Tidemark delivers enterprise performance management (EPM) software. What that esoteric acronym means is that Tidemark helps organizations take internal data they already have and use it to plan the future steps they will take, but also to assess the historical performance of their organization. Tidemark was founded only a few short years ago (in 2009, to be precise) but has already raised close to $120 million from a host of investors over multiple rounds. Tidemark is a good example of a new breed of cloud vendor, those that were born into a world already comfortable with cloud-based enterprise tools such as Salesforce and NetSuite. Because of this fact, Tidemark hasn't had to invent a category; rather it has the somewhat easier job of delivering an existing product category but in new and beneficial ways.
Tidemark has used that impressing funding base (investors include Greylock Partners, Andreessen Horowitz, Redpoint Ventures, Tenaya Capital and Silicon Valley Bank) to gain some high-profile customers, including Netflix, Chiquita, BlackBerry, Brown University and HubSpot. Eagle-eyed readers will see that the list of customers includes a number of high-tech companies, alongside an FMCG company — both categories of business have a critical need for quick and accurate insights into their performance data so they can plan quickly and in real time.
Anyway, the company is today announcing its latest release. Some highlights of the release include:
- Tidemark Compete, a benchmarking capability for planning, budgeting and forecasting
- Machine-learning functions, to drive automatic analytic insights within the software
- Three vertical-specific offerings for retail, hospitality and insurance
Of course, the release comes with a heavy dose of buzzwords, and Tidemark throws around the fact that its latest release will have a significant part to play in the burgeoning Internet of Things (IoT). While it's hard to extend an IoT story into what Tidemark is doing, it is correct to say that the increasing complexity of the user and device landscape is meaning that the decision-making process for organizations has changed and become both more complex and collaborative.
MyPOV
This is a good release, for a number of reasons. Benchmarking is increasingly becoming readily accessible. While in the past benchmarking was both difficult to perform (generally created from manual data collection), it can now be the product of automated collection of stream data. At the same time, this move to real-time benchmarking has resulted in not only quicker and cheaper but also more accurate benchmarking abilities. organizations are increasingly seeing benchmarking as a core requirement of their operations.
Machine-learning is another idea whose time has come. The ready availability of economically priced processing power, the ability to aggregate mass data, and the increase of unstructured data in existence mean that new models toward analysis are required. Instead of needing a data scientist to massage data and find insights, organizations are increasingly wanting their technology solutions to automatically help them to "know what they don't know." Machine learning is an integral part of this.
Finally, vertical applications of horizontal technology offerings are increasingly an important way to grow a business and better deliver customer requirements. We're seeing other cloud vendors (Salesforce and NetSuite, for example) moving strongly into delivering vertical applications. As the cloud matures, it will become increasingly obvious that a simple horizontal platform approach is not sufficient.
This is a good release from Tidemark and answers some fundamental questions and trends in enterprise IT.