Executive Summary

Collaborative Analytics

Analytics almost universally involves collaboration among a team of individuals. Interpreting the results of the analyses, choosing a course of action and tracking the implementation of those actions spans multiple roles and departments within an organization. As a result, most of today’s analytics and business intelligence (BI) products support some form of collaboration.

Capabilities that support the sharing of — and communication about — output from analytical processes help organizations maximize the value of their analytics investments. Facilitating communication and collaboration among those involved in the decision-making process leads to more informed and better decisions. Our research shows that nearly four in 10 organizations are using collaboration to support analytics processes, and more than one-half said they expect to use these capabilities in the future. Analytics and BI vendors have recognized the value of collaboration and have increasingly been incorporating these capabilities into their products.

More than a decade ago, social media tools like Facebook, Twitter and LinkedIn brought on a wave of collaborative analytics and BI capabilities. We saw chat streams associated with specific analyses that users could like or endorse. The number of contributions a user made to the community was part of his or her profile so others could accordingly weigh the importance of the input. However, after an initial surge of interest, these efforts failed to gain traction and waned.

Collaboration requires a large community of active individuals, and there simply were not enough people regularly engaged in using the analytic products. Those early efforts also required users to participate in the dialog from within the analytics and BI products. Rather than working solely with those products, line-of-business personnel spend their days using a variety of business applications.

Two major changes now provide the glue to pull a community of collaborators together: mobile devices and enterprise collaboration tools. The significant expansion of mobile analytics and BI has made it easier for users to get involved. Perhaps more importantly, in the same way the social media users get notifications of activity via mobile devices, collaborative analytics and BI vendors use mobile notifications to engage participants in the analytics process. Organizations have also adopted more widespread use of enterprise collaboration technologies in place of or in addition to email and is more widely available.

The analytics process typically involves multiple people with differing areas of expertise and responsibilities. Collaborative tools can enable this diverse group of participants to coordinate their activities and share knowledge. To be most effective, collaborative capabilities should cover the entire data and analytics process; only this way can participants understand the provenance of data as it is analyzed.

With this approach, it is easy to identify subject matter experts to engage in the dialog. The team can discuss and document decision-making for compliance purposes, and the actions resulting from those decisions can be assigned and tracked to completion. We expect that by 2025, 8 in 10 BI software platforms will include collaborative capabilities designed to support organizations’ decision-making, task management and compliance requirements associated with analytics. These types of capabilities should be a standard part of analytic processes in much the same way that visualization is now a standard part of data and analytic processes.

As organizations embrace more sophisticated analytics such as artificial intelligence (AI) and machine learning (ML), and as analytics become more easily accessible via technologies such as natural language processing (NLP), collaboration capabilities will become even more important. However, strong collaboration capabilities alone are insufficient. These capabilities also must include strong analytics. Our Value Index assessment methodology takes all these factors into account.

This research evaluates the following vendors that offer products that address key elements of collaborative analytics as we define it: AWS, Cloud Software Systems, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau, ThoughtSpot and Zoho.

Buyers Guide Overview

For over two decades, Ventana Research has conducted market research in a spectrum of areas across business applications, tools and technologies. Ventana Research has designed the Buyers Guide to provide a balanced perspective of vendors and products that is rooted in an understanding of the business requirement in any organization. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select technology vendors and products. The findings of this research undertaking contribute to our comprehensive approach to ranking and rating vendors in a manner that is based on the assessments completed by an organization.

This Ventana Research Buyers Guide: Collaborative Analytics is the distillation of over a year of market and product research efforts. It is an assessment of how well vendors’ offerings will address organizations requirements for collaborative analytics software. The index is structured to support a request for information (RFI) that could be used in the RFP process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with technology vendors. An effective product and customer experience with a technology vendor can ensure the best long-term relationship and value achieved from a resource and financial investment.

In this Buyers Guide, Ventana Research evaluates the software in seven key categories that are weighted to reflect buyers’ needs based on our expertise and research. Five are product-experience related: Adaptability, Capability, Manageability, Reliability, and Usability. In addition, we consider two customer-experience categories: Validation, and Total Cost of Ownership and Return on Investment (TCO/ROI). To assess functionality, one of the components of capability, we applied the Ventana Research Value Index methodology and blueprint, which links the personas and processes for collaborative analytics to an organization’s requirements.

The structure of the research reflects our understanding that the effective evaluation of vendors and products involves far more than just examining product features, potential revenue or customers generated from a vendor’s marketing and sales efforts. We believe it is important to take a comprehensive research-based approach, since making the wrong choice of a collaborative analytics technology can raise the total cost of ownership, lower the return on investment and hamper an organization’s ability to reach its potential performance. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on a short list of vendors that does not represent a best fit for your organization.

To ensure the accuracy of the information we collected, we asked participating vendors to provide product and company information across the seven product and customer experience categories that, taken together, reflect the concerns of a well-crafted RFI. Ventana Research then validated the information, first independently through our database of product information and extensive web-based research, and then in consultation with the vendors. Most selected vendors also participated in a one-on-one session providing an overview and demonstration, after which we requested they provide additional documentation to support any new input.

Ventana Research believes that an objective review of vendors and products is a critical business strategy for the adoption and implementation of collaborative analytics software and applications. An organization’s review should include a thorough analysis of both what is possible and what is relevant. We urge organizations to do a thorough job of evaluating collaborative analytics systems and tools and offer this Buyers Guide as both the results of our in-depth analysis of these vendors and as an evaluation methodology.

How To Use This Buyers Guide

Evaluating Vendors: The Process

We recommend using the Buyers Guide to assess and evaluate new or existing technology vendors for your organization. The market research can be used as an evaluation framework to establish a formal request for information from technology vendors on their products and customer experience and will shorten the cycle time when creating a RFI. The steps listed below provide a process that can facilitate best possible outcomes.

1. Define the business case and goals.
   Define the mission and business case for investment and the expected outcomes from your organizational and technology efforts. 
2. Specify the business needs.
   Defining the business requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
3. Assess the required roles and responsibilities.
   Identify the individuals required for success at every level of the organization from executives to front line workers and determine the needs of each. 
4. Outline the project’s critical path.
   What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan. 
5. Ascertain the technology approach.
   Determine the business and technology approach that most closely aligns to your organization’s requirements. 
6. Establish technology vendor evaluation criteria.
   Utilize the product experience: Adaptability, Capability, Manageability, Reliability and Usability, and the customer experience in TCO/ROI and Validation. 
7. Evaluate and select the technology properly.
   Weight the categories in the technology evaluation criteria to reflect your organization’s priorities to determine the short list of vendors and products.
8. Establish the business initiative team to start the project.
   Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources. 

The Findings

The products we evaluated vary widely in their collaborative analytics capabilities, with some vendors heavily invested in collaborative capabilities and others limited to sharing data and analyses. While sharing data and analyses helps support collaboration among participants in the analytics process, much more can be done. Those vendors that went beyond traditional BI and whose products incorporate capabilities such as threaded discussion groups and task management performed better in our assessment. These capabilities can be provided via integration with third party products or directly embedded within the vendor’s offering. You may decide that one approach or the other is a better match your organization’s established practices or support a broader collaboration initiative that is driving the purchase of new software.

Factors beyond features and functions or vendor assessments may also become a deciding factor. For example, an organization may face budget constraints such that the TCO evaluation can tip the balance to one vendor or another. This is where the Value Index methodology and the appropriate category weighting can be applied to determine the best fit of vendors and products to your specific needs.

Scoring of Vendors Across All Categories

The research finds SAP first on the list with IBM in second place and Domo in third. Companies that place in the top three of a category earn the designation of Leader. Oracle has done so in six of the seven categories; SAP in five; IBM in four; Domo and Qlik in two and Sisense and Tableau in one category.

The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the vendors. Those vendors whose Product Experience have a higher weighted performance to the axis in aggregate of the five product categories place farther to the right, while the performance and weighting for the two Customer Experience categories determines their placement on the vertical axis. In short, vendors that place closer to the upper-right on this chart performed better than those closer to the lower-left.

The research places vendors into one of four overall categories: Assurance, Exemplary, Merit or Innovative. This representation classifies vendors overall weighted performance.

Exemplary: The categorization and placement of vendors in Exemplary (upper right) represent those that performed the best in meeting the overall Product and Customer Experience requirements. The vendors awarded Exemplary are: Domo, IBM, Oracle, SAP, Tableau and Zoho.

Innovative: The categorization and placement of vendors in Innovative (lower right) represent those that performed the best in meeting the overall Product Experience requirements but did not achieve the highest levels of requirements in Customer Experience. The vendors awarded Innovative are: Idera, Microsoft, MicroStrategy and Pyramid Analytics.

Assurance: The categorization and placement of vendors in Assurance (upper left) represent those that achieved the highest levels in the overall Customer Experience requirements but did not achieve the highest levels of Product Experience. The vendors awarded Assurance are: GoodData, Incorta, insightsoftware and Sisense.

Merit: The categorization for vendors in Merit (lower left) represent those that did not exceed the median of performance in Customer or Product Experience or surpass the threshold for the other three categories. The vendors awarded Merit are: AWS, Cloud Software Group, Google, Infor, SAS, Sigma Computing and ThoughtSpot.

We warn that close vendor placement proximity should not be taken to imply that the packages evaluated are functionally identical or equally well suited for use by every organization or for a specific process. Although there is a high degree of commonality in how organizations handle collaborative analytics, there are many idiosyncrasies and differences in how they do these functions that can make one vendor’s offering a better fit than another’s for a particular organization’s needs.

We advise organizations to assess and evaluate vendors based on their requirements and use this research as a reference to their own evaluation of a vendor and products.

Product Experience

The process of researching products to address an organization’s needs should be comprehensive. Our Value Index methodology examines Product Experience and how it aligns with an organization’s life cycle of onboarding, configuration, operations, usage and maintenance. Too often, vendors are not evaluated for the entirety of the products; instead, they are evaluated on market execution and vision of the future, which are flawed since they do not represent an organization’s requirements but how the vendor operates. As more vendors orient to a complete product experience, the more robust of an evaluation can be conducted.

The research based on the methodology of expertise identified the weighting of Product Experience to 80% or four-fifths of the total evaluation. Importance was placed on the categories as follows: Usability (10%), Capability (50%), Reliability (10%), Adaptability (10%) and Manageability (10%). This weighting impacted the resulting overall rankings in this research. SAP, IBM and Domo were designated Product Experience Leaders as a result of their commitment to collaborative analytics technology. Vendor rankings for Microsoft, Oracle and Tableau were found to meet a broad range of enterprise collaborative analytics requirements. While collaborative analytics were given more weight in our assessment, core analytics capabilities were also considered a requirement.

Many organizations will only evaluate capabilities for analysts or those in IT and administration, but the research identified the criticality of Usability (10% weighting) across a broader set of usage personas that should participate in collaborative analytics. Many of these individuals are not involved in the analytics process on a daily basis and therefore have different requirements for usability.

Customer Experience

The importance of a customer relationship with a vendor is essential to the actual success of the products and technology. The advancement of the Customer Experience and the entire life cycle an organization has with its vendor is critical for ensuring satisfaction in working with that vendor. Technology providers that have Chief Customer Officers area more likely to have greater investments in the customer relationship and focus more on their success. These leaders also need to take responsibility for ensuring the marketing of their commitment is on website and in the buying process and customer journey.

Our Value Index methodology weights Customer Experience at 10%, or one-tenth, as it relates to the framework of commitment and value to the vendor-customer relationship. The two evaluation categories are Validation (5%) and TCO/ROI (5%), and weighted to represent their importance to the overall research.

The vendors that rank the highest overall in the aggregated and weighted Customer Experience categories are Oracle, SAP and Qlik. These category leaders in Customer Experience best communicate their commitment to customer needs. Vendors such as Tableau, Domo, IBM and Zoho were not Overall Leaders, but have a commitment to customer experience.

There were many vendors that have not made Customer Experience a priority and provide little to no information through their website and presentations for our evaluation. Many have customer case studies to promote their success, but lacked depth on what they do to provide their commitment to an organizations’ journey to collaborative analytics. It is difficult for organizations to evaluate vendors on the merits of their commitment to customer success. As a result, many of the vendors did not rank as well in Customer Experience, though it does not mean their products will not provide collaborative analytics. As the commitment to a vendor is a continuous investment, the importance of supporting customer experience in a holistic evaluation should be included and not underestimated.

Appendix: Vendor Inclusion

For inclusion in the Ventana Research Collaborative Analytics Buyers Guide for 2023, a vendor must be in good standing financially and ethically, have more than 50 dedicated workers, at least $50 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 100 customers. The principal source of the relevant business unit’s revenue must be software-related and there must have been at least one major software release in the last 18 months. The product must be actively marketed as an analytics product and capable of accessing data from a variety of sources, modeling the data for analysis, analyzing the data using a variety of techniques, communicating the results in a variety of ways and supporting the data and analytics processes within an organization.

The research is designed to be independent of the specifics of vendor packaging and pricing. To represent the real-world environment in which businesses operate, we include vendors that offer suites or packages of products that may include relevant individual modules or applications. If a vendor is actively marketing, selling and developing a product for the general market and is reflected on its website that it is within the scope of the research, that vendor is automatically evaluated for inclusion. 

All vendors that offer relevant collaborative analytics products and meet the inclusion requirements were invited to participate in the research evaluation process at no cost to them.

Eleven of the 22 vendors responded positively to our requests for additional information and provided completed questionnaires and demonstrations to help in our evaluation of their embedded analytics products. We categorize participation as follows:

Complete participation: The following vendors actively participated and provided completed questionnaires and demonstrations to help in our evaluation of their product: Domo, GoodData, IBM, insightsoftware, Oracle, Pyramid Analytics, Qlik, SAP, Sisense, Tableau and Zoho. 

Partial participation: The following vendors provided limited information to help in our evaluation: Incorta, Infor and MicroStrategy.

No participation: The following vendors provided no information or did not respond to our request: AWS, Cloud Software Group, Google, Idera, Microsoft, SAS, Sigma Computing and ThoughtSpot.

Vendors that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have significant impact on their classification and rating, we recommend additional scrutiny when evaluating those vendors.

Products Evaluated

Vendors of Note

We did not include vendors that, as a result of our research and analysis, did not satisfy the criteria for inclusion in the Buyers Guide. These are listed below as “Vendors of Note.”