Amanda Kattan, a data and finance consultant with over a decade of investing and operating experience, shares her insights about what startups can do to set themselves up for data-driven success. She shows us how startups can get ahead with the right data stack, fundraising process, and the organizational metrics that best represent their business.
Tell us about your path to consulting for startups. How did you start getting involved in this environment?
I started my career in roles that were heavily analytical - initially investment banking, management consulting, and private equity. I knew I loved numbers and models, but I soon discovered that I also loved working with management teams and entrepreneurs. Over time, I moved into operations where I served in a variety of finance, data and strategy roles for PE and VC backed businesses. Across all of these roles, an ability to leverage data was instrumental in driving impact.
I now work with startups to build the data infrastructure that will set them up for success. Having been an investor and an operator, I’m able to leverage both “sides of the table” to ensure my startups are staying focused on the things that really drive value at their stage of funding.
What are some pitfalls that startups are facing during fundraising?
Fundraising is hard work, and it’s even harder to do when you’re growing your business at the same time. You can’t take “time off” from operating the business to go out and spend months fundraising. Get the right expertise and support to ensure you maximize both business and fundraise outcomes.
Preparation is key. Rehearse your pitch. Scrub your numbers. Updating your model and your pitch decks when you’re in a dozen simultaneous conversations with different firms is a nightmare. Get it organized before you start.
Past success is great but not everything. A clear path to future success is essential. You can build confidence in your company and your team by demonstrating a culture of data driven decision making, measurement and analysis. Be obsessive about your results and those of your competition, dig deeper than your headline metrics, and understand your unit economics inside out.
Pay attention to the questions you are being asked and where the investor is focusing their diligence efforts. Finding a partner who gets ‘you’ can make a huge difference when you need it most.
What kinds of clients do you have and what problems are you helping them solve?
My favorite clients are curious, hungry, and have a degree of complexity to their business. They come to me to help them leverage their data to drive better decision making at all levels of the company. I focus my impact on the following four areas:
Designing the value creation framework: What are we looking to optimize and what are the drivers of that success? How do we design metrics that balance the tradeoffs so that we grow efficiently and sustainably over time?
Forecasting and goal setting: Where do we want to go, how will we get there, what will it cost, and how can we evaluate new investments along the way?
Reporting and communication: How do we ensure everyone is aligned, focused, and operating from a position of maximum knowledge? How do we create an organization that is continuously experimenting, measuring and sharing their learnings?
Tools and systems: How do we build a data infrastructure that provides timely, reliable data that promotes access, transparency and accountability? How do we maximize reporting effectiveness so that it is clear, concise and action oriented?
Fundraising puts a magnifying lens on the assumptions around your business model. I work with companies raising seed to series C on all aspects of their raise - the pitch, financial model, data room, and diligence. As a business matures, data becomes the most powerful tool in illustrating the compelling features of your company. A single question can be answered in a multitude of ways - the more intimately you understand your customer cohorts by time, type, and size, etc. the better chance you have of conveying (and running) your business successfully.
As a business matures, data becomes the most powerful tool in illustrating the compelling features of your company.
What data analytics tools do you use for your clients?
Simplicity is key – I look for tools that everyone can easily access, use and audit. Especially in a startup where speed is important, requiring permission from a “gatekeeper” like IT to change a report or analyze a new data source can really slow you down.
The tools I use most often are Chartio and Google Sheets. I love Chartio because it is intuitive for business users – I can connect the usual data sources (quickbooks, salesforce, google sheets) and build an executive dashboard in a matter of hours. Chartio ‘thinks’ like a typical spreadsheet, only superpowered with an ability to transform and clean data in a plethora of ways. Google Sheets is not as powerful as a true data warehouse but it is the best tool for rapidly iterating on a financial model that can be fed in real-time to Chartio for analytics and reporting.
I love Chartio because it is intuitive for business users — I can connect the usual data sources (quickbooks, salesforce, google sheets) and build an executive dashboard in a matter of hours.
Do you have a set of key metrics as a blueprint that you always create for your clients?
Our overreliance on “standard” metrics is very dangerous. There are certainly some important, boilerplate metrics you should be aware of, especially for modern SaaS businesses: CAC, LTV, Sales Magic Number and so on. But sticking exclusively to these can distract you from telling your story, and finding the right metrics for your business. With most of my clients, I’ve worked with leadership to come up with custom metrics to tell the story that the standard ones don’t. If you find yourself saying ‘yes, but…’ a lot when presenting your metrics, you likely aren’t using the right ones.
I’m a big fan of highlighting tradeoffs in metrics - growth is not free, and metrics that reflect efficiency as well as growth help structure businesses in ways that are more sustainable in the long run.
What are some of the major challenges you face when helping startups work more with their data?
Some companies don’t practice good “data hygiene” because they are so focused on day-to-day operations. As a result, key business data is incomplete and difficult to analyze. Cleaning data is a frustrating and time consuming exercise that often gets repeated many times by many people, when it could have been avoided by properly structuring the data at the onset. This is one area where Chartio is exceptionally helpful in the ‘clean up’. You can connect to the data source and make adjustments that will carry forward to hundreds of tables or charts.
I’ve seen other companies make the opposite mistake and over-invest in the data infrastructure and start tracking everything. They collect and report on many different metrics and analyze their business in a very precise way. They are stubborn about having exact metrics that require hours of manual input versus a proxy that gets 90% of the way there in a fraction of the time. They continuously ask for more data, as a way to put off acting on what is in front of them. That’s neither appropriate nor wise in a startup where focus and rapid execution is key. Whenever you start tracking a metric, you should ask “why is this a key driver for the business?” If you don’t have a clear answer, then reconsider what you’re doing.
What is a project that has been particularly inspiring to you?
One of my clients, RaiseMe, is a microscholarship platform that devoted to making college accessible to students throughout the country. There are so many biases in our education system that are preventing students of certain genders, demographics and ethnicities from achieving their potential. RaiseMe uses their data to measure impact, fight against biases and democratize their platform. The team is devoted, honest and committed to their mission.
When data is used to drive a meaningful impact in people’s lives, my work becomes incredibly rewarding.
Do you have advice on how to get people to rely more on data for decision making?
Focus on driving value rather than volume – slides may be free, but your audience’s attention isn’t – if a metric or report isn’t providing insight, get rid of it. Prove the value of data-driven decision making and evidence based management with concrete examples that are easy to understand and actionable, tied to key business objectives, and tell a story with a logical conclusion. Ask yourself ‘what should we be taking away from this number or report?’ and then make sure it’s spelled out!
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