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3 Things You can do to Build a Data Culture Within Your Acceleratorby@Outset_Data
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3 Things You can do to Build a Data Culture Within Your Accelerator

by OutsetNovember 14th, 2016
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Building a data culture is a strategic advantage to your accelerator, but to date it has been a huge struggle for accelerators. If we’re being honest, once a company leaves your program the team views you as a small contributor on their cap table and has fond memories of thier time in your camp. If you’re lucky they will send updates every quarter which may or may not have the data you need. Perhaps you’ll draw up mandates in your paperwork which require companies to submit specific data to you on a {choose your timeframe} basis. Perhaps those mandates will even spell out the specific portfolio management software they are to use. But all this ends in frustration as the companies just aren’t consistent in their reporting after the cohort.
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Building a data culture is a strategic advantage to your accelerator, but to date it has been a huge struggle for accelerators. If we’re being honest, once a company leaves your program the team views you as a small contributor on their cap table and has fond memories of thier time in your camp. If you’re lucky they will send updates every quarter which may or may not have the data you need. Perhaps you’ll draw up mandates in your paperwork which require companies to submit specific data to you on a {choose your timeframe} basis. Perhaps those mandates will even spell out the specific portfolio management software they are to use. But all this ends in frustration as the companies just aren’t consistent in their reporting after the cohort.

If that strikes a chord with you, you’re not alone. Data collection is the bane of the existence of many an accelerator and entrepreneur center. At Outset, we’re well aware of this frustration because we’ve dealt with it and we’ve spoken to hundreds of you who deal with it day in and day out. You’ve even thought, “It’s just not worth it. I am just going to have to accept that I have limited visibility into my portfolio. These tools look great, but they don’t get the job done.”

So how in the world do you build a culture that LOVES data and that transfers that love onto your cohort and portfolio companies? In today’s startup environment data is a must. How do your startups know what to focus on if they don’t even know their Customer Churn is running 12% or that their Customer Lifetime Value is dropping like a rock?

The easiest and most effective way to build that data culture within your startups is to automate the data collection process and show them that with no additional effort each of their metrics is updated on an ongoing basis so that they know exactly where they stand in real time. If a team us unable to see the value in this, that team may need to reconsider whether or not this is a journey they are willing to make. I know that sounds like a hard nosed stance, but I’m willing to bet your goal is to build a startup portfolio that will stand the test of time and prevail in the face of adversity. You can’t do that without loving your numbers, good, bad or indifferent.

So what are the key ways to develop that culture

Transfer appreciation & respect for data in every activity you undertake.

  • Tie EVERYTHING back into data. If data is mumbled once or twice at the beginning of the cohort and then only requested occasionally thereafter your teams aren’t going to understand how important it is to you and thereby will not understand how important it is to them.
  • Ideal customer profiles, have them give you the number of people they’ve interviewed to develop that profile.
  • Facebook ad campaign, make sure they give you the Customer Acquisition Cost and the Customer Lifetime Value of that specific campaign.
  • Define the MVP, make sure they keep track of the number of calls they’ve made compared to the number of interviews they’ve had.

Make tracking effortless & it MUST be useful to the companies.

  • Great UI only takes you so far. If you and the teams have to sit around and figure out what to track there’s a good chance you’ll find yourself suffering from analysis paralysis. The process needs to be as automated as possible. If the dashboard is not automatically setup for you and/or your teams you will need to budget some time into figuring out what is important to you. With automated dashboards you and your teams get a jump on what is important from a KPI perspective. If you want to add more later, you can, but your standard metrics are defined & captured automatically.
  • API connections. This is something almost all portfolio software has, but without the automated, out of the box dashboard setup previously discussed it still requires time and energy to get functioning properly.

Showcase the power of data.

  • This falls in line with number one, but it has more to do with show, not tell. This is a common mantra in the startup culture, but not so much when it comes to data. You need a single case study that displays the benefit of a startup focusing on data. “Company A had sparse data collection when they tried to raise their seed round and struggled to give investors comfort in how they were going to generate traction. Meanwhile Company B knew the Customer Lifetime Value from their pilot, they had a solid understanding of what their Customer Acquisition Cost was going to be going forward and they knew their Customer Churn rate was high, but that the new functionality driven by real user feedback should drop the churn rate by 50% bringing it inline with their CAC and LTV. MRR is expected to be $10,000 at the completion of their general release.”

The tools today don’t allow for the transfer of enthusiasm and respect surrounding data. They are designed beautifully in both UI and functionality, but they lack key components which drive the adoption of a data centric culture. While you’re not ultimately responsible for building that data culture within a specific company, you are within your accelerator. If you have that love for data and access to the tools that make it work effortlessly you will find that companies will naturally begin to embrace the data centric view.