White paper : the top 10 trends in business intelligence

Top 10 trends in Business Intelligence

The view of Business & Decision

on the evolutions in Business Intelligence


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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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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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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) 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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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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Business & Decision Benelux St-Lambertus Street 141 1200 Brussels BELGIUM +32 (0)2/774 11 00 Contact: Sven Arnauts (Marketing Executive) ([email protected]) Contact: Pierre Dauffenbach (Practice Manager BI) ([email protected]) Contact: Jean-Paul Otte (Practice Manager EIM) ([email protected]) Contact: Jean-Michel Franco (Solution Director) ([email protected])

NOTE: All customer cases mentioned in this document have been realized by

Business & Decision Group.

mailto:[email protected]





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Business & Decision is an international Consulting and Systems Integration (CSI) company. It is a leader in Business Intelligence (BI), and Customer Relationship Management (CRM) and also a major player in e-Business and Enterprise Information Management (EIM) contributing to the success of customer projects by driving maximum business performance. The company has a reputation for functional and technological expertise and has forged partnerships with key technology vendors. Located in 20 countries, Business & Decision currently employs more than 2,800 people worldwide. Additional information is available at www.businessdecision.com.

© 2010 Business & Decision. All rights Reserved.

Business & Decision Group rue de Courcelles 153 F-75017 Paris FRANCE Tel: +33 (0)1 56 21 21 21 Fax: +33 (0)1 56 21 21 22 www.businessdecision.com

Business & Decision Benelux rue Sint-Lambertusstraat 141 B-1200 Brussel/Bruxelles BELGIUM Tel: +32 (0)2 774 11 00 Fax: +32 (0)2 774 11 99 www.businessdecision.be

http://www.businessdecision.com/

White paper : the top 10 trends in business intelligence

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