefit to doing that. But you’re spot on little things like that little anecdotes you can share with the team, anything to just bring them into the process of your strategic and scale direction is a great move.

Charlotte Ward 21:15
And definitely sharing the output, as you said, all of the conversation is that that sheet sparks some really interesting insights because as we alluded to before, neither you nor I are as technically competent as our teams. And as much as we might get them to talk us through stuff or try and understand stuff. There’s not a hope in Hell, I really understand what they’re doing. They’re just that just isn’t you know, I mean, I can sit and watch them and have them explain to me, yes, this these kind of pages of code that are whizzing past represent this and I just do this, this click here, paste that did the job done. And I was like, I was hearing like, I was present in the moment, but somewhere in there you entirely lost me. So I don’t, you don’t actually understand the implications of everything you just did. But so when you get lost in those moments, I think being able to have those conversations sparked by spreadsheets about work is just another way of getting informed, as well, particularly when the work is very varied as yours and mine both seem to be.

Chris Taylor 22:22
Yeah. And when you’re not the most technically competent person, it’s important as well, just as a side note to be really upfront with that. So my team and your team, I expect know that we are, we are the customer support people. We know how to manage customer operations, we know what metrics we need to look at performance, we need to track blah, blah, blah, and we know how to scale that. What we’re not good at is troubleshooting a highly technical product with five different programming languages and stuff like that. So if your team understands that and they know what you bring to the table alongside what they’re bringing to the table, it just makes for good synergy I think.

Charlotte Ward 22:56
I think it really does and I think actually it makes for it Foster’s a great deal of understanding because if I say I haven’t a clue what you just did, they’re very they’re super patient because their support people but at the end of the day, they’re super patient and willing to talk me through stuff. So it’s a learning experience all around I think

Chris Taylor 23:14
that’s support people though, right?

Charlotte Ward 23:17
Yeah, they are. The best were the best. Awesome. All right. Thanks so much, Chris. Lovely to catch up with you. That’s it for today. Go to customer support leaders.com forward slash 108 for the show notes, and I’ll see you next time.

Transcribed by https://otter.ai