Digital Hive, which provides an Intelligent Analytics Portal, announced today that it has appointed Lynn Moore as CEO, with immediate effect. Moore, who is a co-founder and chairman of Digital Hive’s board, has helped define the vision, strategy, and technical direction of the Digital Hive platform (formerly known as Theia) since its inception in 2015. More information on Digital Hive is available here.
Moore’s software engineering background coupled with 25 years experience cultivating relationships with enterprise buyers and strategic partners like IBM made him an ideal fit for the CEO role. Moore’s top priority for 2022 will be to seize the huge market opportunity in this year of change to fuel enterprise sales and close strategic partnerships.
According to Moore
“After a few turbulent years economically, most large enterprises are going through some business and IT consolidation, either through mergers/acquisitions or digital transformation. Rather than having to invest years of resources into integrating systems at the backend, Digital Hive lets enterprises pull them all together at the frontend through a common interface that IT can manage and users can personalize.”
Moore replaces Kevin Hurd, who will continue to serve as Digital Hive’s Chief Product Officer and Managing Director of Digital Hive’s partner Assimil8. This change means that Hurd will have greater resources to lead the product team to deliver new functionality for enterprise customers including full support for Cloud, AI-driven personalization, UX improvements, integrations with popular communications tools, and data storytelling.
Moore lives and works from Plano, Texas. He holds a Master of Science Degree in Computer Systems Engineering from the University of Arkansas. Outside of work, Moore is passionate about marine ecology and can be found doing cleanup dives with his son in Curaçao, in the Dutch Caribbean.
About Digital Hive
Digital Hive is an international software company that provides an intelligent analytics portal to information from multiple analytics and BI tools, content management systems, and file systems – on premise and in the cloud. By providing a single, shared organizational view, federated search across tools, and custom branding, Digital Hive helps drive systems adoption, improve data literacy, and deliver data stories for better decision making and business performance. A 2020 Gartner ‘Cool Vendor,’ Digital Hive customers like Clarity, DFS, Highmark, Froneri, Pomona College, and University of Denver.
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. 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: story boarding, data visualizations and data narrative.
The art of communicating using data and analytics, 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 Enterprise Portal 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.
Organizations today are faced with more decision-making challenges than ever before. This is due to the sheer volume of data, disparate sources, and breadth of information that they must process to operate effectively—not to mention their competitors’ efforts to outmaneuver them at every turn.
Traditional business intelligence (BI) helps organizations make better decisions. However, all these tools can’t solve all the challenges companies face. Technology, process, and people are three key pillars of transformation. Technology will and is constantly changing and innovating and optimizing platforms and processes is the key to leveraging and delivering insights in the fastest and most effective way. Could an enterprise portal be the ticket you’ve been waiting for all this time?
Businesses need to become more intelligent, which means they need to make their organization more agile. They need to be able to adapt quickly and correctly, but in order do that they need a modern platform for insight delivery from multiple tools. To deliver such a platform organization should invest in an Intelligent Enterprise Portal (IEP).
“Highly successful agile transformations typically delivered around 30 percent gains in efficiency, customer satisfaction, employee engagement, and operational performance; made the organization five to ten times faster; and turbocharged innovation.” McKinsey & Company
This all sounds nice… but is it a necessity for all businesses? In this article we’ll highlight how enterprise portals can help businesses cut costs dramatically but drive value at the same time. We’ll also cover what an enterprise portal is, how it works, and why it shouldn’t be perceived as a ‘nice to have’.
What is an Enterprise Portal?
An enterprise portal is a central information hub that provides users with real-time access to critical organizational data and information. It acts as a web-based platform that combines all your existing business’s analytics and intelligence sources (on-premises and cloud), giving users a consistent interface across multiple technologies and a direct route to what they need. Over and above having a centralized analytics experience, the right intelligent enterprise portal can provide your users with that extra layer of value they need by learning from user behavior patterns, history, and peer activity (Learn more here)
Death by multiple systems?
Regardless of a user’s role in the business, most if not all the daily activities carried out involve manual processes because the people involved don’t have a direct route to the information they need, which leads to duplication of effort and the subsequent delays that come with it.
For example, let’s say there is a problem with an order. For a team – whether customer-facing or internal – to solve it, they need access to information across 25 different systems and applications. That’s 25 different platforms with 25 different logins, 25 different looking portals, 25 different ways to navigate around a platform, 25 different ways to extract information, 25 portals that don’t know or understand the user… the list goes on. Based on this example, a user is wasting 37.5 mins simply logging in and accessing what they need – they haven’t even started on the ‘solving‘ part.
Accessing, navigating, and managing multiple systems affects your bottom line. It’s as simple as that. We’re talking about hours and days lost, reducing the productivity of your employees, and impacting their engagement and morale. In essence, businesses are paying people to ‘waste time’.
In most businesses where a lack of efficiency is called into question, it is usually down to people spending too much time on their mobile devices, standing chatting at the coffee machine, or blaming a meeting that overruns. But in today’s technology driven world, could scenarios like the one above (managing 25 different platforms) be:
Costing you in dollars, time, and productivity?
The reason for low productivity and engagement?
Contributing towards low adoption of BI across the business?
Preventing the creation of a data-driven culture?
Stopping you from becoming a smarter organization?
So, in a year’s time, how much money might you be losing?
Keep it simple and centralized with an Enterprise Portal
The pressure to stay competitive is growing and businesses that digitally transform are better places because they are able to use analytics and information to make quick and informed decisions. Focus needs to be on the user, their experience, and what information they have at their disposal. Are in-efficient processes and disconnected technologies hindering the business’s success?
By replacing the multiple portal experience with a centralized view of critical information and analytics across existing systems and technologies – all within one unified interface – allows users to see what’s happening now and what’s coming up next.
This will not only save users time and eliminate in-efficiencies, but it can also help users make better, faster decisions across your organization.
To find out how Digital Hive can help you drive change and centralize, contacts us today!
Gartner currently covers over 250 analytics vendors in their research. By the time you are done reading this article, I wouldn’t be surprised if there were two new vendors or tools. With the recent explosion of business intelligence and analytics tools on the market, you might find yourself drowning in a (data lake) of information and possibilities. What visualization tools should we use? Am I ready to pursue predictive analytics? Who should be using these tools? Whether your company is at the beginning of its analytics journey or operating at the bleeding edge of technology and strategy, one common theme will always be important – culture and mindset. A lack of organizational buy-in can hinder even the most well designed, thoroughly vetted analytics strategy. When it comes to data culture here are 6 essential topics to consider:
1. Data Culture is Decision Culture
Data culture may be experimental – but the objective is always to make better business decisions. Collecting data for data’s sake is useless. A great place to begin leveraging analytics is where people are already making decisions. Communicate with the leaders of specific business units and determine what critical information they use to make daily decisions. To go a step further, consolidate this information in a curated analytics experience for each department, group, or role. Once these groups begin leveraging the unique analytics relevant to their most common decisions, they will become curious what other insights they can discover. To continually improve the value of analytics, it is important to implement an effective feedback loop between business end-users and report developers. Report-rating and commentary mechanisms are critical capabilities necessary for feedback and communication between users and developers to improve the quality, scope, and impact of informational assets.
2. Data Culture and the C-Suite
There isn’t an executive you will meet today who would admit that data is not a priority in their decision-making process, but many don’t actually have a comprehensive understanding of how analytics can benefit the larger organization. Often times it is difficult for executives to define valuable problems for the analytics team to solve. Find ways for your analytics team to engage with and educate the C-Suite so that leadership understands the value behind the entire organization using analytics. A great way to demonstrate this value is by delivering a complete view of the business to your executives via a personalized business intelligence command center. Consolidate the most important KPI’s, reports, and visualizations from various tools and systems in a single pane of glass for quick, effective, executive decision making.
3. The Democratization of Data
The first step when trying to generate organizational excitement about using data for decision making is to simply get analytics in front of different groups within your organization. The informational assets available now, your reports and visualizations, might not be perfect yet – but the sooner you make them available, the sooner you can improve them. By presenting analytics to your end-users regardless of your analytics maturity, you expose them to the power of data-driven decision making, and before you know it, they will be asking for more. This is crucial in securing the organizational buy-in required for the additional investments in business intelligence that you need. One of the most effective ways to increase analytics adoption is to remove the barriers to access, and put analytics in front of your end-users through an easy to use, single point of entry for all the analytics assets you provide.
Check back after the holidays for 3 additional areas of focus when building a strong Data Culture within your organization.
If your efforts to create a rich data culture are going to be successful – identifying, recruiting, and partnering with enthusiastic data champions within the organization is an absolute must. C-Suite mission statements and company-wide initiatives that are as disruptive as digital transformation require catalysts at each level of the business to bridge long-term vision with front-line execution and adoption. This means educating and empowering middle management and the leaders of specific business units to lead the charge. The best culture catalysts will be business leaders and their ability to sell the value of analytics to their respective teams. Knowledge workers on the front-line live and breathe their daily work. Business leaders can articulate the impact data and analytics will have on daily decision making in the language of their unit and drive adoption – a process which is essential to securing top-down dedication to change. When looking at the current state of data literacy and analytics adoption within the organization you might feel that some groups are not yet advanced enough for increased access to business intelligence. You may be correct that data literacy levels are not at ideal levels, however, you can’t learn to read if you don’t have a book! Creating curated analytics experiences with varying amounts of business intelligence for different groups and roles is a great way to slowly increase access to data and drive data literacy over time. Data literacy will be crucial in every role within the next few years, so there is no better time to start than now.
5. Uniting Talent and Culture
The competition for data talent is fierce and growing, and as a result new roles and titles are emerging within the business. In the Higher Education space during 2018, CDO was more likely to mean Chief Diversity Officer than it was Chief Data Officer. However, things are changing, and they are changing fast across all industry verticals – take for example the evolution of the Data Scientist function. How does this effect culture? Given the growing need for data talent across all industries, it is now less important to hire from within your industry as you traditionally might for management, marketing, and sales roles. When it comes to emerging data talent, it is more important to find great talent that fits within the company culture of change and innovation – regardless of industry. Additionally, a diverse range of perspectives on how to extract value from data and analytics will add value to business outcomes and will help push the momentum of change within the organization.
6. Data Culture, Risk, and Ethics
The last topic we will discuss is the necessity to address risk and ethics in your data culture. Data management is increasingly important, including the ability to understand who, how, and what data people are using to make decisions. Misuse of data can institutionalize unfair biases like racism and sexism. Audit capabilities are increasingly important and valuable in understanding what data and reports are being used to make decisions.
Data culture is essential to driving the initial and continued success of BI and Analytics initiatives. No matter what stage of analytics maturity your organization is at, remember that it is important to identify daily decisions that can be influenced first, continue to educate the c-suite on the value of business intelligence, provide easy access to BI for everyone, recruit the leaders of business units to drive front-line adoption, hire great talent and include diverse perspectives, and maintain and unbiased and ethical approach to data use.
For more information on driving data decision making, read this article on BI-Modal Analytics