Tidemark Leads New Wave of Innovation in Planning and Performance Excellence

Organizations succeed through continuous planning to achieve high levels of performance. For most organizations planning is not an easy process to conduct. Planning software is typically designed for only a few people in the process, such as analysts, or organizations might use spreadsheets, which are not designed for business planning across an organization. Most technologies only allow you to examine the past and not plan for the future. For decades organizations have tried to focus planning on driving better results through higher participation, but they have usually failed, as technology has not advanced enough to support this business need.

Tidemark has been working to help organizations plan and perform more VR_2012_TechAward_Winner_Logoeffectively across business, including finance and operational areas. My colleague Robert Kugel a year ago analyzed the launch of the company. Last fall it came to market with generally available applications that operate across the web and mobile technology. They are designed for business but also illustrate my point about business leading the way to cloud computing. Ventana Research awarded Tidemark our 2012 Technology Innovation Award for Finance, as the company’s efforts make finance more effective and smarter in business planning operations. Tidemark’s focus on the user experience engages users with easy–to-read metrics. The software’s ability to update the plan and let users collaborate has gained it attention from organizations looking for a better approach to planning. Early customers such as Acosta, Chuck E. Cheese’s and G&K have validated its premise of a smarter way for organizations to manage performance through analytics and planning designed for everyone in business.

Using dedicated applications to support a business process like planning is a smart idea. Our recent research into business planning vr_bti_br_whats_important_in_choosing_technologyfound that organizations that use dedicated applications report a level of accuracy of 86 percent, compared to those using spreadsheets at 60 percent. Increasing the accuracy of the plan was the top item (47%) where change could improve the value of the financial and business planning process. More importantly, 82 percent of organizations using dedicated applications indicate they have all or most of the numbers for aligning performance through planning, compared with 39 percent of those using spreadsheets. Businesses struggle to blend planning and business analytics. Integrated business planning that encompasses every department should be available for any range of customer, operational, financial, HR, sales and revenue-related needs.

Tidemark focuses on usability, which our research into business technology innovation found to be very important in 64 percent of organizations, higher than any other evaluation criteria. Its metrics and planning processes are easy for people to read, view and understand, unlike today’s typical mashup of email messages, presentations and spreadsheets, or attempts to push a set of standard charts into a dashboard view, which I have already said to be pathetic.

The new Spring 2013 release is the company’s next major product milestone. It introduces the ability to present analytics and metrics in what the company calls Tidemark Storylines – visual business-focused infographics that are dynamically created to interpret and present information about the business in a past, present and future approach that I have not seen in a product to date. Beyond this tool to help inform business and provide better methods to interpret the data, Tidemark has enhanced the business modeling capabilities that make this all possible, and this is what business analysts will love about the product. By using driver-based planning and other important approaches, the application can help provide a unified view of actual and plan data along with business charts to let users examine what changes are needed or envision what-if scenarios. Addressing one of my personal rants over the last decade, the software’s English statements on the analysis and analytic computations (metric or key indicator) make it easier to understand what you are examining, and you can change a statement to drive the presentation of the analytics. Tidemark’s focus on the visual presentation of business analytics goes well beyond that of the majority of technology suppliers in the market today. It takes only a couple of minutes of seeing the application to understand how the intuitive and interactive charts tell the business story and don’t just present the numbers.

This new release provides advancements in collaboration, vr_ngbi_br_benefits_realized_from_collaborative_biwith annotation and collaborative methods built in as part of the application. For years IT analysts have failed to understand that collaboration is the essence of what people do every day to drive improvement, and what those held accountable for business actually need. Our technology innovation research found collaboration to be the second most important priority after analytics, and having collaboration embedded within applications was the preferred method in 43 percent of organizations, over use of Microsoft Office or standalone tools. Tidemark provides collaboration within the context of the analytics and plan. It is able to integrate a range of comments or a document relevant to the analytics. It can securely store content to help with the need for disclosures, or any level of secured document storage, through a partnership with Box. Our recent research into next-generation business intelligence found that by using collaborative methods, organizations improve decision-making and have better communications than those that do not. I would assume that every organization would like these types of benefits for their business.

The next largest advancement is in how Tidemark allows for rapid configuration to make the application quick to deploy and use for a wide range of analytics and planning needs, no matter how strategic or operational they might be for an organization. It is not a one-size-fits-all approach; the Tidemark application can be adapted easily for any business process or planning needs.

vr_bti_br_technology_innovation_prioritiesAs organizations begin to realize the drawbacks of using spreadsheets and legacy applications not designed for the planning and performance processes, they will find that almost half (47%) can get to the details faster with dedicated applications compared to those that use spreadsheets alone (21%) or those that use spreadsheets with other applications (16%).  Respondents in our recent benchmark research in business technology innovation ranked business analytics their top priority (39%), in part for their importance in business planning. As organizations look at how to get better at strategic and long-range planning, they need to ensure they spend the right amount of time, as my colleague eloquently points out.

Tidemark partners with Workday to provide its products integrated with Workday’s HR and accounting applications that operate in the cloud, which are rapidly replacing on-premises ERP implementations. Tidemark also takes advantage of big data related to unstructured content using new technologies like its partner Cloudera.

Just investing in business analytics to analyze the past is not sufficient for achieving higher levels of performance. Without planning it is hard to determine what business should do to improve. Tidemark uses cloud computing and mobile technology in a unique way to advance business planning across the enterprise, and is worth your time to evaluate. Tidemark provides a strong foundation, but it should provide easier access for people to try the application for a short period of time, as I believe that once organizations try it, many will become customers. Tidemark can help meet organizations’ planning and performance needs and determine how a business can reach its full potential with its new and innovative release.


Mark Smith

CEO & Chief Research Officer

ParAccel Takes a Smart Path to Faster Analytics from Big Data

ParAccel is a well-funded big data startup, with $64 million invested in the firm so far. Only a few companies can top this level of startup funding, and most of them are service-based rather than product-based companies. Amazon has a 20 percent stake in the company and is making a big bet on the company’s technology to run its Redshift data warehouse in the cloud initiative. Microstrategy also uses ParAccel for it’s cloud offering, but holds no equity in the company.

ParAccel provides a software-based analytical platform that competes in the database appliance market, and as many in the space are increasingly trying to do, it is building analytic processes on top of the platform. On the base level, ParAccel is a massively parallel processing (MPP) database with columnar compression support, which allows for very fast query and analysis times. It is offered either as software or in an appliance configuration which, as we’ll discuss in a moment, is a different approach than many others in the space are taking. It connects with Teradata, Hadoop, Oracle and Microsoft SQL Server databases as well as financial market data such as semi-structured trading data and NYSE data through what the company calls On Demand Integration (ODI). This allows joint analysis through SQL of relational and non-relational data sources. In-database analytics offer more than 600 functions (though places on the company’s website and datasheets still say just over 500).

The company’s latest release, ParAccel 4.0, introduced product enhancements around performance as well as reliability and scalability. Performance enhancements include advanced query optimization that is said to improve aggregation performance 20X by doing “sort-aware” aggregations which tracks data properties up and down the processing pipeline. ParAccel’s own High Speed Interconnect protocol has been further optimized reducing data distribution overhead and speeding query processing. The new version 4.0 introduces new algorithms that exploit I/O patterns to pre-fetch data and store in memory, which again speeds query processing and reduced I/O overhead. The need for scalability is addressed in enhancements to enable the system to scale to 5,000 concurrent connections supporting up to 38,000 users on a single system. Its Hash Join algorithms allow for complex analytics by allowing the number of joins to fit the complexity of the analytic. Finally, interactive workload management introduces a class of persistent queries that allows short running queries and long running queries to be run side by side without impacting performance. This is particularly important as the integration of on-demand data sources through the company’s ODI approach could otherwise interfere with more interactive user requirements.

The company separates out its semi-annual database release cycle from the more iterative analytics release cycle. The new analytic functions just released just last month include a number of interesting developments for the company. Text analytics for various feeds allows for analytics across a variety of use cases, such as social media, customer comment analysis, insurance and warranty claims. In addition, functions such as sessionization and JSON parsing allow a new dimension of analytics for ParAccel as web data can now be analyzed. The new analytic capabilities allow the company to address a broad class of use cases such as “golden path analysis”, fraud detection, attribution modeling, segmentation and profiling. Interestingly, some of these use case are of the same character as those seen in the Hadoop world.

So where does ParAccel fit in the broader appliance landscape? vr_bigdata_big_data_technologies_plannedAccording to our benchmark research on big data more than 35 percent of businesses plan to use appliance technology, but the market is still fragmented. The appliance landscape can be broken down into categories that include hardware and software that run together, software that can be deployed across commodity hardware, and non-relational parallel processing paradigms such as Hadoop. This landscape gets especially interesting when we look at Amazon’s Redshift and the idea of elastic scalability on a relational data warehouse. The lack of elastic scalability in the data warehouse has been a big limitation for business; it has traditionally taken significant money, time and energy to implement.

With its “Right to Deploy” pricing strategy, ParAccel promises the same elasticity as with its on-premises deployments. The new pricing policy removes the traditional per-node pricing obstacles by offering prices based on “unlimited data” and takes into consideration the types of analytics that a company wants to deploy. This strategy may play well against companies that only sell their appliances bundled with hardware. Such vendors will have a difficult time matching ParAccel’s pricing because of their hardware-driven business model. While the offer is likely to get ParAccel invited into more consideration sets, it remains to be seen whether they win more deals based on it.

Partnerships with Amazon and MicroStrategy to provide cloud infrastructure produce a halo effect for ParAccel, but the cloud approaches compete against ParAccel’s internal sales efforts. One of the key differentiators for ParAccel as the company competes against the cloud version of itself will be the analytics that are stacked on top of the platform. Since neither Redshift nor MicroStrategy cloud offers currently license the upper parts of this value stack, customers and prospects will likely hear quite a bit about the library of 600-plus functions and the ability to address advanced analytics for clients. The extensible approach and the fact that the company has built analytics as a first class object in its database allow the architecture to address speed, scalability and analytic complexity. The one potential drawback, depending on how you look at it, is that the statistical libraries are based on user-defined-functions (UDFs) written in a procedural language. While the library integration is seamless to end users and scales well, if a company needs to customize the algorithms, data scientists must go into the underlying procedural programming language to make the changes. The upside is that the broad library of analytics can be used based on the SQL paradigm.

vr_bigdata_obstacles_to_big_data_analytics (2)While ParAccel aligns closely with the Hadoop ecosystem in order to source data, the company also seems to be welcoming opportunities to compete with Hadoop. Some of the use cases mentioned above such as so called “golden-path analysis, and others have been provided as key Hadoop analytic use cases. Furthermore, many Hadoop vendors are bringing the SQL access paradigm and traditional BI tools together with Hadoop to mitigate the skills gap in organizations. But if an MPP database like ParAccel that is built natively for relational data is also able to do big data analytics, and is able to deliver a more mature product with similar horizontal scalability and cost structure, the argument for standard SQL analytics on Hadoop becomes less compelling. If ParAccel is right, and SQL is the Lingua Franca for analytics, then they may be in a good position to fill the so called skills gap. Our benchmark research on business technology innovations shows that the biggest challenge for organizations deploying big data today revolves around staffing and training, with more than 77 percent of companies claiming that they are challenged in both categories.

ParAccel offers a unique approach in a crowded market. The new pricing policy is a brilliant stroke, as it not only will get the company invited into more bid opportunities, but it moves client conversations away from the technology-oriented three Vs and more to analytics and the business-oriented three Ws. If the company puts pricing pressure on the integrated appliance vendors, it will be interesting to see if any of those vendors begin to separate out their own software and allow it to run on commodity hardware. That would be a hard decision for them, since their underlying business models often rely on an integrated hardware/software strategy. With companies such as MicroStrategy and Amazon choosing it for their underlying analytical platforms, the company is one to watch. Depending on the use case and the organization, ParAccel’s in-database analytics should be readily considered and contrasted with other approaches.


Ventana Research