SNGTDTED

The Game-changing Economics of Fractional Availability

stoweboyd:

The tech world is in many ways like a large city. While we spend most of our time in a few neighborhoods, it doesn’t really come as a surprise to encounter an old friend or colleague that you haven’t talked to in years, hanging out in your corner café. So I was not surprised to hear that my old friend Antony Brydon had started a new company with a compelling value proposition, called Directly, and that he and his head of marketing, Lynda Radosevich, thought I’d like to learn about it.

Antony Brydon

I met Antony when he was CEO of Visible Path, an innovative social startup, one that was working to build the work graph – through email analysis – in the ‘00s. Visible Path was acquired by Hoovers in 2008. Perhaps they were a bit ahead of the market, but that’s a sign that Brydon & Co are generally ahead of the power curve.

I was also not surprised that Directly’s value proposition is very, very smart: helping other companies scale their customer support capabilities by breaking out of what I think of as the skills versus wages snare (see figure 1).

The snare is this: as the necessary skill level for customer support increases, the wages that must be paid increased. This is a fundamental aspect of supply and demand.

figure 1 – The Skills v Wages Snare

But Antony and his partners have come up with a way to break the snare, and Directly is the platform on which that magic happens.

I recently interviewed Antony about Directly, and why the company is growing so quickly.

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The Interview

Stowe Boyd: One thing I’d like you to do is tell the origin story. In every superhero comic strip, there’s the story that they tell about how Peter Parker got bitten by a radioactive spider, or Steve Jobs visiting PARC. So, what led to the founding of Directly?

Antony Brydon: It was not as dramatic as Peter Parker and the radioactive spider, but it was interesting. And it was interesting because the company founding  and the initial  inspiration were probably 15 years apart. Back before Visible Path, I worked in a call center for a few years: back in ‘98. I worked for a venture firm which invested in Genesis, Aspect, and Aurum: a lot of the early call center players.

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Call centers was an interesting beat, but it was a little depressing because the customers were very rarely happy with the service they were receiving. - Antony Brydon

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For the better part of three years, that was my beat. And I was looking at a lot of Fortune 100 call center buyers to figure out what products they needed. Call centers was an interesting beat, but it was a little depressing because the customers were very rarely happy with the service they were receiving.

The agents in the call center were a downtrodden labor force: modern-day galley ships. The call center managers were doing the best they could, but often saw themselves as sort going to war with the tools they had. Under equipped and underserved. Very tactical.

Genesis had some incredible skill-based routing that I used in a project. It could actually connect a customer to an absolute perfect agent. But that capability wasn’t being used very broadly. There were a lot of reasons it wasn’t. Some of the call centers didn’t want to hire the truly skilled agents because it could cost more money.

SB: Right, and I bet they didn’t want to test people to gather all that data, either. That was expensive, too.

AB: Yes. They didn’t want to break their agents down into different pools based on skills levels because utilization would drop. If you had one homogeneous pool, you could give a call to anybody. If you had 10 skills-based pools, utilization fell through the floor, so the economics fell down. A great example of really great technology that didn’t get applied anywhere near the degree that it should because of the constraints in the business model. And that, entrepreneurially, was pretty depressing to watch.

My diagnosis was that the problem wasn’t the technology. The problem was the talent side of the equation, and how that talent was being managed. There was no amount of technology to fix it. When you’ve had very low skill folks being hired at very low wages, who are being pushed to handle 60, 80, 100 customers a day and sort of being churned out 12, 13 months later once they met the learning curve, well that invariably put a low ceiling on customer experience. A depressing trend, and that was the reason I made a conscientious move to stop working on it

That wasn’t the inspiration for Directly, per se, but that was my diagnosis at the time. That was the real problem. It made me very unexcited.

For the last kind of 15 years, whenever Jeff [Paterson, the co-founder and head of product at Directly] and I sold a company, we would come back to this problem that had bothered me a long time ago and just started hacking to see if we had any new approach or insight that we had that we could bring to bear on it.

SB: You’re saying the obvious thing was being blocked by the business model, which led low-skilled people to become more skilled, and then their higher wages would become unaffordable.

AB: Yes, absolutely. Skilled workers could have been created very quickly. So, if you had a Samsung Galaxy question that was routed to a Samsung Galaxy expert, and that person was doing a normal number of inquiries for the day and wouldn’t have the boot on the back of their neck to get off the phone in 6 minutes. But that was blocked by the economics of the business model, and that blocked the talent model.

We looked at this in 2001 after eMusic had just got acquired. We looked at it in 2008 after we sold Visible Path. When we came back to it in 2011, we had the benefit of seeing a lot of these on-demand companies coming up. We saw Lyft coming up. And Uber coming up. And Airbnb. And all of these companies taking advantage of a kind of fractional availability.

When we applied that to the old problem, we saw for the first time we saw the potential of pulling together people with much higher skill sets than would ever sit in a call center. And then making them available for small fractions of time. When their skill set really matched a customer’s problem, and at levels where they could really opt in and delight a customer. With that combination of the ability to get more talent than had existed before, and then also to render that talent. Making the business model, the economics of it, work.

So that was the initial insight. That’s what started down that pathway quickly, building some quick primitive apps and starting testing that idea. It bore out very quickly.

We did some initial tests in kind of 6, 12 weeks of initial building. We got some very good signals back that we could attract very skilled folks and pair them with customers very efficiently and very quickly. It took a lot of work to actually develop the engines and all of the enterprise innovations. But those are the book ends. There was that insight in ‘98 that no amount technology could fix broken talent model and a broken business model. Then there was that 'aha’ in 2011 and 2012 that the on-demand piece would be a very elegant solution to this problem.

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At that point in the interview, I started to sketch a 3D model in my journal, based on Antony’s use of the term ‘Fractional Availability’. In figure 1, the 2D model above, we saw the snare, the dead-end that Antony has described as an economic problem that technology couldn’t fix in 1998. But with the surge of interest in on demand platforms – like Uber, Lyft, and Airbnb – a new alternative appears.

An additional dimension appears, so that people with high skills can still be affordable, because they don’t have to be hired as full-time workers sitting in a call center. They can be paid only for the time that they are handling customer support requests, and they have gained their expertise at no expense to the company using their services on a part-time, on-demand basis. They’ve gained that skill as a power user, on their own time, for their own reasons.

Figure 2 – Fractional Availability

Here we see the 3D reality: it is possible to pay low ‘wages’ (perhaps ‘costs’ would be better) for highly-skilled customer support because of the wormhole that is fractional availability. (I think of it as something like the Guild Navigators in the Dune series, who can ‘fold space’ and travel ‘without moving’ from one star system to another light years away.)

So, if you take the 3D chart above and look at it end on – concealing the dimension of fractional availability, it would look like figure 3, below. Directly allows companies to shift the needle from high costs for high skills, by tapping into the game-changing economics of fractional availability.

Figure 3 – Back in Two Dimensions

Theories into Practice

In the next post in this series, I will dig into the specifics of how Directly has moved the needle at a specific customer’s call center operations, a case study based on the adoption of Directly at MobileIron. But behind that practical and tactical step-by-step adoption is the origin story of Antony’s frustration with call center economics in 1998, and the role that fractional availability is having on the world. Directly’s success has come from harnessing that theory, and making it do the heavy lifting.

Also, you might like to hear Antony and Jonathan Keane, Director of Customer Service at Republic Wireless in a livecast on the topic: How To Deliver 2.9 Minute Response Times During A New Product Launch, Thursday, February 25 @ 11:00am PST/ 2:00pm EST.

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Directly has sponsored this post, but the opinions are my own and don’t necessarily represent Directly’s positions or strategies.

I know Antony some, so grain of salt etc., but this is fascinating.

Diversity and Inclusion: An Update on Our Data

slackhq:

Here at Slack we are working to ensure that diversity and inclusion are fundamental components of our organization. Like many other companies, we are reevaluating and revising our recruiting practices. More broadly, we are trying to change the culture that can make Silicon Valley feel like an unwelcome place for many people. Part of transforming that culture includes accountability and transparency.

We recently reported our diversity and inclusion data in September 2015. Why are we reporting it again now? The answer is simple: we got a lot bigger very quickly, we changed our survey methodology to allow for greater inclusivity, and we have seen a shift in our diversity data since last time.

What We Found

Some notable data points:

• In our September 2015 blog post we reported about women managers at Slack. Today, 43% of our managers identify as women, and 40% of our people are managed by women, down slightly from our last report.
  
• The black engineering population at Slack has grown to 8.9% of our overall US engineering organization (and over 7.8% globally compared to just under 7% globally in our last report).
  
• In December 2015, 6.9% of our US technical employees and 4.4% of our total US employee population identified as black. Technical roles are self-reported but include product, design, engineering, QA and technical account managers.
• The Hispanic/Latino(a) population was either negligible or obscured by having a broad multiracial category in our first survey. In this most recent survey, 5.6% of our US engineering organization reported themselves to be Hispanic/Latino(a), along with 6.1% of all US technical employees.
• In our September blog post, 18% of people in our global engineering organization identified as women. That number has risen to 24% today, 26% in the US. Across all departments globally, women are currently 43% of our workforce, up from 39% in our September post.
• Often not reported among tech companies is the intersection of race and gender. Looking at women within underrepresented people of color (Native, Black, Hispanic/Latina, also frequently referred to as underrepresented minorities or “URMs”) we found that 9% of our engineering organization in the US report in these categories.
• Our LGBTQ population has grown from 10% of Slack’s global workforce in June to 13% of our global population in December.

Slack US by Race & Ethnicity

Slack Global by Race & Ethnicity

Female-identified Employees at Slack

Notes on Methodology

We did our first diversity and inclusion survey in mid-year 2015. At that time, Slack had just over 170 employees. By early December we had over 290 people. Today, just over a month into 2016, we have nearly 370 employees worldwide. That rapid growth was a key reason we re-ran the survey. Some additional context that is helpful in evaluating our results:

• Our diversity surveys are voluntarily self-reported data from employees. Surveys are anonymous. None of the data we collect about race/ethnicity, gender identity, or sexual orientation in these surveys is tied to data in our HRIS system. Some data pertaining to gender identity comes from HRIS reporting.
• The June 2015 survey only allowed for single-select on race/ethnicity, due to the limitations of our survey tool. Employees were given the option to select “multiracial” or “other,” and indicate how they would describe their racial and ethnic background. We received very clear employee feedback that a multiselect option was preferable to “other” so we made that change for our December 2015 survey.
• In both surveys, we did not get to a full 100% participation rate. However, we did get over 90% both times. Note that being short of 100% leaves a margin of error in the results, which could sway the numbers in either direction. All results are therefore approximate.
• The June 2015 report was based on global data. The December 2015 survey population was larger, allowing us to report US and global data separately. In addition to our headquarters in San Francisco, Slack has offices in Vancouver, Canada, Dublin, Ireland, and Melbourne, Australia.

This is an Ongoing Evolution

Because we are still small as companies go, every person we hire and every person who leaves can make a dramatic difference to our diversity data. For the most part, we appear to be harnessing our net growth in a positive way, but that could change. Some changes in our results could also be partly explained by the changes in survey design between the two surveys that we ran.

We recognize that we still have a long way to go. For example, while there are women leaders in our engineering and technical organizations, there are still no leadership positions in engineering, product or design held by URMs. This is a glaring omission for a company where 13% of the global engineering organization reports as URMs. One way we are starting to address this gap is by introducing the Rooney Rule into our recruiting process as we hire for more senior-level leadership roles. We also recognize that we do not yet have a woman or person of color from an underrepresented group on our board of directors. When we begin to add outside directors, addressing this will be an important priority.

All in all, our takeaway from this is that talking about diversity and inclusion keeps the issue front of mind for ourselves and our people. So we are going to keep talking about it. Of course, talk is not enough. We will continue to regularly report on our status so that we can be held accountable, and we will continue to look for ways in which we can improve.