Forrester Methodology To Select Business Intelligence Implementation Service Providers

Business Intelligence (BI) pros continue to look for outside professional services. Forty-nine percent of decision makers say their firms are already engaging and/or expanding their engagements with outside data and analytic service providers, and another 22% plan to do so in the next 12 months. There are two main reasons for this sustained trend:

  • The breadth and depth of BI deployments cannot be internally replicated at scale. Delivering widely adopted and effective BI solutions is not easy. It requires rigor in methodology, discipline in execution, the right resources, and the application of numerous best practices. No internal enterprise tech organization can claim this wealth of expertise and experience; this only comes after delivering thousands of successful and unsuccessful BI projects — which we believe is solely the realm of management consultants and systems integrators. These partners have collectively accumulated such experience over many years and thousands of clients and projects.
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Is Business Intelligence (BI) Market Finally Maturing? Forrester Three Big BI Market Predictions

No. The buy side market is nowhere near maturity and will continue to be a greenfield opportunity to many BI vendors. Our research still shows that homegrown shadow IT BI applications based on spreadsheets and desktop databases dominate the enterprises. And only somewhere between 20% and 50% of enterprise structured data is being curated and available to enterprise BI tools and applications.

The sell side of the market is a different story. Forrester’s three recent research reports are pointing to a highly mature, commoditized and crowded market. That crowded landscape has to change. Forrester is making three predictions which should guide BI vendor and BI buyer strategies in the next three to five years.

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Get ready for Business Intelligence market next wave of M&A

Business intelligence (BI) is a runaway locomotive that keeps picking up speed in terms of enterprise interest, adoption, and spending levels. The result: Forrester now tracks 73(!) vendors in the segment. Their architectures and user interfaces vary, but they support similar use cases. Forrester started the original research with fewer than 30 vendors in 2014 and ended up with 73 in the current 2017 update. Expect this dynamic to continue for the foreseeable future. Even though the BI market is quite mature from the point of view of the number of players and breadth and depth of their functionality, it is still quite immature regarding business and technology maturity, adoption, and penetration levels in user organizations. Vendors will continue to seize this opportunity — new players will keep springing up, and large vendors will continue to acquire them.No market, even a

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Divide (BI Governance From Data Governance) And Conquer

Stop! Before you invest even 10 minutes of your precious time reading this blog, please make sure it's really business intelligence (BI) governance, and not data governance best practices, that you are looking for. BI governance is a key component of data governance, but they're not the same. Data governance deals with the entire spectrum (creation, transformation, ownership, etc.) of people, processes, policies, and technologies that manage and govern an enterprise's use of its data assets (such as data governance stewardship applications, master data management, metadata management, and data quality).  On the other hand, BI governance only deals with who uses the data, when, and how.

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Business Intelligence Skills

So you have gone through the Discover and Plan of your Business Intelligence (BI) strategy and are ready to staff your BI support organization. What skills, experience, expertise and qualifications should you be looking for?

  • Since the term BI is often used to also include data management processes and technologies, let's assume that in your case you are only looking for expertise required to build reports and dashboards and it does not include
    • Data integration (ETL, etc) expertise
    • Data governance (master data management, data quality, etc) expertise
    • Data modelling (relational and multidimensional) expertise
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Is Data Visualization A Separate Market Or Just A Feature Of Business Intelligence Platforms?

Lots of my clients are confused. They start a Forrester inquiry with a question about data visualization capabilities, but when I lead them into discussion about business intelligence (BI) platforms, they say "but we already have a BI platform. All we really want is an ability to create and share data visualizations". Is there a separate market for that? If there is, I am not aware of one. Here's my take on it:

  • If what you are looking for includes requirements for data visualization administration, security, data management, version control, collaboration, etc, you really need a BI platform with data visualization capabilities.
    • The last time Forrester looked at Data Visualization as a separate capability was in 2012 and even then, as you will see from the URL, we ended up evaluated BI platforms.
    • In our last (and going forward) Wave on the topic we grouped data visualization and self service BI capabilities together as we see them inseparable.
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Enrich Customer Insights With Unstructured Data

Over the past several years, Forrester's research has written extensively about the age of the customer. Forrester believes that only the enterprises that are obsessed with winning, serving, and retaining customers will thrive in this highly competitive, customer-centric economy. But in order to get a full view of customer behavior, sentiment, emotion, and intentions, Information Management professionals must help enterprises leverage all the data at their disposal, not just structured, but also unstructured. Alas, that's still an elusive goal, as most enterprises leverage only 40% of structured data and 31% of unstructured data for business and customer insights and decision-making.

So what do you need to do to start enriching your customer insights with unstructured data ? First, get your yext analysis terminology straight. For Information Management pros, the process of text mining and text analytics should not be a black box, where unstructured text goes in and structured information comes out. But today, there is a lot of market confusion on the terminology and process of text analytics. The market, both vendors and users, often uses the terms text mining and text analytics interchangeably; Forrester makes a distinction and recommends that Information Management pros working on text mining/text analytics initiatives adopt the following terminology:

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What To Do When A CIO Pushes Back On Your Agile BI Platform?

 
CIO pushback is part of a typical growing pain of all business intelligence (BI) startups. It means your land and expand strategy is working. Once you start expanding beyond a single department CIOs will notice. As a general rule, the earlier the CIO is brought on board, the better. CIOs who feel left out are likely to raise more objections than those who are involved in the early stages. A number of BI vendors that started out with a strategy of purposely avoiding the CIO found over time that they had to change their strategies - ultimately, there’s no way round the CIO. Forrester has also noticed that the more a vendor gets the reputation of “going round” the CIO, the greater the resistance is from CIOs once they do get involved. 
 
There is of course also the situation where the business side doesn’t want the CIO involved, sometimes for very good reason. That notwithstanding, if there’s a dependency on the CIO when it comes to sign-off, Forrester would strongly recommend encouraging the business to bring him/her to the table. 
 
The two key aspects to bear in mind in this context are:
 
  • CIOs look for transparency. Have architecture diagrams to hand out, be prepared to explain your solution in as much technical detail as required, and have answers ready regarding the enterprise IT capabilities listed below.  
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It's 10 O'Clock! Do You Know If Your BI Supports Actual Verifiable Facts?

Delivering broad access to data and analytics to a diverse base of users is an intimidating task, yet it is an essential foundation to becoming an insights-driven organization. To win and keep customers in an increasingly competitive world, firms need to take advantage of the huge swaths of data available and put it into the hands of more users. To do this, business intelligence (BI) pros must evolve disjointed and convoluted data and analytics practices into well-orchestrated systems of insight that deliver actionable information. But implementing digital insights is just the first step with these systems — and few hit the bull's eye the first time. Continuously learning from previous insights and their results makes future efforts more efficient and effective. This is a key capability for the next-generation BI, what Forrester calls systems of insight.

"It's 10 o'clock! Do you know if your insights support actual verifiable facts?" This is a real challenge, as measuring report and dashboard effectiveness today involves mostly discipline and processes, not technology. For example, if a data mining analysis predicted a certain number of fraudulent transactions, do you have the discipline and processes to go back and verify whether the prediction came true? Or if a metrics dashboard was flashing red, telling you that inventory levels were too low for the current business environment, and the signal caused you to order more widgets, do you verify if this was a good or a bad decision? Did you make or lose money on the extra inventory you ordered? Organizations are still struggling with this ultimate measure of BI effectiveness. Only 8% of Forrester clients report robust capabilities for such continuous improvement, and 39% report just a few basic capabilities.

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Continuing Trend Of Data Exploration - Tableau Closes One Of The Remaining Gaps In Its Portfolio, Acquires HyPer

One of the reasons for only a portion of enterprise and external (about a third of structured and a quarter of unstructured -) data being available for insights is a restrictive architecture of SQL databases. In SQL databases data and metadata (data models, aka schemas) are tightly bound and inseparable (aka early binding, schema on write). Changing the model often requires at best just rebuilding an index or an aggregate, at worst - reloading entire columns and tables. Therefore many analysts start their work from data sets based on these tightly bound models, where DBAs and data architects have already built business requirements (that may be outdated or incomplete)  into the models. Thus the data delivered to the end-users already contains inherent biases, which are opaque to the user and can  strongly influence their analysis. As part of the natural evolution of Business Intelligence (BI) platforms data exploration now addresses this challenge. How? BI pros can now take advantage of ALL raw data available in their enterprises by:
 
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