There is no doubt that across all industries – be it healthcare, retail, manufacturing, or finance – there are a few themes pushing today’s companies to take a closer look at business intelligence solutions: the rise in popularity of analytics (especially given the increasingly mainstream discussion and use of big data); the rise of data discovery and end-user empowerment; and lastly, the increase in the market’s use of cloud-based BI solutions.
Historically, organizations would compete on product alone: “My database is faster than your database.” If you have been around long enough to remember the Oracle vs. IBM days, you will agree. If this doesn’t ring a bell with you – just think of the age-old Coke vs. Pepsi debate and then think of them as software vendors and you’ll get the idea. Today is different though. It’s no longer just about the product, it’s about much more. Organizations now routinely compete on the customer experience and the business processes they use to market, sell and deliver their products.
Driving Your Business Forward
There’s been a big shift in the last five years and this change is gaining momentum and speed. Analytics are becoming more and more important to more and more businesses because, as many analyst studies have repeatedly found, organizations that invest in analytics have better financials, make decisions faster than their competition, and execute more effectively on those decisions.
Organizations are using analytics to drive their businesses forward. Thirty years ago, most global businesses competed on just products and features. Today, that has expanded to the user experience and now it is becoming clear that the customer experience is a massive determining factor during the competitive process. Organizations are competing not only on what they do (e.g. I’m the low-cost provider), but how they compare on the customer experience. This means that ultimately, they are competing on the business process.
We are going to see a few things result from this. First, the number one way you get better at doing something is by measuring how you are doing things. It’s easy to measure features but hard to measure process, particularly in a large organization. Organizations need to measure what works now, what doesn’t, where they are missing the mark, and where they are winning.
This is where analytics come in. If you are going to compete on process, you need analytics and you will also need to be able to use analytics as the language that helps your organization understand the success of your processes. Today’s generation has higher quantitative expectations than those that preceded it. Today’s workforce expects the numbers to be at their fingertips. The days of card catalogues, the Dewey Decimal System and having to read through books (gasp!) of information to find the answer to one question are long gone. In fact, if you are typing “Dewey Decimal” into Google right now, you have proved my point.
A couple of years ago, IBM conducted a survey among CEOs that brought a few interesting data points about BI to the surface. Most importantly, it underscored the importance of BI. The survey respondents revealed that BI allows you to access information on the front lines of your business, giving you the ability to draw insights that go beyond the spreadsheet of numbers normally used to make decisions, and that by using data to make informed decisions, you can do something about what it is that you are seeing within that data. If it is a negative and you want to rectify it, or if it is a positive that you want to replicate, the information is readily available.
Why is any of that possible? Because analytics drive results.
In that same study (IBM’s 2012 CEO Study), outperforming organizations based on revenue and profit growth compared to industry peers held a significant advantage in terms of their ability to turn data into insight and insight into action. This isn’t surprising because fact-based decision-making has consistently shown that it drives business results. Firms that are able to turn data into decisions are driving more revenue and profit than those that aren’t. This is exactly why businesses keep funding analytics – because it works. And if it works then organizations are better run with it and hopefully are able to use it to unlock the competitive advantages locked-up in their data.
This has become something of a hot topic in the BI market over the last few years. What do we mean by ‘empower the end user’ and more importantly, how do we do it?
The truth is that today, end users expect to have the data they need so that they can get the information they need to make better decisions to do their job. Fundamentally, everyone wants to be successful at their job. But in order to be successful, people need information and that information has to be timely and accurate and hopefully, informative. The days where management says they don’t work from the numbers is gone. Everyone knows that success lies in an organization’s ability to analyze their information and make decisions based on it.
This notion is exactly what is driving a pretty significant challenge in BI. End users need to be able to analyze their information. But naturally their information is different from others in the organization – they want to ask different questions, answer their own questions and draw their own conclusions. That leads to a big headache.
In general, businesses want people to be on the same page whether they are in the marketing, sales or engineering departments. How many times have you been in meetings where different people have come to the meeting with different numbers, and the group spends 20 minutes debating which is the right number instead of arguing about how to grow that number or achieve the previously set goal that was related to that number? If everybody has the same numbers, the conversation goes much quicker, and that has real value within not only that one meeting, but across the entire organization. It empowers that user to make decisions and to take action against the information.
Unfortunately, this consistency has had an historical downside because legacy BI has been built around consistency. It is big and slow to develop but you get consistent metadata and you get consistent information. They are also slow and hard to roll out, and it is hard to get it to every corner of the organization. Data Discovery tools are a hot newcomer to the conversations of today. There is a growing emergence of a lot of tools (Excel was the original pioneer) where there is loads of freedom. People aren’t going to wait for the waterfall approach, especially for a low priority project. But the tradeoff for the loads of freedom is a complete lack of consistency.
With the widespread use of Data Discovery, we got speed but gave up on the richness of what was possible with analytics. We got freedom but gave up on consistency. I believe that with cloud BI from Birst, you don’t need to compromise like this and can have depth of analysis combined with agile delivery of information. I’ll expand on this theme in my next blog.