Higher Education Is Hurting – Data Can Help (COVID 2020 )

Higher Education Is Hurting – Data Can Help (COVID 2020 )

Those of us preaching the power of data – on LinkedIn, on stage at keynotes, and at yearly budgeting meetings – prescribe data as the solution to all problems. However, we all know the execution of a powerful analytics strategy is often more challenging than anticipated.  These challenges are especially severe in higher education, even before operating in the midst of a global pandemic and looming economic recession. Now, the hurdles seem larger than ever. Budgets are being significantly reduced or frozen, analytics teams are being defunded and paralyzed in the face of uncertainty. Yet, the greatest action universities can take today, one thing they can control, is to double down on data. Those who choose to do will evolve and emerge stronger. Those who don’t, may not survive.

Adoption is essential

Higher education has always been slow to adopt new technology, which I think is understandable. Universities are large and complex. They have many layers of leadership and often rely on external funding. It’s this complexity that makes data such a valuable asset for university decision making, and in the past decade, major strides have been made to introduce data & analytics tools across departments. The results of these changes, however, have been slow to surface.

One of the reasons that data investments are seeing less than stellar returns, is a product of the university’s organization and structure. Many groups operate independently from one another – especially when it comes to technology purchasing decisions – and this has resulted in a variety of siloed tools and technologies. 

However, efforts have been made to create university-wide analytics councils and information management teams, but working backwards to resolve the existing incompatibility of different technologies is still difficult. 

Now as we start to see valuable information being generated by many different departments, having an awareness or sight of key information that could be a saving grace to universities in crisis-mode is critical.  However accessing, sharing, and acting on this information quickly is still next to impossible.

Everything in one place

Pomona College Branded as ‘ConnectTo’, Pomona’s advancement department used Digital Hive and created a single, unified information portal bringing together IBM Cognos, Microsoft Power BI, Tableau, and SSRS. Last year, Pomona College won a National Silver CASE Award with ‘ConnectTo’.  Now, users have one place to go to easily find reports, dashboards, documents, training materials and more.

This has resulted in greater efficiency and productivity across departments, an increase in adoption (more than quadrupled), a reduction in technology management costs, and has directly impacted decision making in regards to fundraising campaigns.

Future-Proofing

While actively investing in new technology projects during a period of uncertainty may seem risky, the greatest risk is in retreating to the status quo. In all areas of our society, both in business and our personal lives, we have experienced a steady increase in digital transformation. 

The COVID-19 pandemic is not creating a new normal, it has simply accelerated the inevitable evolution of how we behave and interact. For many businesses who made digital investments early on, this period will mark an opportunity to accelerate past the competition. For others, it’s a wake-up call that the train is leaving the station, and immediate action is required. Unfortunately for the rest, a lack of action when times are good and when times are bad, will result in devastating consequences.

Click here to read more about howDigital Hive ransformed Pomona College’s fundraising efforts or book a demo to see Digital Hive in action. 

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!

Do Customer Analytics Portals Matter?

Do Customer Analytics Portals Matter?

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. 

The Challenge

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.


Data Storytelling: An Intersection of Art & Science

Data Storytelling: An Intersection of Art & Science

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 one,

“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.

Data Storytelling

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:

components of data story telling

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.

Capturing Business Context

All BI and Analytics initiatives should aim to do the following: make money, save money, or protect against risk. However, only 20% of analytics insights are predicted to produce a business outcome through 2022 according to Gartner. To unlock greater value, analytics teams and business leaders must radically change the way they communicate.

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.

Theia gameboard showing assets from different BI tools sitting side by side, creating a full datastory
*Storyboard storyboard incorporating visualizations from 2 different BI tools, context from Google Drive, and custom messaging.

Conclusion

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.

Analytics from different BI systems side by side
*Image shows an example Digital Hive gameboard/storyboard with assets from multiple BI tools sitting side by side in a single view.

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.

Click here to download our e-book 7 Steps to Drive Data Literacy‘ or book a quick 30 min 1:1 demo with a Digital Hive expert!

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.

BI Consolidation is Almost Impossible

BI Consolidation is Almost Impossible

750 million people use it daily and many use it as their primary business intelligence tool. You might find this surprising if you consider Excel was invented in the 1980s, nearly 40 years ago, but, so were Business Objects (SAP), Microstrategy, Hyperion (Oracle), and Cognos (IBM). And guess what? Those tools are the foundation for most of the Fortune 1000’s data strategy.

Has your company recently implemented Tableau, Qlik, or Power BI? Well, even those tools are now between 10 and 30 years old! Not to mention, they probably co-exist in your company with one of the other BI tools I mentioned.

Let’s fast forward. Arguably, the hottest analytics company on the market right now is ThoughtSpot. With their “Search and AI-driven capabilities, they are at the cutting edge. If you have implemented ThoughtSpot, I am 99% certain it co-exists alongside AT LEAST one of the aforementioned BI tools.

 “What’s the point, Spencer?”

Well, let’s tally up the number of BI tools you have. You certainly use Excel, most likely have a legacy BI tool like SAP, Oracle, or IBM and there is a good chance you’ve introduced a 2nd generation data viz tool like Tableau or Power BI. If you are cutting edge, you might also have an augmented analytics tool like ThoughtSpot.

So you probably have 3 BI tools, if not more. Our thought exercise is supported by research from Gartner and Forrester, as well as an informal survey I conducted on LinkedIn, and I haven’t even touched on tools with analytics capabilities like Salesforce.

The point I am trying to make is that it’s very hard to keep up with innovation, resulting in the co-existence of many multi-generational analytics tools. Enterprise companies are simply too big and move too slow to keep pace while simultaneously consolidating technology to a single platform.

“Who cares? What’s the problem?”

Having multiple BI tools makes it hard to use analytics and make decisions. All of your end-users are concerned with analytics tools, instead of DECISION MAKING. This creates silos of BI assets, making it difficult to find information, hard to drive BI adoption, impossible to establish data governance, consistency, or ease of use. This is a huge obstacle to establishing a strong data culture or effectively executing a change management strategy. To put it plainly, it makes things difficult. People don’t like difficult. People like easy. People like fast.

“What is the solution?”

I’m glad you asked! ? The solution is Digital Hive. Digital Hive is “Your Intelligent Enterprise Portal” that surfaces and recommends analytics in a personalized experience.