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This Is Why Innovation Is Hard

Brendan Lys
By
Brendan Lys
Brendan Lys

Operating at the intersection of Human Resources and Data Science, I leverage extensive specialist experience within Human Resources, with the methodologies and approaches of Data Science. This focus on the discovery of actionable insights from data, has been applied to areas such as: remuneration & benefits, workforce planning, recruitment, health & safety, diversity, and training. But what does the application of data science to HR challenges and opportunities actually look like. Within an HR framework the data we work with typically comes directly from our HRMIS, an advantage of using data science methodologies is that we can bring in additional data either held within the organization or from external sources - data which is out of reach from a pure HR analytics approach. Consider for example position descriptions, these contain a wealth of data that we typically ignore as its not in a analysis ready format. A side project I'm working on currently (April 2019) is using text mining on job descriptions to provide insights into which job family the position may fit into. The insights of my work have been enjoyed by organizations across a diversity of sectors including: Government (Australia and New Zealand), ASX and NZX listed companies, utilities, not for profit and higher education.

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Last updated on Nov 18, 2022
QUICK SUMMARY

Innovation is hard because organisations get in the way, the rest on current success. Innovation is about doing something differently, yet organisations are really good at doing the same thing the same way – take McDonalds for example, regardless of whether you like or dislike the food they prepare, you know it’s the same every […]

This Is Why Innovation Is Hard

Innovation is hard because organisations get in the way, the rest on current success. Innovation is about doing something differently, yet organisations are really good at doing the same thing the same way – take McDonalds for example, regardless of whether you like or dislike the food they prepare, you know it’s the same every time. I enjoy the occasional Big Mac, and regardless of where I am in the country, I know it will taste pretty much the same as the one I had a week ago in a different part of the country. And doing producing the same widget to the same quality every time is what business is about. And this is why innovation is hard, because you have a business which has been successful doing the same thing to the same quality, and you're asking them to change this.

Often it’s not simply about widgets either, I’ve worked in service orientated companies where innovation doesn’t mean making sweeping changes to a production line but rather simple changes to a process or policy. That same reluctance to change is still there, those similar hall marks of sunk cost decision basis are still very much present. If something is being changed or improved through innovation, then often all people perceive is that they’ve been doing it wrong. People place so much focus on the fear that they’ve been doing it wrong, that they fail to focus on doing it better.

Turning this around is incredibly hard, particularly in successful companies. My take on it is that to initiate change or innovation you need to be able to leverage the organisations past. Unless they’re a young company, they didn’t always do things this way, at some point they innovated and got to the point they’re at now. Something they need to be reminded of this, indeed sometimes we as individuals to be innovative in our own lives need to reminded of this.
At some point we all made a choice which set us down a particular path, both we as organisations and as individuals need to find this sense of self again, we need to be brace and challenge ourselves – the alternative is we do the same thing every day and wait to die.

And on that cherry note, all the best. Innovation is something we all struggle with, be it in our professional roles or in our private lives. Remember when you were brave, and be that brave intellect again.

Brendan Lys
By Brendan Lys

Operating at the intersection of Human Resources and Data Science, I leverage extensive specialist experience within Human Resources, with the methodologies and approaches of Data Science. This focus on the discovery of actionable insights from data, has been applied to areas such as: remuneration & benefits, workforce planning, recruitment, health & safety, diversity, and training. But what does the application of data science to HR challenges and opportunities actually look like. Within an HR framework the data we work with typically comes directly from our HRMIS, an advantage of using data science methodologies is that we can bring in additional data either held within the organization or from external sources - data which is out of reach from a pure HR analytics approach. Consider for example position descriptions, these contain a wealth of data that we typically ignore as its not in a analysis ready format. A side project I'm working on currently (April 2019) is using text mining on job descriptions to provide insights into which job family the position may fit into. The insights of my work have been enjoyed by organizations across a diversity of sectors including: Government (Australia and New Zealand), ASX and NZX listed companies, utilities, not for profit and higher education.

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