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On any particular day, there are probably dozens of articles that go up on sites with titles such as ‘What successful people do in their first hour of work’, with typically one of the tips being don’t check your emails for the first hour or during the morning at all. Here’s my opposition to that, successful people and people who want to be successful need to do different things. Let me explain with a sports example, now if I were to undertake the training regime of Miguel Indurain (five-time winner of the Tour de France, amongst other cycling achievements) I wouldn’t make it through the first week. The fact is that Indurain spent years building up a base so he could do manage the training demands of being a professional cyclist. The same is true of successful people in general, they have a base to work from, they most likely spend years checking emails and other online information sources every moment of the day to keep their finger on the pulse. And now they are able to ignore emails, like Tumblr founder David Karp who tries not to read emails before 9:30 am, the stuff that gets his attention most likely will be communicated via a phone call, business lunch, or in-person meeting, etc. Does anyone really think that in the lead up to the purchase of Tumblr (David Karp's company) by Yahoo, that Yahoo CEO Marissa Mayer sent an email to David asking if he wanted to sell his company? Time and time again within the technology sector we hear how these massive acquisitions where discussed over dinner, indeed Mark Zuckerberg is reported as inviting some for dinner to discuss a potential deal. The point that I’m labouring here is that successful people and people who want to be successful do different things, so by simply doing things that already successful people do you may be doing the wrong thing.

Regardless of what I have on that day, regardless of what I’m thinking about as I’m driving to work, the first thing I do after saying good morning to my colleagues is to check my emails. Emails are the lifeblood of information for me, and I’m guessing for many other HR practitioners. And although I’m right outside the door of senior staff – who more often than not will drop by or call me into their office if they want something from me, I still need to check to see if they’ve emailed me something that needs my attention. And often this isn’t about the work, my area is workforce planning so not a lot happens overnight – different for example in HR Consulting area where critical incidents can happen (and often do) in the space of minutes. Rather I don’t want to miss an opportunity to communicate to senior leaders that if they email something to me, then it’s my priority. When an executive drops by your office/desk to discuss something, saying you haven’t read the email simply isn’t good enough. Its telling them very clearly that they are not a priority, and that you’re not client-focused – or perhaps worst you’re letting them know they’re not a client.

The advice of successful people is worth taking a look at, however its also worth remembering that they are in a different phase of their career than yourself. Different times call for different actions.

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.