Every organisation wants to be ‘data-driven’ these days — but not all are using data as cleverly as they could be.
Smart use of data can help companies nail funding rounds, make better product decisions and — an especially important one at times like these — keep a very close eye on cashflow.
But all this data can also feel intimidating. Software company Oracle NetSuite found that 94% of us feel overwhelmed making decisions at work, and having data coming out of your ears doesn’t help.
So, to figure out how businesses can get a handle on data to drive performance, we gathered a panel of experts featuring Dave Rosenberg, head of marketing and business development and private equity EMEA for Oracle NetSuite, Melissa McCracken, an investor at cancer therapeutics focused VC Nextech Invest and Tatiana Okhotina, chief financial officer at money transfer service Azimo.
Here are the main takeaways:
1) There are heaps of tools to help you utilise and understand financial data
Adios, old Excel spreadsheets, data analytics has come a long way from manually sifting through thousands of rows and columns. The tools that are available for companies to collect data today are much more advanced, and you should take advantage of them.
Okhotina recommends using tools like Domo, Google for data warehousing and Google Data Studio for visualising analytics. And those aren’t the only tools Azimo uses: “We have built an internal treasury management system, which is custom-made based on different data integration. We also use NetSuite for financial reporting… which isn’t heavy on data inputs and gives us timely and accurate results.”
“Go take an online class in data science or whatever it may be, because you can very quickly see the gaps in your business where you don’t understand…”
McCracken says knowing when to build tools out is as important as which tools you use. She recommends using an electronic lab notebook (ELN), which can be a great tool for data scientists to track resources. These can help companies keep an eye on cost, time spent on projects and the allocation of teams — and make business operations run more smoothly as a result.
It’s a good idea to keep learning about new tools, says Rosenberg. “Go take an online class in data science or whatever it may be, because you can very quickly see the gaps in your business where you don’t understand, whether it’s forecasting, inventory or something else.”
2) Integrate data analytics early on — it’ll help a lot in the long run
Using data from the outset is crucial. McCracken says that it’s important that investors see that companies can utilise data from an early stage. Startups should refer to their data when presenting financial plans for the next few years, to demonstrate current and potential future growth based on different data-based scenarios.
“Without having the right data to see how you’re growing, you can’t really make an educated decision.”
“We see ourselves as long-term investors, taking a long-term view on the company. I would say we would never be able to invest in a company where we didn’t feel that there was a good financial plan of how to grow, and that’s what needs to be achieved,” she says.
“Without having the right data to see how you’re growing, [an investor] can’t really make an educated decision.”
3) Deploy data teams when and where necessary
Okhotina stresses the importance of having data science teams that can help make decisions in different parts of the business and facilitate growth, based on her experience at Azimo.
Azimo has embedded data scientists within its product teams, which Okhotina says makes it easier to make data-driven decisions about product development. As a result, she says it’s easier to develop and derive key performance indicators (KPIs) if you have data analysts within the team instead of relying on external resources, overall reflecting that Azimo’s “performance and monitoring has improved.”
For other businesses, Okhotina says that the people you need to gather and use data successfully depends on the stage and position of the business. She says that you may not need to invest in data if the current business stage isn’t “dynamic.” If the business requires complex decision making, however, Okhotina recommends that it’s better to hire people who can source data sets for the business.
But that doesn’t necessarily mean that you need the whole data team within your business: “What you could do early on is outsource [the data] and have your internal management team partially manage the data sets. You can then grow the team from there,” says Okhotina.
4) Don’t just collect data, use it
“Most [businesses] don’t do data properly,” says Rosenberg, meaning that while many companies gather data, most don’t know how to utilise it. He adds that credit card companies like Visa do a better job of this, while travel companies are good at changing their pricing frequently online. He thinks that tech companies, and large ones in particular, struggle to source and use their data well because of their scale.
“It’s one thing to say that you’re data driven and that’s how you make your choices, and another to say you actually use that and balance the qualitative and quantitative.”
“Most [businesses] don’t do data properly.”
McCracken points out that many businesses don’t collect enough data and need to work to reverse that, even if they may not use the data at later points — because there’s no going back. “Sometimes I think people aren’t collecting as much data as they could, even if they’re not going to analyse it later. I would say the hard part with science and biology is, once you missed the opportunity you’ve missed it — so I always encourage that [businesses] collect more.”
Data analysis and management has become more commonplace in business operations in general — which means it’s easier for companies of all kinds to follow suit. “What was once a trade secret has become so commonplace that everybody should do it,” says Rosenberg.
5) Dazzle your investors with data
It’s unlikely that you’ll win over investors without some hard data that clearly shows where your business is going in the next year or two. As a CFO of a startup, Okhotina has noticed what investors look for when it comes to companies’ financial data.
Investors are looking for a strong business model which gives a sense that the company has an idea what is going to happen in the next few years, and an understanding of the different scenarios that could happen, she says. “Being able to demonstrate [all these different things] is really, really important.”
Okhotina also advises companies to understand factors like consumer behaviour and product development through data. “Keep investors in the loop about what decisions you are making and how data is relevant for your specific business model,” she says.
Many thanks to Oracle NetSuite for sponsoring this virtual event — and thank you very much to our panel. Missed the live event? Catch up on the webinar here.
We’d love to continue holding webinars like this in the future. If you’d like to partner with us and sponsor one of our virtual panels, get in touch with [email protected]