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Lightning Talk: Where Did Everybody Go?

Jo Cranford • June 23, 2016 • Singapore • Lightning Talk

In the lightning talk titled "Where Did Everybody Go?" presented by Jo Cranford, lead developer at Culture Amp, the discussion revolves around employee retention and the underlying reasons behind why people leave their jobs. Jo challenges common perceptions, particularly the belief that employees primarily leave due to poor management, by presenting data derived from over 100,000 survey responses from various tech companies. The talk emphasizes the significance of company culture and employee engagement as pivotal factors influencing retention rates.

Key Points Discussed:

- Employee Insights: The data reveals that individuals leaving their jobs often do not cite manager-related issues. Instead, reasons for leaving are more closely linked to employees' perceptions of their roles, opportunities for advancement, and the organization’s future viability.

- Career Development Opportunities: Among the factors impacting commitment, career development opportunities are found to be the most significant, outweighing managerial influence and compensation. Employees who believe they have paths for growth and recognition are more likely to stay.

- Tenure Influences: Jo identifies a notable decrease in job commitment among employees who hit the two to four-year mark in their tenure. This period is critical as these employees possess valuable experience and knowledge yet often feel less positive about their roles.

- Gender Imbalances: The analysis highlights disparities in experiences based on gender. Female employees who left reported feeling a lack of communication, confidence in the company’s prospects, and equitable workload distribution.
- Work Environment Not a Deciding Factor: Contrary to popular belief, the physical work environment, including amenities like recreational facilities, had minimal impact on employees' decisions to stay or leave. It suggests that while such perks may initially attract talent, they do not contribute significantly to long-term satisfaction or commitment.

Conclusions and Takeaways:

- Organizations should prioritize creating clear opportunities for career advancement and recognize employees' contributions.

- Companies need to be particularly aware of the transition period around the two-year mark to ensure valuable employees remain engaged.

- Enhanced communication and workload fairness are crucial to retaining female talent in tech, indicating the importance of fostering an inclusive workplace culture.

- Ultimately, focusing on aspects that genuinely matter to employees—such as future company viability and personal growth opportunities—can lead to improved retention rates.

Lightning Talk: Where Did Everybody Go?
Jo Cranford • June 23, 2016 • Singapore • Lightning Talk

Speaker: Jo Cranford, Lead Developer, Culture Amp

In our current market, almost of half of our employers are hiring for experienced developers. Many people move jobs every couple of years, leaving teams in an ongoing state of forming or storming, unable to find their rhythm. Company culture is a major influence on people deciding to stay in their jobs. This talk uses data gathered from over 100,000 responses to engagement and exit surveys from fast growing, successful tech companies to analyse why people leave, and how we can encourage our team members to stay (hint: it's not pay!)

Speaker's Bio
Jo is lead developer at Culture Amp, the world’s leading culture analytics platform. Before her current role, Jo worked at the likes of Lonely Planet, Atlasssian, ThoughtWorks and Expedia, in roles such as Product Planner, Senior Business Analyst, Development Manager and Chief Technical Officer. She was also a CTO of an Australian startup accepted into Telstra’s Muru-D program.

Event Page: http://www.reddotrubyconf.com/

Produced by Engineers.SG

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Red Dot Ruby Conference 2016

00:00:13.799 so I've got a question to ask you all
00:00:16.160 what's the first place you go to if you
00:00:17.640 don't know the answer to
00:00:19.960 something where
00:00:21.640 else Google right but what happens if
00:00:24.840 you go to Google and ask them why people
00:00:26.599 leave their jobs I'll tell you they lie
00:00:30.320 people don't leave their jobs because of
00:00:32.000 bad manages and I'm going to take some
00:00:34.280 time over the next few minutes and show
00:00:35.920 you some data to prove it to you you may
00:00:38.480 be wondering where this data's come from
00:00:41.000 I work for a company called culture amp
00:00:42.800 and we collect survey data we help
00:00:44.719 people to run Employee Engagement
00:00:47.000 surveys they also Run exit surveys and
00:00:49.600 we collate the data so that we can see
00:00:51.680 for people who go on to leave their
00:00:53.239 company within a year or two after their
00:00:55.359 engagement survey how they were feeling
00:00:57.600 at the time and how it was different to
00:00:59.280 the people who went went on to stay now
00:01:01.879 the first thing that we notice is that
00:01:03.920 people are actually pretty honest so we
00:01:06.560 ask people do you think about looking
00:01:08.280 for a job at another company or do you
00:01:10.320 see yourself staying with the company
00:01:11.840 over the next couple of years and
00:01:13.720 there's a really big gap between the
00:01:15.240 people who stay with the company and the
00:01:17.119 people who do actually go on and leave
00:01:19.960 which gives us some confidence in the
00:01:21.400 data
00:01:22.640 itself so let's look at where the other
00:01:24.840 differences are in the data these are
00:01:27.520 the questions where we see some big gaps
00:01:29.400 between people who stay in their jobs
00:01:31.000 over the next couple of years and people
00:01:32.960 who go on to leave the people who are
00:01:35.799 happy in their role who actually feel
00:01:37.960 that they're doing the job that was
00:01:39.560 described to them when they took the
00:01:41.159 when they took it on are much more
00:01:43.439 likely to stay on the people who leave
00:01:46.399 are less likely to believe that their
00:01:47.799 company is in a position to succeed over
00:01:49.600 the next few years they're more likely
00:01:52.759 to not believe that they can make a
00:01:54.520 positive difference at work the people
00:01:57.000 who stay are more likely to feel that
00:01:58.960 they are receiving appropriate
00:02:00.719 recognition for what they do and have
00:02:03.000 confidence in the
00:02:04.240 leaders and they're more likely to
00:02:06.079 believe that there really are good
00:02:07.320 career opportunities for them at their
00:02:09.479 company what we don't see on this list
00:02:12.120 is anything about managers it gets even
00:02:14.800 more interesting when we look at the
00:02:16.080 data at the other end of the scale these
00:02:18.280 are the things that make very little
00:02:20.640 difference to people when they come to
00:02:22.480 making a decision of whether to stay in
00:02:24.000 a job or not one thing that we see is
00:02:26.840 that physical workplaces being an
00:02:28.560 enjoyable place to be there's no
00:02:30.640 difference between the people who leave
00:02:32.519 and the people who
00:02:34.080 stay I think there's a bit of a backlash
00:02:36.599 around the kind of free ping pong free
00:02:38.560 craft beers and all that kind of stuff
00:02:41.400 I'm not saying that it doesn't attract
00:02:43.319 people into your company in the first
00:02:44.800 place but what we see is that when it
00:02:46.959 comes to making a decision whether to
00:02:48.680 Stay or Leave people aren't hanging
00:02:50.400 around for the
00:02:52.920 games now we did another um another
00:02:56.599 little survey there was about 175 teams
00:02:59.400 we we we looked at the data for oops
00:03:02.120 I've just given the game away now um but
00:03:04.640 we we correlated these four different
00:03:07.200 areas and we tried to to figure out
00:03:10.000 which of these was most closely related
00:03:12.599 to whether or not people felt committed
00:03:14.159 to their job and we already know that
00:03:16.120 people who were committed were more
00:03:17.440 likely to actually stay on at the
00:03:18.760 company so who here would think that
00:03:20.760 managers would be the biggest reason why
00:03:22.879 people would
00:03:24.040 stay okay so you're all listening in the
00:03:26.200 first half who would think that it was
00:03:27.799 the leadership put your hands up
00:03:31.319 noty who would think it was
00:03:33.599 pay oh there's a few more and who would
00:03:36.280 think it was development
00:03:38.280 opportunities so you would be right
00:03:41.040 development opportunities had almost
00:03:43.560 twice as big of an impact on whether
00:03:45.319 people felt committed to the company and
00:03:47.519 were more likely to stay in their job or
00:03:49.239 not even compared to leadership which
00:03:51.159 was the next most important one and pay
00:03:53.879 and managers really had very little
00:03:55.959 impact across the company on whether
00:03:57.599 people really felt committed to staying
00:04:01.439 now if you've been in your job between
00:04:02.879 about two or four years this next slide
00:04:05.079 is for you so you can take this back and
00:04:07.360 show it to your boss and tell them why
00:04:09.159 they should be really nice to you at
00:04:10.480 this point in
00:04:11.799 time I like this cuz I'm coming up to my
00:04:14.120 2-year anniversary as well um so what we
00:04:17.359 see is that when people get to their
00:04:19.120 two-year anniversary they go through a
00:04:21.000 period where they really feel more
00:04:22.400 negative they're more likely to then go
00:04:24.479 on and leave and to feel less committed
00:04:27.000 now these people are going to be some of
00:04:28.360 the most valuable in your company
00:04:30.360 they know their jobs well they've been
00:04:32.000 there for a while they probably have a
00:04:33.440 good Network in the company and they
00:04:34.840 know how to get things done and yet
00:04:37.240 these are the ones that companies are
00:04:38.639 letting feel more
00:04:42.720 negative there's also interesting gaps
00:04:45.639 among genders so women when they leave
00:04:49.520 more of the women who actually left felt
00:04:51.639 that there was a lack of open and honest
00:04:53.720 Communication in their
00:04:55.240 companies more of the women who left
00:04:57.320 felt that their company wasn't really in
00:04:58.919 a position to succeed over the next few
00:05:01.080 years and they felt that workloads
00:05:03.240 weren't particularly fairly divided at
00:05:04.919 their company now gender diversity in
00:05:07.520 the tech industry is a big deal it's a
00:05:09.639 big Focus for a lot of companies we want
00:05:11.280 to try and make it more equal so these
00:05:13.400 are things that we should be paying
00:05:14.639 attention
00:05:17.120 to so just to to summarize all the
00:05:20.280 things that I've run through very
00:05:21.639 quickly today we had a we had some data
00:05:24.560 from around 20,000 people to to put this
00:05:27.280 together and these are the things that
00:05:28.840 they told us were more important to them
00:05:30.720 when they were deciding whether or not
00:05:32.400 to stay in their job from that data so a
00:05:34.720 lack of confidence in the company's
00:05:36.240 future a lack of confidence in the
00:05:38.600 leadership lack of career development
00:05:41.080 opportunities there's a danger zone in
00:05:43.800 that two to foure tenure just lock him
00:05:45.560 in the office for that time for women we
00:05:48.720 need to think about making sure there's
00:05:50.280 open honest communication and fairly
00:05:52.319 divided workloads and no Google we don't
00:05:54.960 see anything there about direct manages
00:05:57.759 thank you
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