A roadmap for Business Intelligence

A non-technical discussion, key-definitions, critical steps and perspectives for customer-centric corporations: A simple definition of Business Intelligence would be ‘the technological framework which enables corporations to explore, analyze, and model large amounts of complex data towards one major goal: to improve business performance’. Although simple and clear, there is a plethora of technologies, methodologies and practices which, along with a rich terminology, allows misconceptions and gaps in business expectations. According to our experiences, most frequent misconceptions of the BI concepts are:
  • Business users conceive BI as the magic box which somehow captures the business state of the corporation, generates predictions and ensures business performance. Depending on their level, business users usually fail to understand that introducing a state-of-the-art Business Intelligence environment in the corporation also requires a new culture, a modern approach in decision-making. 
  • I.T. people typically identify business intelligence solutions as ‘another database’ or some kind of Reporting. Although databases are the core elements of such environments and reports are part of the typical output, it is risky not to see the big picture:  a proper Business intelligence environment consists of numerous components, a range of technologies and applications, involves several business processes and requires specialized human resources

Our view on Business Intelligence and how corporations can benefit is clear & robust. Trying to limit the use of those well-known buzzwords, we present the following generic & simplified roadmap towards a powerful BI-enabled corporation:

1.       The data store
As a first step, you need tools that automatically gather your data, apply proper transform & standardization and feed a data mart or data warehouse. This data store must gradually become and be identified as the central point of reference regarding corporate activity data.

2.       Basic data access & Reporting
Having clean and reliable data you need some kind of access to your data, basic summarization and visualization. This is where you typically have basic Reporting and ad-hoc report/ query capabilities.

3.       A first BI layer
As your corporation becomes data-aware and the business questions set by management get smarter, you will need a family of tools, a platform, to enable business users perform their own information exploitation, analysis and visualization. This is a ‘dynamic Reporting environment’ which should add great value to your accumulated data. At this point you can start mentioning that you have some form of Business Intelligence infrastructure.

4.       Data mining & statistical modeling
Once the corporation realizes that accumulated data may contain answers to a range of business questions, data mining receives the focus. Since you have rich & clean data, (semi) automated statistical & mathematical models are applied in order to generate knowledge and meta-data such as customer classifications, churn predictions, consumer credit risk estimations, campaign response predictions and more.

5.       The Analytics Center
As the infrastructure gets mature, data should be enriched in terms of metrics & dimensions. This is a type of post processing, transforming your initial data store into an Analytics provider.  

6.       The Analytics Provider
Now the infrastructure is a powerful analytics center that must become a corporate level intelligence provider. Here you need robust integration with all these platforms and channels that will enable controllable diffusion of the intelligence towards the right management people. Dashboards, micro-applications for smart devices, alerts and messaging are typical examples of tools that will advance your infrastructure into a powerful Business Intelligence provider.

Your corporation at this point is Business Intelligence enabled. The prerequisite to become a smarter corporation is to use this intelligence for better product offerings, customer management, process optimization and decision-making in general.

7.       An Intelligent Customer Interaction layer
At a next level you should be able to define, manage & assess packages of business rules, automatically generating proposals to your customers: a recommendation engine able to generate consistent customer communication scenarios through any channel, with feedback capturing and automated processing. This takes into consideration user-defined business rules, customer lifecycle and metadata along with overall accumulated intelligence.

8.       Empowering the Analytics Center
As the corporation grows and the market changes, it is of critical importance to identify new sources of ‘environment’ data, and enlist a data-feed towards your analytics center. For instance:

  •  telecoms may integrate a feed with competitor’s tariffs (this would allow to evaluate competitor offerings on actual customer and traffic, and more) 
  • retailers may gather, feed competitors pricing for certain categories of products (this would enable advanced strategies, pricing models, loyalty applications)
Although the above may be altered depending on the priorities and the industry, it clarifies that:
  • Your BI must be powered by a centralized, highly available, properly maintained data store
  • The internal goal should be to establish the so-called Analytics Provider, enabling the corporation for better decisioning, improved or even optimized functions. This requires certain culture and attitude, especially on decision-making.
  • The ultimate target should be to apply this intelligence and take customer experience into a next level. 

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