That that difficulty of matching that data together you’ve mentioned as well mapping a journey mmm so one thing I’m curious about is it’s all very well tracking data but how does that change behavior how does it actually change behavior within the organization so for example if I was to learn certain aspects of an employee’s journey and the time from when they started to their performance to whatever happens later on in the business does that.
Actually change the way that.
People deal with it does that change the way people do performance reviews does it change the way that employees behave is there sort of a you know like a cultural change in that process as a result of mapping it and measuring it um.
I suppose like like anything the act of measuring change is the thing then but and so you know going through like performance management exercises whether that’s you know once.
A year or every week that that kind of process focuses people’s attention on their performance.
Makes them think about what they’re achieving so so I think processes are themselves actually it can be beneficial if they’re done well but but I think particularly to the to the panel its usefulness and and power here is allowing people to see the results of their.
Decisions and then influence them to make better decisions going forward right and so an example.
Where it’s in a fast-moving organization you need to make an organization change and you realize okay well I need to move this manager to that team I need to move this manager to that team and I’m just gonna you know make those moves happen to release one of my high talents to go and do some new project and you know and you just do it.
And you think about what’s best for the business is to release that great talent to go and.
Run that new project so you shuffle your managers around and you move on with good life but if you have a data point that shows very clearly to a very high degree of accuracy that if an employee has three different managers in a year they’re 80% more likely to leave right of.
Course any organization across any industry any country three different managers who are responsible for driving your career owning your career giving you jobs to do assessing you if that person changes three times in a year that person’s almost certainly grown and so when you’re making that decision around quickly moving these managers around to get your organizational goal if you have a very simple very quick very easy to access tool that shows you that if you do that yeah this group of 10 people are almost certainly.
Out the door if you don’t do something extra so.
I’m not saying you then don’t do the or change that you’re that you need to do to drive the business you still need to write the business but then you put some extra attention into those ten people you pull those of them aside to give them a development plan you give them some face time with the CEO to let them know that they’re really valuable to let them.
Know that that they are important to the organization you’re not just playing musical chairs with no manager just for the hell of it right and and I think a lot of very fast-moving organizations are very top-down they’re driven by you know the charismatic founders and I’ve worked that you know people.
Like Steve Jobs and and and Travis right so I’ve seen that in action and they’d make decisions on the fly and they’re normally great decisions in the business they’re normally pretty terrible decisions for the individual interesting yeah because they’re doing it from guttin and then they’re doing it maybe.
From a very good analysis my business needs it might be driven by numbers but that decision yeah but the impact of it is invisible until suddenly.
Six months later they turn around to HR and say well why is our attrition gonna why we’re losing so many great people there’s your data points you don’t care about right and I can prove you don’t.
That brings me to asking this question why because we dive into the case studies has got some great case.
Studies on a sort of expansion but the why behind panel it hmm you’ve spent.
You know your career in HR and people why did you decide to do this because especially if somebody who’s worked in large organizations like uber noble groups apples for example you could build a very successful career continued building in for these large organizations until you just kind of sailed off.
Into the sunset with your retirement so why have you chosen to come out start a startup and do this what was the the the what was missing yeah no it’s great question it’s it’s funny I think of my time at that’s actually all.
Mean so three the large companies I worked I recently did the Apple mobile group and uber they’re all organizations going through tremendous growth they’re all going through massive change and so I don’t think of them was working for large companies I think of them was working for companies.
That are going through that change and and they’re it’s an exciting time to be in organizations like that and I think that’s kind of become a specialization of – to work with organizations going through scale and and I suppose I enjoyed working at uber especially the first six months or.
So where we had I was head of HR for international we had maybe a hundred people in Asia maybe 200 people in Europe and over the course of 18 months we grew that to about four and a half thousand people that’s the kind of scale that no organisations ever done and I never recommend.
Any organization to different but it was an amazing thing to experience and coming out of.
That and you know obviously had some tremendous cultural problems and which party left led to me leaving but there it definitely got to the point where yeah it’s becoming a.
Large corporate and I realized that’s not really what I enjoy what I.
Really enjoy is helping small organizations scale so after uber I spent.
Two years doing my own sort of one-man consulting working for VCS and investors with their portfolio companies so it’s been about two years supporting high-growth startups companies that are getting ready for their their Series B where they’re gonna.
Have to scale very rapidly helping them set up their HR departments reach to their comp plans you know sort of relook at who they are from a people for this perspective and get them.
Set on a different track so after working with investors for a couple of years doing that and having them repeating me telling me that I should be doing this as well and then working with a number of founders people that I really came to respect since there’s something right that some great founders out there running some great businesses and yeah generally I was persuaded to do it and.
I’ve been thinking about panel letters or the concept of a self service people analytics tool that’s always been in the back of my mind as that’s what my industry my specialization needs that’s actually a tool that I want to use so I went and built it you do.
That ya know you stop taking advice yeah yeah well I took the advice in this wind and when it made it happen I said anything you can do I think given your experience as well and you know you work with high-growth startups or scale you know when people are scaling up and whether that be a corporate who’s very much to start up you know going from that two hundred to two thousand whatever down to the smaller startups you know maybe now they’re going through that scale.
Phase one of the things that you’ve mentioned is about being able to measure performance within the organization or be able to like track back and find a decision made led to this.
Outcome with this person right now surely without knowing how this works shortly the the issue is.
Is that in a start-up they don’t have a history they don’t have a workforce of 200 are you then going out and grabbing datasets from other well that that’s what the benchmarks yeah.
So the benchmarking comes in that there is no publicly available data of the kind of quality that I think we would.
Problems with organization with sites or data sources like Glassdoor it’s completely self-reported there’s no.
Way to really know if those numbers are true or if what’s reported is true where where and so therefore it’s very easy for a manager who doesn’t agree with your advice to.
Just dismiss it and say well I look at our self-reported data I.
Don’t need to listen to that whereas what we’re building with impanel it is a data universe of similar sized companies in the region or in the regions where our our car clients are so we we cover the location we cover the type of.
Industry the type of employees that are what.
The jobs are they doing and so you then we build up a even a short history across a very large number of companies and a very large number of employees gives us the predictive data to be able to to basically say what is and.
What is normal what is what is usual within your industry so you know it is about a one organization that had a attrition of 50% that lose 50% of their people every year hi yeah yeah it is high and and.
Then you and then a manager see that top-line number and they want to make a knee-jerk decision but when you when you’ve got a larger data set and you can dig in and see well actually the developer team have got a very normal attrition.