Tidemark announced the latest update to its cloud financial planning platform today, one that mixes big data from internal and external sources to give customers a way to predict what’s going to happen next, rather than simply report on what’s happened.
Tidemark CEO Christian Gheorghe says today, too many companies are looking at their financials and not seeing the whole picture because the data in the general ledger provides only so much information. “Planning in past [involved] spreadsheets with rows and columns, based on historical information,” Gheorghe told me, but he says today you can’t find all the information in the record. You need to look at external data sources to be able to predict with greater certainty how certain moves will affect the future of the company.
He uses a retail company opening a new store as an example. They could do some external market analysis or hire consultants to learn about the new markets, but Tidemark wants to make this type of decision making easier by looking at external data sources from within the Tidemark service. You can find information like average rents or average salaries in a given area and you can use this information to make more intelligent decisions.
It’s taking big data and analytics and applying it to financial planning, so that when finance sends a plan to operations, it has real details they can use to implement the plan instead of a pie-in-the-sky forecast. The new tools are built on top of Apache Spark, which provides quick access to data and can take advantage machine learning techniques to help users get at the answers they need using natural language queries.
They are looking at a variety of data sources such as weather data from weather.com or labor statistics from Open.gov and providing ways for customers to use this data to make more informed business decisions faster and more accurately than they could before.
Gheorghe says this isn’t a pivot to big data, so much as finding ways to help customers use data in more proactive ways. For him, it all starts and ends with finance and helping them make better decisions. He wants customers to be able to look at the data and build a story around that data to affect better outcomes –the ability to change the plan and test the outcome and see how different scenarios play out based on actual data, then see how these changes affect the bottom line.
As an example, one customer Reddy Ice, which supplies bags of ice to retail stores knows broad weather patterns of course. It will need more ice and more drivers in the summer than the winter, but it doesn’t know the fluctuations within those broad patterns, and by linking their operations data with weather.com data, the company can make more informed decisions about how much product they’ll need and how many drivers will be required to deliver that product with greater accuracy. And what’s more, they can do it day to day and week to week, giving them a much faster way to look at operations requirements.
