Length of stay and readmission might be accessed via your QlikSense application, Patient Satisfaction information stored in Tableau, and Employee demographics & Dependent coverage ratios are in a third system…meaning you’re forced to remember all of this as well as login information for each of the individual systems. So what happens when another, newer, augmented analytics system like ThoughtSpot is introduced?
You might lose track of where the information is stored… might try to ‘cut and paste’ pieces of the information you need into a PowerPoint so you can create an overview ‘dashboard’. Maybe you’ll dump all of the data into Excel and make a pivot table?
While you think this might ‘work at the time’, what’s worth pointing out is that all of the above is time consuming, inefficient and increases the risk of misinterpretation – not to mention the issues this creates around data privacy.
Enter the Analytics Portal
There is a better way than cobbling your data and visualizations together with cut & paste! Digital Hive provides an efficient and code-free way to bring together silos containing the length of stay and readmissions information, patient satisfaction information, employee & their dependant’s demographics, into a unique, personalized ‘portal’. One login, one solution. Simple.
When was the last time change didn’t happen? Rarely, that’s when. The tools and applications organizations leverage to understand & present information is fluid. You need to be able to adapt to these changes as well.
Digital Hive not only allows for these changes to take place but encourages them. With the ability to integrate new analytics tools at any point, you are in complete control of how to use new capability sets in concert with your current applications – giving you the ability to leverage the right tools for the right job.
Now Tableau exists with PowerBI and ThoughtSpot for a more holistic view of your healthcare world.
A word on personalization
Adapt and adopt, make the experience unique to your community. Let’s be honest. Just bringing all of your required information, visualizations and applications together into a single experience is paramount, but what if people don’t like the look and feel of the experience. Limited adoption is the outcome.
Digital Hive provides a unique drag and drop, code-free, personalization experience so you can tailor your analytics hub to suit the needs of and requirements of individuals, roles and groups in your organization. Now you’re on your way to increased adoption and are driving towards the realization of data-driven decision making.
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 Hive…YES!
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.
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.
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.
Digital Hive has been named a 2020 Gartner Cool Vendor in Analytics and Data Science
With the average organization using 3.8 different BI solutions, and the number of different business roles wanting to analyze the data increasing, it’s critical that businesses make it easy for users to leverage, share and scale the analytics value from different systems that have been generated before.
According to Gartner’s report, published May 7th, 2020:
“Organizations are struggling to manage analytics content from different tools. This hinders the ability to share and scale the use of analytics, and limits adoption as users fail to find and compile the insights that have been generated before.”
Garter recommend that one way this can be achieved is by
“establishing an easily accessible portal that has single access to the analytics content built by multiple existing analytics solutions.”
Gartner’s definition of a Cool Vendor is “a small company offering a technology or service that is: innovative — enables users to do things they couldn’t do before, impactful — has or will have a business impact — not just technology for its own sake, intriguing — has caught Gartner’s interest during the past six months.”
Why is Digital Hive Cool?
Digital Hive’s technology consolidates key information assets across an entire organization in one convenient and digestible place, giving users real-time access to the relevant information they contain through a single point of entry.
Digital Hive (formally known as Theia) connects to analytics and BI tools platforms such as ThoughtSpot, Tableau, Qlik, IBM Cognos as well as standard document systems such as Google Drive, SharePoint, Box and social media platforms.
Click hereto read Gartner’s full report – link off to Gartner.
Gartner Disclaimer: The GARTNER COOL VENDOR badge is a trademark and service mark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
As companies race to find value in their data and improve the customer experience, many have overlooked an obvious value-add: providing analytics for the customer. Client-facing analytics differentiates companies from the competition, helping increase market share, retention, and even direct revenue if packaged and productized.
Why aren’t all companies doing this already? The data is there, and the reporting, dashboards, and visualizations are plenty.
One of the most difficult aspects of trying to provide analytics to customers is delivering a complete, appealing product. With analytics coming from a variety of internal business intelligence tools, packaging all of this information is far from easy. Both internal and external, users desire a seamless analytics experience. If bringing all of this content together into a single user experience wasn’t challenging enough, each experience needs to be tailored for various audiences.
On top of wrangling content, curating different experiences, and creating a pretty product – facilitating understanding is also a challenge. Chief Data Officers are tasked with fostering data culture, increasing BI adoption, and improving data literacy. However, these initiatives shouldn’t be limited to the internal organization. Companies need to extend this concentration to clients and partners as well.
The Ideal Customer Analytics Portal
Given the needs and challenges discussed above, let’s describe the ideal external analytics portal for clients and partners:
In summary, companies should aim to deliver analytics both internally and externally to clients and partners to maximize the value of data and grow together with strong data-informed relationships using an analytics portal.
The ideal analytics portal integrates reports and visualizations from all of your different BI tools, allows for the curation of content for different groups including data literacy support, and provides an attractive and easy to use experience.
Why Act Now?
If you provide your clients with informative analytics to help them grow their businesses, your business will become an irreplaceable source of value. If you DON’T provide your clients and partners with analytics, someone else will.
The demand for analytics is continually increasing as companies use data to drive decision making. If you are not providing clients with informative analytics to help them grow their business, how are you ensuring that your service will not become an irreplaceable source of value?
Offer your clients a service that goes above and beyond the competition. Replace any frustrations by giving them full autonomy over their analytics environment.
How to create a Customer Portal with Digital Hive
Read more about our enterprise portal solutions, or get in touch, if you want to chat about customer analytics portals – we can show you how simple it is to get set up!
Book a demo with a member of the team. See the full Digital Hive experience as well as some of the branded customer portals we’ve created.
A few years ago I met Walter Isaacson, former Chairman of CNN, Editor of TIME, and author of Steve Jobs’ biography. If you
can’t tell from his pedigree, Isaacson is a great storyteller. He also wrote
about other famous innovators including Benjamin Franklin, Albert Einstein and
Leonardo Da Vinci. I only had time to ask him one question, so I made it a good
“What did Jobs, Franklin, Einstein, and Da Vinci have in
common that made them such great visionaries?”
Isaacson smiled and responded, “All great innovators operate at the intersection of Art and Science.” I think Isaacson would agree this balance applies to data storytelling as well. Truly effective storytelling drives business action, and this occurs with the right mix of facts, visual presentation, and contextual narrative. Finding this balance is a challenge, but with the right tools and methodology, you can go from creating flashy dashboards to actually informing decisions.
Over the past decade, there has been a massive push for companies to leverage data. We are starting to see the Rise of Chief Data Officers. Humans are visual by nature, so we have also seen increased adoption of user-friendly visualization tools like Tableau, Qlik, Power BI, and ThoughtSpot. As the push for data democratization and access to data continues to increase, we need to ensure data is being effectively communicated and consumed – not just put into a pretty dashboard. Enter Stage Left: Data Storytelling.
What is Data Storytelling? Data Storytelling is translating data in an easy to understand the way to help people take action on the business. There are three main components to data storytelling:
The final component, the art of communication, is still on the starting block. However, by establishing a methodology and using new technologies to support us, we can realize the full value of our data, inspire action, and transform Data Storytelling from an industry buzzword into an effective boardroom practice.
Rather than just deliver report requests, analytics teams must establish a dialogue with the business to understand the context. Context includes goals, challenges, and potential decisions that the business will make. In creating this dialogue, gaps in understanding will appear. These gaps will highlight the best questions to ask of the data. Ultimately, the answers to these questions will deliver the value business leaders have been seeking.
Using Technology for Storytelling
Once the context has been established and the right questions are being asked, analytics teams, can use technology to help communicate information with a narrative to increase understanding. We use reports and data visualization tools now. Data visualization helps us see blatant patterns, but it isn’t ideal for communicating context and situational nuances. We also shouldn’t assume interpreting a visualization is easy for everyone. With the global Data Literacy rate struggling around 24%, delivering an isolated report or visualization is risky – the information can easily be misinterpreted and lead to costly decisions.
New technology, like Digital Hive’s Analytics Hub, enables companies to easily balance the art and science of data storytelling so they can communicate and understand the entire business narrative – and ultimately make the best decisions.
By bringing together reports, visualizations, and dashboards from all of your different BI tools into a single storyboard, you can mix best-of-breed technology to deliver all of the facts. Contextually, you can incorporate video, custom messaging, presentations, and data literacy support assets to complete the narrative and inspire action.
The ideal balance of data, visualization, and narrative can now be achieved without the limitations of any one tool or technology because you can use all of your tools together seamlessly.
To increase the value of analytics for the business, we must find a greater balance between the art and science of data storytelling. When looking to improve the art, we must change the way analytics teams and the business communicate context. Then, we need to ask impactful questions of our data.
Finally, when delivering our findings, we should leverage technology to support us by using data visualization and data storytelling tools to communicate insight within a narrative.
Digital Hive and Data Storytelling
Digital Hive dynamically displays content from any information system seamlessly in one unified platform – providing the easiest, most efficient, and customizable experience for the delivery and consumption of data stories on the market today. Behind the scenes, Digital Hive defends users from change-disruption, tracks analytics adoption, and reduces the IT backlog.
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)
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
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 of “Analytics 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.
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:
Do you have a clear leader and advocate for D&A on the executive team? Hiring a CDO is now a must.
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?
Do you have dedicated individuals responsible for developing Data Culture, Data Literacy, and driving adoption? This is a full-time job. Hire for it.
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.