What Do Business Intelligence Consultants Mean By “Solutions”?

Management consultants and business intelligence, analytics and big data system integrations often use the terms accelerators, blueprints, solutions, frameworks, and products to show off their industry and business domain (sales, marketing, finance, HR, etc) expertise, experience and specialization. Unfortunately, they often use these terms synonymously, while in pragmatic reality meanings vary quite widely. Here’s our pragmatic take on the tangible reality behind the terms (in the increasing order of comprehensiveness):

  • Fameworks. Often little more than a collection of best practices and lessons learned from multiple client engagements. These can sometimes shave off 5%-10% of a project time/effort mainly by enabling buyers to learn from the mistakes others already made and not repeating them.
  • Solution Accelerators. Aka Blueprints, these are usually a collection of deliverables, content and other artifacts from prior client engagements. Such artifacts could be in the form of data connectors, transformation logic, data models, metrics, reports and dashboards, but they are often little more than existing deliverables that can be cut/pasted or otherwise leveraged in a new client engagement. Similar to Frameworks, Solution Accelerators often come with a set of best practices. Solution Accelerators can help you hit the ground running and rather than starting from scratch, find yourself 10%-20% into a project.
  • Solutions. A step above Solution Accelerators, Solutions prepackage artifacts from prior client engagements, by cleansing and stripping them of proprietary content and/or irrelevant info. Count on shaving 20% to 30% off the effort.
  • Productized Solutions. The main difference between Solutions and Productized Solutions is that the latter require a dedicated support team. These are mostly non-client facing resources that are responsible for enhancing and maintaining the solutions. Productized Solutions will get you 30% to 50% into a project.
  • Products. Products have an SKU, which you can buy with or without professional services. Just like any product from a software vendor Products have a fully dedicated, non-client facing R&D staff, help desk and a release and upgrade cycle. Similar to any other packaged off-the-shelf apps Products will still require professional services for integration and implementation, so count on saving 50% to 75% of a project effort.

We recommend using the above definitions to separate hype and fiction from reality when evaluating consultants and system integrators responses to your RFIs and RFPs.

As always I welcome suggestions, comments, and constructive criticism. 


Agree but what about the cost of customization ?

Very interesting Boris, and very usefull both for SIs on their way to productization and customers when selecting SI.
But don't you think that we should add one parameter: packaged solutions are good if they match the project destination. But things don't always happen this way, especially when the goal of the project isn't only to adopt best practices, but also to differentiate or innovate.
Then, you need flexibility to move away from the standard, and in ly experience the more the solution you use is packaged, the more costly it can be to customize. An exemple in BI is SAP BW who provides very interesting business content, which corresponds in my opinion to your product categorization. This brings value, but it won't bring 50 or 70% of project efforts down except if you decide to take it as a standard without any customization... which is very rarely the case in data centric project in my opinion.

Jean-Michel, thanks for the

Jean-Michel, thanks for the comment. I should've mentioned in the blog what a solution or a product is in the BI context. As you know most often these consist of industry or business domain specific
- data connectors
- data extractors
- data models
- metrics
- reports and dashboards

Solution Accelerators, etc.

Boris's categorization of frameworks, solution accelerators, etc. is very appropriate.

I would like to make one other observation: in the form of a couple of sub-categories in the solution accelerators as well as solutions categories - this has to do with technology/productivity enhancement solutions versus buisness solutions.

Technology/productivity enhancement solutions typically provide a fully or partially automated solution to an often encountered technology related problem. For example, consolidation of BI reporting in multiple platforms to a single standardized BI platform, or migration from platform A to platform B for BI reporting, requires that we understand the need, size and complexity of the transformation exercise. A metadata-based tool that can read the metadata from the as-is BI platform, and provide clear statistics on the complexity, significantly reduces or nearly completely automates this assessment phase in the lifecycle. A reader component for the source platform and a writer component for the target platform might as well substantially or partially help in automation of the migration process.

Business solutions essentially focus on a particular industry/domain and the creation of either a jumpstart analytical kit or an elaborate prepackaged solution with identified KPIs, metrics, reports, dashboards and a data model for a particular area (e.g., investment management analytics, or HR analytics).


Yes, Sundar, thank you,

Yes, Sundar, thank you, excellent point. I indeed only mentioned business solutions/accelerators/products. I are absolutely correct that code conversions, metadata readers, data profiling tools are all technology solution accelerators.

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