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News 11
| Date | Title | Description |
| 11.08.2020 | What to do... | What to do when demand increas... |
| 28.07.2020 | Measuring ... | One of the most important aspe... |
| 24.06.2020 | The Scienc... | 3;...using near term activities:;;For example, a company may have the following assumptions and results:;;Similar to the leading indicator cohort analysis, we can now instrument the leading indicators into daily, weekly, or monthly activity charts to evaluate our progress toward go-to-market fit.;;The dashboard above provides monthly, and potentially weekly, updates on how we are tracking against long term unit economics. We are in good shape if the blue line stays above the red line. A few considerations are as follows:;With a scientific, data-driven definition of go-to-market fit, we can now evolve our GTM decisions to align with this new “north star” for the organization. Similar to the prior phase, we need to evolve each component of the GTM strategy to achieve scalable unit economics while preserving customer retention.;;Pages 20 to 29 in the Science of Scaling eBook elaborates on the considerations behind these GTM decisions.;Download eBook: The Science of Scaling A scientific, data-driven approach to two critical questions: When to scale? How fast?;Phase 3: Growth and Moat;We now have established a more rigorous framework for the first question, “when to scale?”. In summary:;;But what about the second question, “how fast”?;Our approach to initial scale is another common cause of Series A failure. All too often, once we decide it is time to scale, we hire a number of salespeople all at once. Usually this behavior occurs at the start of a fiscal year or right after a funding round. Pretty much every company I looked at over the past few years took this approach to scale at some point. I never really saw it work. I am sure successes are out there. I just haven’t seen it. Most of the time, these companies hired 10 salespeople in January and 2 were left at the end of the year.;When we stop and think about it, the reason for the massive rate of failure with this approach is somewhat obvious. We have not developed the prerequisite organizational capabilities to hire, on-board, feed, and manage that many salespeople at once. Let’s just reflect on the hiring piece for a minute. If a company decides to scale and establishes a plan to hire 10 salespeople next month, think about the new capabilities they need to find time for almost overnight. Think about how many in-person interviews are needed to land 10 great salespeople. Think about how many phone screens are needed. With the sudden surge of additional work on our already busy schedules, we rush through these efforts and make suboptimal hiring decisions. Furthermore, we don’t really know what we are looking for. We have never done it before. What if our hiring criteria are wrong? We have just multiplied an already expensive mistake by 10! That will probably kill our company.;For these reasons, we need to think about scale as a pace, not a single lump sum event. A best-in-class scale plan is not 10 salespeople next month and then see what happens. It is 2 salespeople a month for the next six months. If things break, we can stop and fix them. If they do not, we can go faster.;However, we still have not addressed the question “how fast?”.;Here is the answer. We should scale as fast as possible without losing product-market and go-to-market fit. Scale will compromise product-market and go-to-market fit. At this stage of our venture, the ten of us sitting around the office have figured out how to acquire customers, make them consistently successful, and do so in a profitable manner. However, can we now go out and acquire hundreds of employees over the next few years and teach them to do it? That is an even more difficult problem.;Therefore, we should scale as fast as possible without losing product-market and go-to-market fit. Fortunately, we know exactly how to measure product-market and go-to-market fit. In fact, we know how to measure leading indicators to inform us months in advance if these metrics look to be compromised. We use the leading indicator to customer retention chart we developed in the product-market-fit section and the leading indicator to scalable unit economics chart that we developed in the go-to-market fit section.;These two charts become our speedometer.;;How fast should we scale? Establish a pace and watch the speedometer. If the speedometer breaks, slow down and fix the issue. If the speedometer looks good, accelerate. At the next board meeting, when our investors put pressure on us to scale as fast as possible, we can now come back to them with a predictable plan. “Our plan is to hire 2 salespeople a month for the next 6 months and monitor our leading indicators. If they are good, we will accelerate to 4 salespeople a month for 6 months. If they still look good after another 6 months, we will accelerate to 8, and so on.” Now we have a scientific, data-driven approach to scale.;With growth comes a new set of risks. We mitigate these risks by aligning the components of our GTM strategy with growth.;;;Pages 31 to 44 in the Science of Scaling eBook elaborates on the considerations behind these GTM decisions.;Download eBook: The Science of Scaling A scientific, data-driven approach to two critical questions: When to scale? How fast?;Conclusion;“When should we scale? How fast?”;This decision is so critical to startup execution and success. Yet, as an entrepreneur community we approach it with qualitative instincts rather than data-driven science. I hope this article has inspired an alternative approach.;It is important to note that I am not arguing for slower growth. I am encouraging healthier growth. While following these frameworks may yield a slower revenue outcome in the following quarter, they will lead to long term success faster and at a higher success rate.;Also keep in mind that I have only been iterating with this framework for about three years. Every discussion with an entrepreneur, I learn and codify further. In a way, it is simply an aggregation of what I have learned from all of you. The learning process is not over. I welcome feedback, positive and negative, so as an entrepreneurial community we can further demystify the science of scaling.;Download eBook: The Science of Scaling A scientific, data-driven approach to two critical questions: When to scale? How fast?">Should we re-establish growth ... |
| 11.06.2020 | Using Surv... | Whether understanding employee... |
| 03.06.2020 | Coaching Y... | “Bad news. The deal is slipp... |
| 26.05.2020 | I Cut My M... | Our campaign budget has been c... |
| 20.05.2020 | How to imp... | Now that we are two months in,... |
| - | Matching S... | Across the globe, almost every... |
| - | [ROLE PLAY... | For most businesses, economic ... |
| - | Crisis Man... | Organizations look to their CE... |
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| Date | Title | Description | Category | Author | Source |
| 19.06.2019 | Enboarder ... | By LAURA LOREK, Publisher of S... | - | - | siliconhil... |