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The Business Intelligence

Software Guide 2013

ThinkBusinessy

8th August 2013

Ian Tomlin

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Introduction

There are many makes and types of business intelligence software product

available to buyers these days. Which type of product is right for your business?

In this guide I provide a perspective on the capabilities you might be unknowingly

looking for – just to make sure everything is ‘in the box’.

Topics I cover include:

What is Business Intelligence?

The Players

Capabilities

Constructs

Technology Disciplines

Future Trends

Check-list

Final Thoughts

Within this guide I haven’t spent too much time profiling each of the products as

this isn’t particularly helpful given that specifications and features change all of

the time so it is always a good idea to conduct your own web research. I do

however provide a summary of the more popular products at the end of the

article.

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What is Business Intelligence?

While there are many definitions the role of business intelligence software is to

source insights from data. There are two main forms of data:

Structured data – The sort of stuff you see in a database or a CSV (Comma

Separated Value) file that you’d expect to open in a desktop spreadsheet

application. These days we also have formats like XML that are essentially

structured composite files that carry data and a description of the data (so

the data file might say, “I’m an invoice” and “This first column is the Invoice

Number” which helps with data transfer between computer applications).

Unstructured data – Data that’s held in documents and other formats that

hasn’t already been placed into nicely labelled boxes but we still might

want to mine it.

The technology tooling required to surface useful data, organize it and present it

is complex and embraces a variety of capabilities, constructs and technology

disciplines. Few Business Intelligence tools cover all of the areas - but that’s okay

because you don’t always need every attribute.

The Players

With so many vendors in the business intelligence market it would be a pretty

meaningless and unfruitful exercise as the boundaries of capabilities for each

vendor are constantly in a state of flux. Even segmenting business intelligence

tools into ‘pre-cloud’ or ‘Made of the cloud’ does not provide great signage to

buyers given that many of the old school vendors have acquired or developed

in-memory and web 2.0 self service style capabilities.

Some of the more notable names in BI with exceptional technology or big brands

include SAS, IBM, MicroStrategy, SAP BusinessObjects, Oracle Hyperion,

Informationbuilders, Microsoft, Tibco, Qliktech, Tableau, Actuate, Encanvas,

Targit, Pentaho, Yellowfin, Birst, iDashboards, Jedox, Borad International and

Jaspersoft.

In addition to these software providers there are literally hundreds if not thousands

of business intelligence consulting and IT services companies around the world

that offer expert skills in selection, deployment and outsourcing of BI services

where a ‘blended’ strategy is adopted. The best advice therefore is to define the

requirements before attempting to select the tool-ware and service provisioning.

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Capabilities

Capabilities are big categories of ‘things’ that business intelligence DOES – not be

confused by HOW it gets done. Business Intelligence has four main areas:

Enterprise Performance Management

A business intelligence platform for managing organizational performance

including governance of progress towards strategic objectives as defined in a

scorecard and the monitoring of daily activities that result in budgets and

forecasts being achieved. Business Intelligence software used for this purpose will

often adopt the very popular Balanced Scorecard model to frame and articulate

strategy as exampled in the Strategy Map illustration above.

Daily Operating Controls and Operational Reporting

Applications used to disseminate reports that show progress towards budget and

forecast targets so that managers can react to sub-optimal performance and

before it’s too late to do anything about it.

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Operational Analytics

Applications used to source actionable insights that cause managers to review

their processes and decisions in search of improvements.

Community/Social Business Intelligence

Applications used to source insights within a community to aid community

learning and cooperation; often resulting in the creation of new or enhanced

applications and processes adopted by the community.

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Constructs

I use the term construct to describe core characteristics of HOW business

intelligence software does what it does. These are:

1. Capture – In many analytical applications there is more data to be added.

Tools to author forms are important to enable keyboard data entry from PC, tablet

and mobile phone devices.

2. Discover and harvest – The ability to harvest data from multiple sources is

essential for most data analysis applications. Advanced platforms provide

opportunities for discovery of new insights held within data. For example, natural

language search tools can present data on companies that are similar to those

in the enquiry to suggest content that may be interesting to the enquirer.

3. Assimilate – Assimilation is an essential yet least understood aspect of business

intelligence and operational analytics software. Assimilation is about get data

brought into a useful form for analysis. The extent to which assimilation is required

will depend on where the data is held, what form it is in, and how it needs to be

used. This stage might include tools that normalize data, sort it, cleanse it and

mash-it into a form that’s useful.

4. Analyze and interpret – Making sense of data has always been a feature of

business intelligence tools since the humble spreadsheet came of age. Analytics

is a challenging aspect for vendors because users have such varied requirements

and expectations. Interpretation is ‘in the eye of the beholder’ which is why self-

service tools have become such a competitive battleground.

5. Present– The presentation of data could be anything from a simple table to

sophisticated charts, maps and data visualizations. Data becomes generally

more interesting when people can look at two, three or four characteristics of the

subject on the same page (examining customer data that includes spending

habits, social networking behavior, location and affluence can expose new

understanding of customer personas that would be difficult to find if each

attribute were explored separately). Presentation needs to cater for analysis of

single or multiple attributes of one entity, or single or multiple attributes of multiple

entities and should include:

Tables with the ability to sort, group, order and compare

Simple (easily absorbed) entity analysis views like gauges, traffic lights, slider

scales and ‘direction of trend’ arrows that bring at-a-glance understanding

Enlightening charting and graphing tools including bar charts, pie charts,

line graphs, geo-spatial maps, spatial graphs, spider diagrams etc.

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Scorecards – that enable formation and comparison of key performance

indicators in a dashboard to accommodate for period by period analysis,

mixed compositions of KPIs including run-rate, first-past-the-post etc.

These days it’s hard to imagine any of the above presentation modes without the

ability to drill-down into source data and download data for further analysis. Drill-

down features are so important to aid comprehension and to enable the enquirer

to gain a deep understanding of ‘the data behind charts and graphs’, and how

summary values have been aggregated.

6. Manage enquiries and socialize – It can become time consuming for users to

keep re-building the reports and report-views of data that are most useful. Expect

BI platforms to therefore provide the means for users to personalize their own suite

of queries. Establishing profile-based customized report selections means that

users don’t have to keep re-creating the same enquiries time and again. In the

noughties, users expect to be able to socialize their reports and charts; normally

by publishing them to a dedicated webpage so they can share the precise report

view they’re looking at with colleagues.

7. Predict – Business Intelligence software becomes REALLY INTERESTING to buyers

when it can not only expose insights but predict consequences on growth

opportunities, resources, operating constraints and exposure to risk or

unbudgeted costs. It takes a heady mix of clever software AND a deep

appreciation of how processes work to create the magic formula needed to

source predictive analytics.

8. Install new or adapted processes – There’s little point learning if you can’t do

anything about it. Increasingly, Business Intelligence platforms are providing the

tooling to enable business analysts to apply learning lessons. Modern BI platforms

install changes to operating processes by providing the methods and tools to

design and deploy new applications or adapting existing ones. Tools like

Encanvas and Interneer enable cross-platform, cross-discipline workflows to be

installed that run across existing administrative systems and silos of data.

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Technology Disciplines

I use the term ‘technology discipline’ to describe the big chunks of technology

found in Business Intelligence applications. The market for tools is so diverse these

days that it’s difficult for buyers to compare like-for-like capabilities. Many vendors

have particular strengths, or specialize in a specific discipline which means

creating a solution can be a choice between:

Purchasing a ‘total platform solution’ from a software vendor where

everything is expected to be sourced by one vendor including the expertise

to deliver outcomes.

Purchasing a ‘pick and mix’ of best of breed software vendor tools and

building your own solution.

Inviting a third party IT Services company to take on the project overhead

of managing business intelligence sourcing across your enterprise based on

an agreed set of outcomes.

Here I describe the most prevalent technology disciplines under the headings of

the constructs I’ve outlined in the previous section. Note that I’ve not produced

a fully comprehensive list as it might stretch into pages! Neither have I

documented ‘IT hygiene’ factors such as User permissions management, security,

scaling, portal deployment, cross-browser compatibility and mobile integration

(etc.) that are ‘must-have’ business computing requirements.

(Capture)

Key-fill forms applications - To enable keyboard-fill data entry of data that

adds-to existing business insights applications. Applications normally need

to support one-to-many and many-to-many data relationships and support

cross-browser deployment to PC, tablet and mobile devices.

(Discover and harvest)

Natural language search engines – To spider the Internet and recover

content held in unstructured content (documents and websites articles)

based on natural language terms.

Recommendation engines – To source recommendations of contextualized

insights (view services like Factiva and you will see that search enquiries on

a topic such as the name of a company will result in other similar companies

being ‘recommended’ to the enquirer. You will also see similar side-bar

discoverable insights from searches on popular mapping tools like

Googlemaps).

Data source connectors – To connect to data sources and file formats.

These generally take the form of a wizard that makes it easy to connect to

a data source and configure an extraction of data or two-way dynamic

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integration. Vendors like Microsoft, Tibco, Encanvas, Xchanging, Pentaho,

and Mulesoft all offer suites of data connectors and integration tools so you

can source virtually any data from any source.

(Assimilate)

Information upload and flow management tools – To automate triggering

and extract workflows for the purposes of loading data from its various

sources into the business intelligence environment (see products like

Information Flow Designer from Encanvas).

Extract, Transform and Load tools – To source data and make it usable in

business intelligence applications; normally by executing transforms.

Data mashup tools- To bring data together in news ways by picking ‘bits’ of

data from different places and creating new data structures with it (for

example, taking data from a spreadsheet and combining it with data from

Oracle and SAP in the same table-view).

(Analyze and interpret)

Tables with Sorting, Ordering, Filtering and Grouping – To offer users the

ability to interrogate data using interactive table views.

Comparison Views – To offer users the ability to compare entities side-by-

side in table views.

Metering and Charting with Drill-down – To offer users the ability to view

data in the form of meters and charts used to report on aggregated data

views with the ability to drill-down to the original data; probably in an

interactive tabular view.

(Present/Self-service tooling)

KPI Scorecarding – To enable users to create scorecards by specifying a

series of key performance indicators each with its own formative logic –

such as first-past-the-post, run-rate, period comparison etc.

Graphing and Charting – To enable users to create charts and graphs from

the assimilated data without complexity or programming.

Mapping and Visualizing – To enable users to geo-map or visualize data

using spatial graphing tools.

(Manage enquiries and socialize)

Web page/dedicated-URL sharing – To enable users to share their insights

by using dedicated-URLs that can be pasted into messages etc.

Interactive slider and choice controls – To enable users to interact with data

in real-time to understand likely impacts of decisions.

Voting and crowdsourcing – To enable communities to contribute opinions

on the analytics being shared.

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(Predict)

Prediction engines - To predict pinch-points in areas of resourcing capacity,

process loadings, consequences of decisions etc.

(Install new or adapted processes)

Applications design tools – To create applications that facilitate the

iteration of business processes that are demanded when users seek to

apply the learning lessons surfaced by actionable insights.

Business Process Management (BPM) workflow automation – To install cross-

cutting workflows that run across silos of business operation in support of the

change agenda demanded when users seek to apply the learning lessons

surfaced by actionable insights.

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Future Trends

The future trends emerging in Business Intelligence include:

1. More ‘born of the cloud’ BI products

It would be hard to imagine a business intelligence vendor surviving if they

aren’t able to provide a cloud delivered service. Companies like Encanvas

and Tableau have mature and sophisticated cloud offerings that make it

painless to configure a private-cloud environment within which company data

can be assimilated without risk of security breaches. In the architectural purity

debate, platforms that are able to deliver their insights through a browser

agnostic front-end will inevitably be favored against those that require plug-

ins or downloads. It still amazes me how incredibly poor companies like IBM

and Microsoft are at supporting the diverse range of browsers out there. It

seems these bigger players are confident enough in their brand positions to

say to customers ‘You can have IE and Safari if you’re lucky’ which a decade

ago was possibly good enough. If it was then, it isn’t anymore.

The products that will eventually grow to become the leaders in this industry

will have been ‘born’ in the cloud and of cloud technologies. Many of the

current products are built on code authored in the 1990’s and that’s a big

problem. Technologies like in-memory processing and use of AJAX tools CAN

be bolted on to legacy platforms but eventually the complexity and cost of

supporting aging technology platforms becomes a competitive Achilles’ heel.

2. Greater focus on sourcing of actionable insights than technology tools

Whilst dashboards and charts are the ‘bread and butter’ of business

intelligence solutions, what business people expect now are ACTIONABLE

insights that cause them to take action. The company that is leading the

charge to prove how effective and influential operational analytics can be to

bolster business success isn’t actually a business intelligence company at all.

It’s Google. Take a look at Google Analytics and you see a demonstration of

the art of operational analytics done well. Now imagine having Google

Analytics across every aspect of your business landscape. Wow.

Buyers are worried far less about tools than they ever used to be. They are far

more interested in outcomes. It’s the actionable insights, not the operational

analytical tools that deliver them, that’s taking center stage.

3. Increased embedding of BI tooling into business apps

Google Analytics also demonstrates the power of incorporating business

intelligence technologies into the operational platforms that business people

use. No longer is business intelligence software something separate, it is

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embedded into the applications people produce. In this sense the clever tools

of business intelligence software becomes smaller parts of a bigger system.

One could argue that platforms like IBM WebSphere and Microsoft SharePoint

have been doing this for some time. Take a look at Oracle’s fusion apps and

you will see the very best of operational analytics technology ‘ready-for-use’

and built within the core applications companies can now purchase on a

cloud. Business intelligence offerings like Tibco Spotfire and Encanvas

BusinessIntel take on the shape of applications design tool-kits that bolt into

existing applications and become as one with them. Meanwhile database

platforms like SAP Hana are symptomatic of the trend to merge operational

and business intelligence data management structures into one. This reduces

the complexity of IT architectures and increases the possibility of creating a

‘single-version-of-the-truth’.

4. More focus on predictive technologies

What tends to happen when people use business intelligence (when it works

well) is they start to see in dashboards and activities patterns of ‘things that

happen’ they can act on. Over time it becomes apparent that the task of

seeking out these insights is itself time consuming and it would be better if the

SYSTEM could itself predict these occurrences and recommend actions. The

ability to ‘predict’ resource constraints, understand events that could create

opportunity and risk – and other stuff – becomes smarter and more effective

over time. The rewards can be enormous.

5. Platforms that cover ALL of the bases

As I outlined earlier, modern business intelligence software has to cover ALL of

the capability areas including capture, discovery and harvesting, assimilation,

analytics and interpretation, presentation, socialization and enquiry,

prediction and solutions delivery. At present only a minority of vendors are

able to service all of these bases and often they achieve this only through use

of third party apps. Progressively as the market matures and it becomes more

of a brand war than a feature by feature battle, we can expect that all of the

major vendors will have to find ways to offer COMPLETE solutions; either

through development or acquisition.

6. Cloud BI going main-stream

Business intelligence software has to-date been seen as the cherry on the

cake; something businesses purchased later when they realized the system of

record they’d purchased didn’t actually source the performance analytics

and actionable insights they required. In future, business applications that

DON’T offer rich analytics and self-service tooling to source actionable insights

simply won’t be purchased. The Software-as-a-Service (SaaS) model enables

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buyers to choose their products in full view of their strengths and weaknesses.

Vendors are no longer able to hide behind the PowerPoint sales pitch or well-

fashioned demo site. The ‘capabilities’ of business intelligence software will

eventually merge into the Social Operating Systems that people use in their

work-day and as users we will see these as features of the tools we use rather

than seeing them as something different.

7. (And finally…) Price erosion

Google said almost a decade ago that buyers could one day expect to get

‘all the software they needed’ for $10 a head. I still believe this is ultimately the

way the industry will go and it becomes all the more possible when vendors

like Amazon, Apple, Encanvas, Microsoft, IBM, Oracle, SAP, Salesforce.com

and others continue to mature their Social Operating Systems platforms in the

cloud and start to provide menu-based industry and process specific solutions

that buyers can buy with ‘good practice’ built-in.

Checklist for Buying Business Intelligence Software

Requirements vary so much for business intelligence that no single vendor

offerings will always be the best-fit. Here’s a simple check-list?

1. Qualify the role that you expect business intelligence to play in your business

and the BI capabilities you will need. Some businesses (and indeed business

models) don’t change that frequently in which case a more traditional

business intelligence platform will probably work, but if you expect users to

demand intuitive self-service tools and expect your dashboards and

operational analytics to grow and grow then one of the more ‘agile’

platforms would spring to mind. Depending on your industry there may be

vendors that have ‘ready-to-deploy’ solutions to match your immediate

role needs and bring faster ‘time-to-value’.

2. Consider where the data your business intelligence platform will need to

harvest is held and in what form – it could be coming from desktop apps,

existing administrative systems, documents, web services, third party

services etc. – and check to see if the BI tools you’re considering can

access them. Check for data connectors and assimilation capabilities.

3. Audit the ‘constructs’ you will require and make sure your BI tools have the

ability to service these requirements – either from one vendor, or from

several.

4. Review the ‘hygiene’ issues like federated user permissions management,

security, scalability, cross-browser support, multi-threading capabilities and

enquiry processing potential.

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Final Thoughts

While not all BI offerings are the same but innovation in the Business Intelligence

market does seem to be reaching its peak. While some players have fallen off of

the pace, the majority are able to offer ‘complete’ solutions one way or another;

even if it involves integration with third party tools or months of development!

Competitive differentiation is strongest in areas of:

Real-time analytics – making sense of data while it’s still moving!

Self-serviceability tooling – giving users the tools to serve themselves with

new analytics, new applications etc.

Discovery (exposing new insights from queries you haven’t even thought of)

Assimilation tooling such as data mashing and normalization

Time-to-value (often achieved by off-the-shelf process or industry specific

dashboards and reports)

Predictive analytics that reduces manual interventions

Faced with maturing technology, we appear to be entering a new period where

BRAND will play an ever increasing role in decision making. This is good news for

companies like SAP, IBM, Oracle and Microsoft – and potentially for Apple, Nokia,

Amazon and Samsung – that already have BIG brands, particularly as business

intelligence tooling becomes integral to business applications.

We have seen in the past 20+ years a move towards ‘platforms’ in business

computing where companies sacrifice any opportunity for competitive

advantage through the tools they use for ‘good practice processes and a single

view of data brought about by the ambition of a single computing system. This

norm of behavior in buying approaches adopted by large corporations has really

helped the larger brands to dominate.

Nevertheless, it’s not all bad news for new entrants and smaller players that may

be light on brand awareness but have the more adaptive ‘born of the cloud’

tools buyers need and the opportunity to grow their brand story thanks to the new

playing field that the cloud offers. When it comes to surfacing actionable insights

and harvesting the BIG DATA that’s becoming available to business users around

the world, there’s still plenty of room for innovation.

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About the Author

Ian Tomlin is a researcher, writer and author on topics of customer science,

organization design and agility, stretch strategy and enterprise technology. He

has worked in the European Information Technology sector since 1990 holding

sales and marketing management roles covering disciplines including business

intelligence, document management, computer printing, output management,

document, content and knowledge management, search, cloud computing,

enterprise social networking, enterprise integration, ETL and data mashups.

Article Sponsors

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Books by Ian Tomlin

Agilization – The regeneration of competitiveness (2008)

Cloud Coffee House – The birth of cloud social networking and death of the old

world corporation (2009)

SOS - Social Operation Systems (2011)

Blogs and Articles by Ian Tomlin

Loyalty Beyond Reason – iantomlin.blogspot.com @ictomo

ThinkBusinessy – thinkbusinessy.blogspot.com @ThinkBusinessy

Slideshare - www.slideshare.net/ictomlin