Does Gartner’s “Cool Vendor” Report Mean Anything?

Does Gartner’s “Cool Vendor” Report Mean Anything?

Every year, Gartner, one of the world’s leading IT research companies, publishes a Cool Vendor Report highlighting new technologies in Analytics and Data Science. This year, Digital Hive (formally known as Theia) received this recognition. Previous Gartner Cool Vendors include Tableau, Snowflake, and Looker just to name a few. Many CDO’s and CTO’s use Gartner to help successfully guide their IT strategy and technology purchasing decisions.

So, does being named a Gartner Cool Vendor mean anything to Digital HiveYES!

The Intersection of Need and Solution

Gartner analysts are some of the most informed middle-men in the world. Working with both technology vendors and enterprise data leaders, they sit at an incredibly valuable intersection of information. It’s at this intersection that Gartner is able to provide value, having 1000’s of conversations a year on both sides of the fence, identifying emerging challenges and the technologies that will provide a solution. 

Validation of Enterprise Need

For Digital Hive, being named a Gartner Cool Vendor is a validation that the use of many BI & Analytics tools within large enterprises is creating real problems for end-users with BI Adoption, Data Literacy, and meaningful ROI. Companies are now in a full-sprint race to go digital, maximize the value of their data, and provide more meaningful experiences. Without frictionless access to information, meaningful data literacy education, and a push for greater user adoption, many companies are going to see the millions they invested in data & analytics go down the drain.

Even more, we now have the validation that a multi-tool tech stack is NOT going away. Co-existence is needed. If consolidating to a single BI tool is on your roadmap, be forewarned it’s a long, expensive, and ever-changing journey. Every year innovations in data & analytics produce new tools and vendors, making it necessary for companies to keep pace and maintain a competitive edge.

A Rise in Vendor Competition

For many, competition in the marketplace is a threat. For Digital Hive, seeing the recent increase in competition indicates that there IS a marketplace for our Analytic Hub solution and that we are providing much-needed value.

We welcome new competitors as we work towards a common goal –  increase awareness of the value in Analytics Hubs, Analytics Catalogs, and data literacy support.

Why Digital Hive is the Best Analytics Hub Solution 

That being said, Digital Hive was the first Analytics Hub solution to identify and solve the market need of bringing enterprise BI together. The first-mover advantage has allowed us to evolve and innovate more quickly than our competitors and provide increased value to our clients as their needs change.

Digital Hive is uniquely differentiated as the only true technology-agnostic analytics hub that allows users to interact with the full-functionality of different reports and dashboards seamlessly within the experience.

Most of the competition in our space only provides a functional analytics catalog (or is yet another BI tool in disguise). Digital Hive is the only true Analytics Hub. In addition to an Analytics Catalog Digital Hive enables end-users to create interactive Data Storyboards using reports from different tools, and contextualize information with presentations, video, RSS feeds, and custom messaging. 

This means that clients can unlock the full power of Data Storytelling and Data Literacy support. Every department, persona, partner, or client receives relevant and tailored information supported by context.

Only Digital Hive can do that.

Learn how

How You Can Use Digital Hive Today

Digital Hive has clients in every vertical, all around the world – Financial Services, Healthcare, Higher Education, Manufacturing, Retail, and more. With out-of-the-box connectors to 18 major information systems and a Custom API connector, any business can bring their choice of BI & Analytics tools together and benefit with Digital Hive.

Want to learn more? Book a 30 min demo today!

Poor Change Management is Killing Analytics Value

Poor Change Management is Killing Analytics Value

Unless it pertains to politics or parking meters, people dislike change. Why? Change involves work, learning new skills, and the possibility of failure. This makes people uncomfortable and resistant. Maintaining the status quo is simply easier. When we look at why BI & Analytics initiatives fail, the reasons are not usually technical problems, but people problems related to change management and communication. Yet, in contrast to the average stakeholder, individuals who lead change are enthusiastic advocates and willing to put in the extra effort.

Why is this?

Champions of change understand the “Why, What, and How” of the change that is taking place.

Most stakeholders do not understand the “Why, What, and How” This is where D&A strategies are failing. If you map these 3 critical pieces of information to hot trends in Data & Analytics it is very clear. Industry challenges include:

  • Understanding the potential value of data – Rise of CDO (Data Culture)
  • Developing the skills to use data – less than 24%  (Data Literacy)
  • Using BI to make decisions – less than 35% (BI Adoption)
  • Producing a positive business outcome – less than 20% (Value)

Why, What, and How…

The “Why” must be the basis for change, and if it does not bring significant value to stakeholders, the initiative is doomed from the start.

All three of these factors are important, but the first is the most critical. To determine value, there must be strong communication between the analytics team implementing technology and the stakeholders who will use it. This is when we need to determine:

  • What are the business goals or outcomes?
  • What decisions will be made to reach these outcomes?
  • What information is needed to make decisions and act?

This channel of communication between “Analytics” and “The Business” has been historically very weak. One reason that “change management” and “communication” are the most poorly executed components of an Enterprise Data Strategy, is because Data & Analytics initiatives are championed by technologists. While data scientists might be some of the smartest in the room, technology is their passion, not people. So, technology is what they focus on and the people side of analytics gets neglected. This has led to the rise ofAnalytics Translators and other intermediaries.

The titles for this role are wide-ranging and have little consistency, but the need for an individual to lead the change management aspect of D&A initiatives is apparent. Call this person an “Analytics Translator”, a “Data Champion”, a consultant…whatever gets the job done effectively.

The Solution

This is the hard part. Every company has unique needs, strengths, and weaknesses. There are a number of things to consider when improving the change management aspect of your Enterprise Data Strategy or Digital Transformation effort in addition to a focus on the above:

  1. Do you have a clear leader and advocate for D&A on the executive team? Hiring a CDO is now a must.
  2. How does your analytics team work together and communicate with the rest of the business? Does your company have a dedicated analytics team or a (CoE) Center of Excellence? Should your company have a centralized or decentralized analytics team?
  3. Do you have dedicated individuals responsible for developing Data Culture, Data Literacy, and driving adoption? This is a full-time job. Hire for it.
  4. Is there a focus on business outcomes first and technology second?

We believe establishing an Enterprise Analytics Hub helps solve many of the challenges related to Data & Analytics change management. By centralizing all BI content in a single location and user-experience, you establish a foundation from which to build a data culture, communicate with end-users and receive feedback on business needs. You can also launch embedded data literacy campaigns and increase BI adoption by providing a single point of entry, and insulate end-users from the disruption that comes with the introduction of new tools and sunsetting of legacy systems.