TIBCO Jaspersoft eBook

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Software makers no
longer compete on whose
application performs its
core functions better.

With the consumerization of data, the best
solutions – the ones that stick – are the ones
that empower users to realize the full value
of their data.

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Introduction

We’re all software
companies now

It’s been said that every
company is, regardless of
industry or sector, competing
on a software playing field*.

Cars are becoming computers on wheels, banks
are digital service providers rather than physical
places, and in retail stores are increasingly
made out of bits, not bricks and mortar.

Because whatever a company makes or sells,
whatever service it provides, it can be improved
by software – and it probably has already.

This has had an enormous impact on user
expectations.

* ‘You Don’t Have to Be a Software Company to Think Like One’, Harvard Business Review, 20 April 2016 - Vijay Gurbaxani

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The volume of data generated by
businesses has exploded and as a
result business intelligence has
been liberated from the boardroom.

Research that points to traditional
BI penetrating only 20% of business
users misses the point* – data-driven
decisions are increasingly being made at
every level, through the feedback users
receive from all kinds of applications.

* ‘Business Intelligence for the Other 80 Percent’, Information Management, 03 April 2015 – Ted Cuzzillo

Analytics is now a major
competitive factor for
software and applications.

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The consumerization
of data, in 4 trends.

#1 BI meets UX

A typical business user uses 20+ desktop
and web applications every day. They
don’t have time, and don't want, to
learn new ones. To convince them to
adopt a new application, its value must
be immediately clear. An intuitive UI
with user friendly dashboards and
controls (aka self-service analytics)
is an expectation not a nice-to-have.

#2 Demanding users

Enterprise apps have become more
consumerized and the cloud has removed
vendor lock-in, making users choosier
about everything – including analytics.

#3 Monetizing data

Research has shown that software
companies whose applications
support custom analytics can
charge a higher price-per-user
– a lot higher. (More on this in
a minute.)

#4 Immersive analytics

Software makers left separate analytics
applications behind in the ‘90s, in favor
of reporting tabs in the ‘00s – but the
‘10s are the era of ‘immersive’ analytics.

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Product managers whose
roadmap doesn’t take
these trends into account
are taking a risk.

Customers will become increasingly unhappy with
the limitations of their solution, and sales will
be knocking on the door, pleading: “look at
what our competition are doing!”.

Finding a solution to this problem is urgent,
but finding the development resources to build
and maintain it is a real challenge.

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Part 1

Own the problem,
reap the rewards

reap the rewards

UX is out of sync with
modern standards.

In the past BI was a separate function
that application makers didn’t worry
about.

It was on the end user to find a
suitable package for gaining insights
from the applications they were using.

As a quick fix they offered ‘data dumps’,
i.e. generated large spreadsheets, and
left the user to create static reports
based on those.

From websites to smart phones to enterprise
applications, the effects of a bad UX are hard to
overstate. 88% of online consumers are less likely
to return to a site after a bad experience with a
slow website.*

* ‘Site speed: case studies, tips and tools for improving your conversion rate’, Econsultancy – David Moth

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Today, the best applications
natively embed analytics,
putting answers next
to the data that informed it.

This offers the best UX, but brings with it product
design and resourcing challenges including the added
complexity of maintaining additional code.

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Argument for embedded analytics #1

Stickiness

The lack of ROI is the number one
killer of applications today.

Analytics enables users to solve
real problems with insights from

their data, continually reminding them of
the application’s value.

The popularity of short-term subscriptions
for cloud-based applications means
customers are making a buy decision every
billing period.

This puts pressure on product and
development teams to get new features to
market quickly. It also means that
applications need to be useful, and
easy to use, in order to become sticky.

* ‘Software 2006 Industry Report, SandHill
** ‘Worldwide Public Cloud Services Spending Forecast to Double by 2019’, IDC, 21 January 2016

2005*

2015**

2019*

SaaS market

$bn

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Argument for embedded analytics #2

Charge more for your applications

In 2016, 96% of the 2016 Montclare
SaaS 250 included reporting and
analytics in their products, and
the more flexible their offering the
higher they could charge per user.

Average cost per user of SaaS tools

Analytics add value to applications

$

Don’t charge for analytics
Charge for reporting
Charge for custom analytics

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Argument for embedded analytics #3

Add value for customers

Waggle had a big idea ................... but resources were stretched ......... so they chose embedded BI.

Use big data to help
teachers identify which
students needed more
support, and the exact
type of support required.

They needed to hook up to
cloud-based data in real time
and a UX that let teachers
and school administrators
drill into data from grade
level down to individual
students.

At last count, over 800,000
user hours had been clocked,
and the number of pieces of
data stored and analyzed is
fast approaching one billion.

Developers at Waggle fused
the solution with analytics
and their customers saw
immediate value.

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Part 2

Complexity vs.
Competitiveness

%

The potential benefits of offering
in-application analytics are
enormous, but the challenges
can be pretty big too.

While analytics features make
applications more competitive, they
also make the product and
development teams' jobs a whole lot
more complex.

With developer resources perpetually
scarce, this can be a challenge.

At the time of writing there are currently
506,808 open computing jobs across the
US, but only 42,969 computer science
students graduated into the workforce
last year – just 8% of total demand.*

* Code.org/promote – November 2016

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“Product managers have
a lot of great ideas for
new features, but like I tell
them, ‘in my job I have
three dials to balance...

one for adding new features
the market demands, another for
improving the existing features
and a third for fixing stuff that’s
already broken. There are no more
dials and I can’t turn one to 100
and the others down to zero’.”

As one head of engineering explained to us:

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%

Once analytics has been added,
it must be maintained and
continuously improved.

Every piece of code written, if you
want it to keep working, needs to
be supported forever or
re-architected when programming
languages are updated or new
technologies released.

Additional complexity
arises because once
analytics have been
added, it must be
maintained and
innovated on top of
in subsequent releases.

Estimates show that about
90% of software life cost
is related to its maintenance
phase.*

* ‘Which Factors Affect Software Projects Maintenance Cost More?’, ResearchGate – Sayed Mehdi Hejazi Dehaghani and Naﬁseh Hajrahim

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So, should you buy and embed a BI/analytics
solution, or try to build your own?

The truth is there is no right answer.

Why build?*

Control
You get exactly what you want.

Niche functionality
Maybe your specialist requirements
aren’t supported by available
embedded BI tools.

No need to wait
If you have limited requirements
then it may be quicker to build.

Less administration
Building avoids licensing and royalty
negotiations.

Why buy?*

Focus on your strengths
ISVs are not BI specialists and don’t
want to divert precious resources
to building BI.

Simplicity
It can be much simpler to buy BI, while
achieving more functionality. For
example – it’s difficult to build
self-service analytics from scratch.

Best-of-breed
Working with a BI specialist instantly
adds best-of-breed features, and they
will continue to enhance their product.

Time to market
Embedding a BI solution accelerates
time to market.

* ‘Embedded BI: Putting Reporting and Analysis Everywhere’, Eckerson Group, December 2014 – Wayne Eckerson

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Part 3

Buying embedded analytics:

why, what and who

TechTarget asked 55 software
providers to select the reasons
they bought rather than built
their embedded BI.

* ‘Embedded BI: Putting Reporting and Analysis Everywhere’, Eckerson Group, December 2014 – Wayne Eckerson

Buying enables us to provide best-in-class BI functionality to customers

We would rather focus our developers on our core product

Building takes too long

Buying gives us a competitive advantage

Building is too expensive

Other

Why do you buy instead of build BI functionality? (%)*

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If you decide to go down this route,
what are the key considerations
and talking points for your team
that will help you to better
understand what you’re looking for?

Total cost of ownership

Some BI vendors charge per user,
but is it practical to negotiate with
your vendor every time you make
a sale or a customer wants to add/
remove users? Probably not. Either
way, the cost of analytics should
only be a reasonable or even modest
proportion of your subscription.

Multi-tenancy support

In today’s SaaS dominated market,
multi-tenancy support is essential to
securely, efficiently and flexibly deliver
BI to customers. The best embedded
BI solutions will enable you to ship
common reports to all customers,
while catering for specific customer
requirements on an individual basis
as necessary. This should be a deal
breaker for any embedded BI solution
not offering this functionality.

Architecture

Software is just code if not deployed
correctly so embedded BI tools
must integrate with a plethora of
architectures, source control systems
like Git, continuous integration
systems, containerization solutions
like Docker and modern APIs like
REST and Javascript.

Single Sign On (SSO) and UX

Users expect to log into a single
portal to use your entire product.
If your analytics looks like it’s
been nailed onto the side of your
application it’ll be more Franken-
App than masterpiece, and UX and
stickiness will suffer.

Data sources

A ‘data agnostic’ solution will let
you work with the broadest possible
range of data sources, whether
traditional databases or NoSQL,
MongoDB, Hadoop or Redshift.

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But there are also
some common pitfalls
to beware of.

There are many applications for mining and
analyzing data and some are temptingly easy
to get started with.

But if they’re not primarily created for the
unique demands of ISVs and SaaS companies
and don’t truly blend in with your application,
then they will eventually topple over when it
comes to demanding functions such as SSO,
self-service analytics, multi tenancy and security.

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Final word

Like everything worth doing,
it isn’t easy to create an analytics
UX that your customers love to use.
But with embedded BI it can be
made a little easier.

As the world’s most widely used
Business Intelligence tool, TIBCO
Jaspersoft empowers millions of
people every day to make faster
decisions by bringing them timely,
actionable data inside their apps
and business processes through
an embeddable reporting and
analytics platform.

Head to Jaspersoft.com to find
out more, or try it for free here.

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