How To Scale Your Startup Part 4: Results

CERN’s Infinity Machine, one of the most precise measurement tools in the world

As a refresher — we’re using the metaphor of the “black box” from Andy Grove’s High Output Management to help us think about scaling.

via High Output Management

The black box is comprised of 3 parts — the input, the machine itself, and the output. If we translate this to how to think about your startup, we can say:

• Input → People
• Machine → Organizational Structure
• Output → Results

In this post, we’ll focus on the last part — results. For earlier posts, you can find the intro here, second one here, and the third one here.

The purpose of getting the right people and building the machine is to make sure that the system is producing the results you need. Most businesses are measured on standard metrics such as revenue, costs, margins, etc. Your job is to make sure that the right metrics are moving in the right directions.

This is not always easy. So a few thoughts on this below.

Dashboard

The first thing to managing your metrics is to make sure that everybody knows what the important ones are. If your team doesn’t know what the key metrics are for the business, how will they be able to change them?

The presentation of these metrics often takes the form of a dashboard. You need to make sure you define the right metrics, make sure everyone understands why they’re important, and then ensure that they’re always front & center. As Keith Rabois said —

You need to simplify the value proposition in the company’s metrics for success on a whiteboard. What does business success look to us and key inputs to those and then have someone create something that is very intuitive for every single person in the company [..] to use.

So make sure you have the company’s key metrics exposed, well understood, and easily accessible. This focuses the team and allows them to understand what is important and what success look like.

The actual format of the dashboard doesn’t matter as long as it’s easy to find & use. For SaaS, some good examples here.

Leading & Lagging Indicators

Producing results is tough because the important metrics (ie revenue) are often lagging indicators. Lagging indicators are metrics that trail the actual event(s) that took place. Meaning that by the time you see these metrics change (or don’t change), it’s too late.

For example if one of your goals is to close $50 million worth of new business this year, by the time you evaluate what you’ve actually closed at the end of the year, it’s too late to affect that number.

So in addition to tracking your lagging indicators, you need to make sure that you & your team are tracking the leading indicators. Leading indicators are metrics that signal future events. So changes in these metrics precede changes in lagging indicators.

So for the same example above — if the target is $50M for the year, you can break this up into into quarterly targets. Those quarterly numbers are the leading indicators for the $50M. So if we put our goal at $12.5M each quarter, we can evaluate each quarter and and make sure that we’re trackign towards hitting the $50M before we the end of the year.

In addition, for each quarter you can break your $12.5M quarterly goal down and put more leading indicators around that. If there are 5 stages in your sales funnel, you can track number of opportunities at each stage + conversion at each stage to get a better sense of how you’re tracking towards the $12.5M.

A decent way to structure this is to have a CEO-level dashboard with the important business metrics, and then more dashboards for each department. These department level dashboard should contain a subset of the relevant CEO-level metrics and also the leading indicators for those metrics. This way you’ll have visibility all the way up and down the business.

OKRs

Now that you have a dashboard with all of the important metrics for your business, the goal is to make sure you’re pushing them in the right directions. A common and effective way is through OKRs.

There has been a ton written about OKRs, but will do a short walkthrough of how I’ve done this and how it’s worked for us. Here’s also a template for our quarterly OKR scorecard.

As a quick primer, OKRs is a management tool that stands for Objectives and Key Results. The structure is typically 3–5 high level objectives, and then 3–5 key results per objective. Objectives are higher level goals, and the key results are tangible and quantitative results that roll up into the objective. Once set, hitting those OKRs should be the only focus of the team for the duration (quarterly).

We did a check in 1x / month to share where we were and what we’ve learned so far. Focusing on what we learned helped it be less of an update meeting and more of a learning session.

And then at the end of the quarter, we scored each key result. The scale is from 0 to 1, with 0.7 meaning you hit the target. Anything over is above and beyond. You average all the KRs to come up with a score for each O and then average your O’s for a score on the team’s output for the quarter.

Setting these OKRs become hugely important as it dictates your focus for the entire quarter. To set them we would look at our dashboard, our goals / targets, and come up with themes that were important (objectives) and then changes we wanted to make to our leading indicators (key results).

OKRs are a critical part of making sure that the team is aligned and they’re driving your metrics in the right directions. It can feel a bit silly & heavy when you’re first implementing it (and take 1–2 quarters to calibrate) but once they’re in place I’ve found no better way to focus and manage teams.

Pairing Metrics

Once you start trying to change your metrics, you have to start thinking about pairing metrics. OKRs are great for focusing and making sure important metrics are going the right way, but you have to make sure you’re protecting yourself from adverse affects. Every action has an equal and opposite reaction.

Indicators tend to direct your attention toward what they are monitoring. So because indicators direct one’s activities, you should guard against overreacting. This you can do by pairing indicators, so that together both effect and counter-effect are measured.

— Andy Grove, High Output Management

Pairing metrics help you better understand the effects and counter effects of what you’re doing. A simple example — if one of the key results was to reduce support tickets by 25%, an easy way to impact this is by just closing all the tickets, whether they’re solved or not. But that’s likely not the actual goal of that key result — the goal is probably to make sure customers are happier. So perhaps a reasonable paring metric could be ‘overall customer NPS’ to make sure we’re still maintaining quality.

So think through each metric that you’re tracking and make sure that you pair it with the appropriate pairing metric.

Conclusion

In this 4 part series we’ve now covered several things to keep in mind while scaling your startup.

To sum up — once you hit product market fit, it’s time to start scaling and thinking deeply about management. It makes a huge difference between good and great companies. And the key principle behind management is to think about things like you’re building a black box — you put something in, a process happens, and something else comes out.

The first part (the things that go in the black box) is people. For people, make sure that you spend the requisite time recruiting and finding the right ones. Once you get them, spend the time doing great onboarding to indoctrinate them and get them into the mindset of your company. And don’t forget that training doesn’t happen on its own — if the company is growing, it’s a different company every few months and you have to ‘re-onboard’ existing team members to the new company. That re-onboarding is done through training.

The next step is to design how the machine works. Have a clear org structure where everyone can see how work flows through. In addition, clearly codify and explicitly define your culture — it’s how people behave and get things done. And lastly, you want to make sure that the machine stays efficient as it grows. Common ways of maintaining efficiency during growth is through centralization / decentralization and eliminating rules.

Third is measuring the results of your startup correctly. Build a dashboard and track both leading & lagging indicators so everyone knows what is important. Then use OKRs to drive the right metrics and pair each metric to make sure you’re measuring and aware of the counter-effects.

And finally — this is all hard stuff. Running large teams and making sure that they’re focused, aligned, and producing results is really challenging. And it will be an ongoing one. You can’t do this entire thing overnight, and you also can’t blindly follow this and expect it to all work out. These are guidelines, not a prescription. But if you do these things, you’ll have a good starting point & foundation to building a great company.

So good luck and thanks for reading! If there’s anything at all I can do to help, please reach out anytime. Always happy to hear feedback, thoughts, or just chat. ✌🏽

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