Playing by numbers

The theme of last week’s Learning Cafe in Sydney was How to Win Friends and Influence Learning Stakeholders.

Among the stakeholders considered was the “C-Level & Leadership”. This got me thinking, do the C-suite and lower rung managers expect different things from L&D?

There’s no shortage of advice out there telling us to learn the language of finance, because that’s what the CEO speaks. And that makes sense to me.

While some of my peers shudder at the term ROI, for example, I consider it perfectly reasonable for the one who’s footing the bill to demand something in return.

Show me the money.

But I also dare to suggest that the managers who occupy the lower levels of the organisational chart don’t give a flying fox about all that.

Of course they “care” about revenue, costs and savings – and they would vigorously say so if asked! – but it’s not what motivates them day to day. What they really care about is their team’s performance stats.

I’m referring to metrics such as:

• Number of widgets produced per hour
• Number of defects per thousand opportunities
• Number of policy renewals
• Number of new write-ups

In other words, whatever is on their dashboard. That’s what they are ultimately accountable for, so that’s what immediately concerns them.

The business savvy L&D consultant understands this dynamic and uses it to his or her advantage.

He or she appreciates the difference between what the client says they want, and what they really need.

He or she realises the client isn’t invested in the training activity, but rather in the outcome.

He or she doesn’t start with the solution (“How about a team-building workshop?”), but rather with the performance variable (“I see your conversion rate has fallen short of the target over the last 3 months”).

He or she knows that the numbers that really matter don’t necessarily have dollar signs in front of them.

LATI: A better way to measure influence on Twitter?

I’ve never been comfortable with attributing digital influence to the number of followers someone has on Twitter.

To me, it’s more a measure of your longevity on the platform. The longer you have been on Twitter, the more followers you will have collected over the years.

Sure, the quality of your tweets and other variables will have an effect, but simply comparing the raw number of followers among tweeps is not really comparing apples with apples.

I was ruminating over this when it dawned on me: why not divide the number of followers by the number of years the person has been on the platform? That will remove the variance due to longevity from the equation.

For example, I currently have 831 followers and my Twitter age is 2.1 years, so my Longevity Adjusted Twitter Influence (LATI) is:

831 / 2.1 = 396

According to convention wisdom, someone who has 1500 followers is much more influential than I am. In absolute terms that may be true, but if their Twitter age is 4 years, their LATI is 375 – which suggests I am relatively more influential than they are. That means I’m on track to becoming more influential overall.

Compare that to someone who joins Twitter and attracts 200 followers in 3 months. That’s a LATI of 800 which blows both of us out of the water.

In the short term I imagine a typical person’s LATI would follow an s‑curve, whereby they take a while to attract followers in the beginning, then they ramp up as word spreads, then they plateau out again as their target demographic is exhausted. Over time, their LATI will decline as the years rack up without significantly more followers.

In contrast, truly influential people will continue to attract followers into infinity, so their LATI will remain high.

Now I’m no mathematician, so my logic may be all screwed up. But to me it’s more meaningful because it levels out the playing field.

Of course, the metric doesn’t recognise who is following you. Someone with 10,000 followers won’t be very influential if those people have neither the means nor the inclination to act upon their pearls of wisdom.

Conversely, someone with only 3 followers will be incredibly influential if those people happen to be the President of the United States, Rupert Murdoch and the Head of the European Central Bank.

So notwithstanding complicated and opaque measures like Klout, LATI provides an open and convenient snapshot of digital influence. At the very least it’s fun to toy around with.