InetSoft Participates in DM Radio Broadcast on the Consumerization of Business Intelligence

This is the transcript of DM Radio’s program titled “The Consumerization of Business Intelligence: How and Why,”

And with that, let's kind of dive in.  So the topic of Consumerization of Business Intelligence, well gosh, 12 years ago, when yours truly first moved to Austin, Texas, to work for a business intelligence consulting firm, actually a data warehousing consulting firm, we were talking back then.  It was called BI for the masses, right.  We kept talking about how can we get these great insights, these data-driven insights to front-line workers, to more than just the C-suite, more than just the power analysts who get paid a lot of money to dive through all kinds of data and come up with great ideas, how do we get past that.  And I remember the reports came out and it was anywhere from 5% to 10% of the enterprise was actually using business intelligence tools, leveraging those insights, which is a pretty small number.  And for years and years, we have talked about this, and we can talk all day about exactly what happened and why things have changed and what's going on.  

Obviously there are a lot of factors, and one that I’m sure we will talk about today is that form factor revolution called the iPad, the iPad and of course the iPhone, but more the iPad than anything else.  Because all of a sudden, you have got this decent sized device, it's got beautiful graphics, you can carry it around, it's very light weight, it's cheap, you can do all kinds of fun things with it, and that kind of changed things in organizations because all of a sudden you had senior executives who wanted their iPad at work, and when the boss of a big company wants something, usually the boss gets something.  And so that happened, and that’s why we got into this whole BYOD thing, Bring Your Own Device, that’s why we talk about this stuff today.

And lots of other things happened too, of course.  The Internet has really taken off in terms of providing functionality for people to do various things like e-mail marketing, supply chain management, sales force automation.  All of these Cloud-based services have driven people more online to get things done.  And I am talking about reporting too.  The web of course is a wonderful mechanism for reporting and ad hoc queries and so forth.  Web is everywhere so if you get online, you have access to data if you have authority to get to it and so forth.

 So there are lots of these things that are happening to create the consumerization of BI.  But what are they and sort of why is this happening and what can you do about it?  Well that’s what we will talk about today.  So, let's bring in our expert guest host, none other than the inevitable Justin Kern, Senior Editor of Information Management Magazine.  Welcome back to DM Radio.

Justin Kern:  Eric, thanks as always.  12 years ago, what is that in BI years?  Is that like 36 years?

Eric Kavanagh:  84 I think.

Justin Kern:  84 years.  But I am glad that you kind of gave it that historical context, because it has gone by different names, different promises, over the last decade.  And when we are on, in the media, we tend to be kind of on the leading edge of some of the trends, and this consumerization one has been historically one of the less abstract of the BI or data trends, an actual promise that business could use, could see, could have in its pocket additional access to data and business results.  But in the last couple of years, as you said, it's actually come to the forefront.  And I think that as you said, Apple can get some credit for that, but I think it's just the existence of that general in-your-face mobility.  But you have these things, they are there, and now IT just has to deal with it I suppose.  

But Bruce was at CES, the big Consumer Electronics thing, and I think it's in Vegas.  He was there in January and he wrote a blog for our site, where he kind of said that this was the year where enterprise IT and all the vendors were kind of catching their breath over this consumerization trend.  So it wasn’t so much the bloviating or the promises and that type of thing, it was the idea that we actually have these smartphones, we have these tablets now, we have these visualization tools, and now we just have to figure out how to deal with them.  And I think that’s kind of the interesting promise and challenge ahead for consumerization, especially in very near term here, is figuring out how to make it work best and who is actually owning and dealing with it all.

What Does the Consumerization of Business Intelligence Mean?

The consumerization of business intelligence (BI) refers to the trend of making BI tools and technologies more accessible, intuitive, and user-friendly for non-technical business users. This shift parallels the broader consumerization of IT, where technologies traditionally confined to experts become mainstream and usable by the general public. Here's a deeper dive into what this means and its implications:

1. Accessibility and Usability

• User-Friendly Interfaces: Modern BI tools are designed with intuitive interfaces that require minimal training. Dashboards, drag-and-drop functionalities, and visual data exploration capabilities allow users to interact with data without needing deep technical skills.
• Self-Service BI: This is a key component, enabling business users to generate their own reports, perform ad-hoc analyses, and visualize data without relying on IT departments. Tools like Tableau, Power BI, and Qlik have led the way in this democratization of data.

2. Empowerment of Business Users

• Data-Driven Decision Making: With easier access to BI tools, business users across departments (marketing, sales, HR, finance) can make more informed decisions based on real-time data. This shift leads to more agile and responsive business operations.
• Reduced Dependence on IT: By lowering the technical barriers, the consumerization of BI reduces the bottleneck traditionally caused by IT departments. Business units can move faster, generating insights and making decisions without waiting for IT support.

3. Integration with Everyday Tools

• Embedded BI: Business intelligence capabilities are increasingly embedded into the everyday tools that users are already familiar with, such as CRM systems, ERP software, and even spreadsheets. This integration makes data insights a natural part of the workflow.
• Mobile BI: The rise of mobile applications allows users to access BI tools on their smartphones and tablets, ensuring that they can analyze data and make decisions on the go.

4. Cloud-Based Solutions

• Scalability and Flexibility: Cloud-based BI solutions offer scalability, enabling organizations to adjust resources based on demand. They also provide flexibility, as users can access data and analytics from anywhere with an internet connection.
• Cost-Effectiveness: Cloud solutions typically operate on a subscription model, reducing the upfront costs associated with on-premises BI infrastructure. This financial accessibility further drives the consumerization trend.

5. Collaboration and Sharing

• Collaborative Features: Modern BI tools often include features that facilitate collaboration, such as shared dashboards, comment sections, and real-time updates. This fosters a collaborative culture around data, where insights are easily shared across teams.
• Social BI: Some platforms incorporate social media-like features, allowing users to follow data streams, like and comment on insights, and receive notifications on relevant data updates.

6. Data Visualization and Storytelling

• Enhanced Data Visualization: Effective data visualization tools help users to quickly understand and interpret complex data sets. These visualizations can be more engaging and easier to digest than traditional reports.
• Data Storytelling: This involves combining data visualizations with narrative elements to tell a story that is compelling and easy to understand. Data storytelling is a powerful way to communicate insights and drive action.

7. AI and Machine Learning Integration

• Advanced Analytics: The integration of AI and machine learning into BI tools allows for more sophisticated analyses, such as predictive analytics and anomaly detection, without requiring advanced technical knowledge from the user.
• Natural Language Processing (NLP): NLP features enable users to interact with BI tools using natural language queries, making it even easier for non-technical users to extract insights from data.

Implications of Consumerization of BI

• Cultural Shift: Organizations need to foster a data-driven culture where all employees are encouraged and trained to use BI tools. This cultural shift is essential for maximizing the benefits of BI consumerization.
• Data Governance: As more users gain access to data, organizations must ensure robust data governance practices to maintain data quality, security, and compliance.
• Competitive Advantage: Companies that successfully adopt consumerized BI can gain a competitive edge by making faster, more informed decisions and being more responsive to market changes.

Next: The How and Why of the Consumerization of BI