{"id":10753,"date":"2017-01-31T10:30:58","date_gmt":"2017-01-31T16:30:58","guid":{"rendered":"http:\/\/www.mrc-productivity.com\/blog\/?p=10753"},"modified":"2022-11-22T16:08:32","modified_gmt":"2022-11-22T22:08:32","slug":"6-big-business-intelligence-trends-of-2017","status":"publish","type":"post","link":"https:\/\/www.mrc-productivity.com\/blog\/2017\/01\/6-big-business-intelligence-trends-of-2017\/","title":{"rendered":"6 big Business Intelligence trends of 2017"},"content":{"rendered":"

\"Education\"Summary: Poised for rapid growth, Business Intelligence is undergoing some major changes. Driven in part by recent trends and development advances, the BI landscape is shifting dramatically from traditional BI solutions of the past. In this article, you\u2019ll learn more about why BI is changing and where it\u2019s heading.<\/em><\/span>
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\u201cKnowledge has become the key economic resource and the dominant, if not the only, source of competitive advantage.\u201d<\/em> – Peter F. Drucker<\/p>\n

I like the wording in that quote. You\u2019ll notice that he doesn\u2019t say, \u201cData has become the key economic resource.\u201d He says \u201cKnowledge.\u201d<\/p>\n

It\u2019s important that we separate those two concepts. Every business has data. Most have too much data. A lack of data isn\u2019t the problem.<\/p>\n

Knowledge is the hard part. It\u2019s taking that data and turning it into something meaningful. It\u2019s converting an avalanche of data into action-oriented insights. That\u2019s the hard part. <\/p>\n

How do you turn data into knowledge? That\u2019s where business intelligence (BI) comes into play. BI is the process of turning unusable data into actionable insights. When done correctly, BI will improve visibility, provide insights into customer behavior, improve efficiency, and so much more. <\/p>\n

How can you get the most out of your BI investment? I won\u2019t get into the details here, as it\u2019s a topic covered in a previous article<\/span><\/a>. But, I would like to add one point: To truly get the most out of BI, it\u2019s important that you stay ahead of the curve. The world of BI is constantly changing. New tools emerge. New trends take hold. If you can stay ahead of the curve, you\u2019re better positioned to turn your data into knowledge–and a competitive advantage.<\/p>\n

So, where is BI headed this year? What trends should you monitor? Today, let\u2019s focus on those questions. Here are 6 BI trends to watch this year.<\/p>\n

1. The rise of fast data<\/h3>\n
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Over the past few years, big data has stolen the show. Businesses have focused on getting a handle on the flow of data. How can you capture, store, and analyze this data most effectively?<\/p>\n

Now that\u2019s changing. As organizations get more comfortable with the idea of big data, the focus shifts to speed. The question IT departments must answer in the near future: How quickly can you turn this data into something useful?<\/p>\n

This trend is summed up nicely in this article<\/span><\/a>: \u201cGiven this ever-increasing amount of available data — and the fact that most of it is live in the moment — the benefits of big data will be lost if the information isn\u2019t processed quickly enough. Here\u2019s where the concept of \u201cfast data\u201d steps up to the plate.\u201d<\/em><\/p>\n

Of course, this trend goes beyond \u201cbig data.\u201d The need for fast data is greater than ever. How quickly can you turn your data into meaningful management information? Do your end users have access to self-service tools so they can analyze data on their own? In the coming years, the need for speed will be one of the biggest trends in the BI world.<\/p>\n

2. The move towards BI consolidation<\/h3>\n

Research<\/span><\/a> finds that the average business uses multiple BI tools. The average IT team interacts with nearly four tools, while the average business user interacts with about three. <\/p>\n

Why so many? Maybe they use different tools for different functions. Or, maybe different departments licensed different tools. And, of course, there\u2019s always some employees doing all reporting on spreadsheets.<\/p>\n

The problem is, this approach delivers multiple versions of truth and hurts collaboration. You\u2019re stuck with data in different locations. You\u2019re stuck wondering which report is accurate. You\u2019re stuck manually moving data across different platforms. This process is not only slow, it leads to data inaccuracies.<\/p>\n

As mentioned in the first point, modern BI must be fast. It must deliver insights immediately. Using multiple BI tools slows the process down–a problem that you can\u2019t afford these days. <\/p>\n

In the coming year, we\u2019ll see a shift towards a single version of truth. As businesses try to bring all of their data into one place, we\u2019ll see them consolidate multiple BI tools into multi-purpose BI platforms.<\/p>\n

\n\u201cWe are a software selection platform and over the past year we’ve seen a lot of companies wanting to consolidate their BI tools – having invested originally in some of the best in class and now wanting to use a single source software for BI – one that obviously connects to all data sources,\u201d Michael Shearer, Director, Marketing Operations, SelectHub<\/span><\/a>.\n<\/p><\/blockquote>\n

3. The push for quality over quantity<\/h3>\n
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Taking the last point one step further, BI tools aren\u2019t the only thing that\u2019s getting pared down. In 2017, we\u2019ll see a major shift in how businesses view their data.<\/p>\n

Let me explain. <\/p>\n

As data volumes grow, many companies have falsely equated data quantity to value. The more data, the better…right? Not exactly.<\/p>\n

What they\u2019re finding, is this data only overwhelms them. In his book, \u201cThe Paradox of Choice<\/span><\/a>,\u201d Barry Schwartz explains how more options actually hurt decision-making. We\u2019re stuck trying to compare every available option, which ultimately becomes counter-productive. <\/p>\n

Businesses are finding this exact problem when trying to sort through all of their available data. As they take in more data, their choices become harder. It actually hinders decision-making. <\/p>\n

In the coming year, we\u2019ll see businesses focus on data quality over data quantity. This means removing unimportant data points from reports\/dashboards. This means narrowing down the data that really matters. Rather than deliver massive amounts of data, businesses will instead focus on delivering actionable data. <\/p>\n

\n\u201c2017 will be the year where all the data that makes it to the screen (report, dashboard etc) will finally get pared down,\u201d says Ted Clark, Founder and Data Automation Builder at Adventag<\/span>. \u201cThere’s too much information to consume now, and the focus will turn to making and presenting only metrics that are actionable and aid decision making.\u201d\n<\/p><\/blockquote>\n

4. The transition from traditional to self-service BI<\/h3>\n

As mentioned above, knowledge is a massive competitive advantage. More and more, your ability to quickly turn data into meaningful management information will directly impact your bottom line.<\/p>\n

The problem: The traditional Business Intelligence (BI) process struggles in this area. Businesses are finding that they can\u2019t deliver the data users need, when they need it\u2013a problem that\u2019s creating a shift in the BI world. <\/p>\n

What is this shift? Business Intelligence is increasingly becoming an end-user task, rather than an IT-driven task. As tools improve and the need for speed increases, self-service BI is quickly supplanting traditional efforts.<\/p>\n

How big is this shift? Last year, Gartner<\/span><\/a> made waves in the BI industry when they revamped their BI magic quadrant criteria. The move towards business-user-centric platforms forced a new market perspective, and reordered the entire landscape.<\/p>\n

Now, this isn\u2019t a brand new trend–it\u2019s been in the works for a few years. But, we can expect this trend to pick up steam in the coming year. Self-service BI will become the norm, while traditional BI methods fade away.<\/p>\n

5. The growth of Artificial Intelligence within BI<\/h3>\n
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Over the past few years, we\u2019ve seen a few important trends emerge:<\/p>\n

First, we have big data. Data is growing in volume, and at an unprecedented pace. But, without a way to turn this data into insight, it offers little value. <\/p>\n

Second, we have a lack of data experts. As data has grown, data analytic skills have not kept up. In fact, research finds there\u2019s a global shortage of data scientists. <\/p>\n

Third, we have a growing need for fast data. Businesses need insights quickly, and can\u2019t afford to wait around.<\/p>\n

Why am I sharing these trends? Combined, these trends are the driving force behind a huge BI trend: Artificial Intelligence (AI). AI has the ability to turn mountains of data into insights, and is poised to play a major role in the BI world.<\/p>\n

\n“Artificial Intelligence will become an essential element of Business Intelligence,\u201d says Jack Porter, CEO of Razorthink<\/span><\/a>. \u201cAI as Data Scientists will emerge as a way to propel sales, reduce churn and dramatically improve customer service through behavior-based micro-segmentation, rather than traditional demographic segmentation.”\n<\/p><\/blockquote>\n

Now, I realize that “Artificial Intelligence” is a complex topic, with many different uses across many different areas. How will it impact BI from a practical standpoint? Here are a few important ways:<\/p>\n