Highlights trends in Business Intelligence. though written in early 2010, it is still accurate. I would add Mobile BI and Collaborative Decision Management as complementary trends.

1. Top 10 trends in
Business Intelligence
The view of Business & Decision
on the evolutions in Business Intelligence

2. Top 10 trends in Business Intelligence
Today’s business environment is identified by an extreme
competitive nature which is driving companies to optimize the
processes that have a direct impact on their financial and operational
performance. As a result, many companies are seeking to apply
performance-driven management techniques to streamline their day-
to-day business operations and facilitate better decisions across the
organization.
With these evolutions on the demand side, solutions need to grow
too in order to meet these requirements and even be ahead of
things.
As leader in Business Intelligence consulting, Business & Decision
wants to share its view with you on the Top 10 Evolutions and the
new challenges this brings in taking Business Intelligence to the next
level…
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3. Top 10 trends in Business Intelligence
1) Self-service Business Intelligence for easier consumption of information
As businesses are urging for deeper insights to support their key decisions, they
want to reduce the distance between them and information, and therefore fight
against the dependence on “middle men”. BI should establish itself as the shared
“utility” service to provide the shortest path to information: canned reporting was
the first answer, then came ad-hoc reporting to help users define their own views
on data and customize the presentation layers. OLAP allowed deeper analysis and
navigation into data, while allowing more sophisticated ad hoc analysis (e.g. time
series, complex calculations).
Still, knowledge workers feel frustrated when they depend on the presence of Data
Marts that aren’t always ready to go and can be too long or too costly to create.
Some of the data needed may also be missing. As a result, some of them create
their own spread marts, as shadow IT initiatives with high risks in terms of security,
compliance and data accuracy.
Customer case: A world-class player in the development of human vaccines is
implementing the ad-hoc data marts concept as a component of their BI
deployment strategy. Self Service BI is an option for demands that are beyond
continuous improvement of the current environment, but not prioritized as strategic
new IT projects. Implementing them as ad hoc data marts for departmental
deployments is therefore an option.
2) Managed BI
On the other side, as BI expanded in organizations, it now represents a significant
part of the IT budget. TCO and quality has therefore become a topic of interest.
This leads to:
- Consolidation of BI platforms
- Creation of BI Competency Centers (BICC): shared services within an
organization to design, prioritize, govern and continuously improve BI
initiatives. New organizations with information stewards that act within the
business lines as facilitators to make information available when needed.
Those stewards source the information from the data warehouse, under IT
control.
- Creation of BI Service Centers: shared insourced or outsourced “factory” to
implement, maintain and support BI initiatives.
Customer Case: A large French financial institution created the so-called
“decisional” initiative to manage their BI projects and other information centric
initiatives (e.g. risk management and compliance to the Basel 2 legislation. An
internal BICC pilots the overall program from a business perspective and establishes
the organization, processes and infrastructure. An outsourced “close shore” BI
Service Center delivers and maintains the projects.
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4. Top 10 trends in Business Intelligence
3) Information management goes up/mainstream
BI, by its nature, is a place where data quality problems are illuminated. As this has
been a pain point for years, BI Practitioners established best practices to manage
information integration, such as modelling techniques (e.g. conformed dimensions
for common master data across systems), data quality management initiatives,
empowerment of business users with process and applications to refine data
categorization and description...
Now, as organizations face data deluge, this pain point has propagated at all levels
of the organizations, and as a result:
- Best practices have to be refined and adopted as a discipline across IT
landscape, in a similar way than other discipline such as SOA or Business
Process Management.
- Information management initiatives have to evolve progressively to tackle
problems at the source, as this is proven to work already when establishing
total quality management programs in other domains. However, the issue is
not straightforward to tackle, the issue involves change management and
process re-engineering which leads to new strategic programs like Data
Governance, Master Data Management....
Customer case: A major services and solutions provider in the communications
industry is launching a data governance program to tackle data quality issues, with
priority on Product Data Management. The initiative is led by the business that
nominates data stewards and defines an organization and a set of processes to deal
with information quality issues. A first quick win has been launched to assess the
data and solve low hanging fruits in terms of data quality. Next steps will result in a
full data governance and master data management program and the creation of an
Information Integration Competency Center.
4) BI 2.0 (from users to prosumers)
While the web evolved from a somewhat centralized information publishing model
to an enabler of social network where each node is a participant rather than a
passive consumer, BI-users are taking a similar path: users want to create by
themselves and share new applications and actionable dash-boards, enrich
information content, etc. As a result, in addition to the classical information
distribution and discovery layer, a new layer is appearing, what we call information
enrichment. This layer enables:
- User input of new information into the system. The most frequent demand is
the ability to edit comments linked to detailed data values, aggregations,
reports, etc. But it can be enriching the classification of data by taking
advantage of folksonomies. Last but not least, new figures (independent or
calculated) have to be integrated directly by users or group of users, such as
for planning and forecasting budgets, resource needs, carbons emissions....
- Creation of ad hoc dashboards and information mash-ups: as a natural
evolution of the reporting concept, users want to assemble and mash-up data
the way they want, leveraging rich interface application to virtualize data, do
“what-if”-analysis...
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5. Top 10 trends in Business Intelligence
5) IaaS (information as a service)
Untackled value of information can be found when it is viewed with an innovative
perspective. Therefore, the ability to expose information independently of any
envelopes has the potential to unleash new opportunities of innovation. It is also a
way to integrate information services into a SOA architecture so that information
can be consumed not only by users, but also by applications.
Customer case: One of our projects in France aims to illuminate social and economic
information about the region of the “pays de Loire”. It federates information that
comes from 40 disparate sources and that used to be distributed through 15
disparate watchtowers. The solution enables the description of the incoming
information, the documentation of the meta data, and the presentation through
rich interfaces (with strong use of maps). More than 300 KPI’s are currently
managed, and the target is to cover more than 800 in the future.
6) Performance Management and Business Intelligence
As Business Intelligence goes closer to the processes and operations, it aims not
only to get the work done and improve it, but also to make sure it’s in sync with the
strategies, that resources are properly allocated in a lean manner at measurable
costs, that work is documented and traced, and that it complies with legislations.
As a result, every business activity tends to adopt technologies that are pretty
mature, but whose usage was until then dedicated to the finance department:
strategy management, planning and forecasting, profitability management and
resource allocation, or legal reporting.
Example: a new breed of applications is appearing in the area of Sustainability
Performance Management, to report on the respect on sustainability policies.
Planning and activity based management practices, for example, provide great
value when applied to carbon accounting, since it helps to identify the carbon
impact of an activity, a business partner, a product...
7) Unstructured data meets BI
Some of the more valuable information for decision making does not follow
predefined processes. They are created through office applications and exchanged
informally through e-mails and other collaboration environments. As a BI
environment comes with a set metadata to describe business terms, those
metadata can be leveraged as taxonomies, around which unstructured information
can be federated and linked to structured data. While this is still an emerging trend
that didn’t reach mainstream yet, we feel that organizations have sufficient
foundations with their Data Warehouses to begin tackle the problem.
Customer Case: With a leading European aeronautical group, we implemented a
customer dashboard to get a 360° view of their customers. Not only does it allow
cross analyzing information from CRM, finance and after sales service, but it
integrates data previously only found on personal laptops and mailing systems. An
example is the customer satisfaction data that used to be stored in Excel and
distributed through PowerPoint.
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6. Top 10 trends in Business Intelligence
8) Embedded BI
Embedded BI is about integrating Business Intelligence into business applications.
This happens particularly for “daily decisions”, when decisions have to be quickly
guided. One example is an employee of a call center who has to solve a problem.
He has to put a knowledge base in context with the problem he has to solve “on
line”. BI should then “pop up” within the current application to support the
employee’s decisions.
Customer case : A large player in the distribution of commercial television is using a
real time decision engine at their call centers to guide the operators with incoming
calls to quickly find the best offering to propose to their customers.
9) New delivery models
A lot still has to be done to make BI more affordable and easier to manage. New
delivery models are appearing to tackle the problem. With appliances, hardware
and software being “hard wired”, fine tuned and delivered as black boxes. Those
boxes can be provided “as a service”, meaning that vendors can manage remotely
and engage on a service level agreement, including performance commitment,
support and upgrades.
A whole BI platform can even be delivered as a service. However, we feel that the
traditional SaaS is mostly adapted to applications that can be easily packaged and
isolated from the rest of the IT landscape. Some subcomponents of BI, such as
Corporate Performance Management and some very specialized analytical
applications can be good candidates for BI. But, overall, we feel that data
warehousing involves too much information movement and integration efforts to
be a good candidate for SaaS.
Also organizations have to take care that all of these new delivery models don’t
lead them to a complete vendor lock-in.
10) BI for e-government/citizen self service
A new mindset is happening in our industry. Consumers are less and less interested
by a product but more and more by their usage, and the experience they have on
an ongoing basis while using the product; they don’t buy an MP3 music player but
an environment to manage their music assets; they don’t want to buy energy but
an environment that will help them to optimize their energy consumption and
carbon footprint; they don’t want a bank to propose them financial products but to
provide them an environment to manage their financial assets by themselves... As a
result, organizations must provide their customers with the right digital
environment to deliver that citizen/customer experience. BI is a key pillar in that
direction.
Customer case: One of our projects in France, already referenced in this document,
is a good example of that. Instead of trying to sell the benefits of a region, it
provides to citizens and enterprises valuable information that they will use to decide
if they should use this regions as a location for their planned activity.
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7. Top 10 trends in Business Intelligence
Business & Decision Benelux
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1200 Brussels
BELGIUM
+32 (0)2/774 11 00
Contact: Sven Arnauts
(Marketing Executive)
(sven.arnauts@businessdecision.com)
Contact: Pierre Dauffenbach
(Practice Manager BI)
(pierre.dauffenbach@businessdecision.com)
Contact: Jean-Paul Otte
(Practice Manager EIM)
(jean-paul.otte@businessdecision.com)
Contact: Jean-Michel Franco
(Solution Director)
(jean-michel.franco@businessdecision.com)
NOTE: All customer cases mentioned in this document have been realized by
Business & Decision Group.
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8. Top 10 trends in Business Intelligence
Business & Decision is an international Consulting and Systems Integration
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Relationship Management (CRM) and also a major player in e-Business and
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customer projects by driving maximum business performance. The company
has a reputation for functional and technological expertise and has forged
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& Decision currently employs more than 2,800 people worldwide.
Additional information is available at www.businessdecision.com.
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