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SaaS BI - A Value Driver for ERP Deployments?

Posted by Joseph Schramm on Mon, Jul 06, 2009 @ 10:17 AM
  
  
  
  
  

Having spent more than the last 10 years involved in "Business Intelligence (BI) for ERP customers" I have heard countless stories from which a number of themes have evolved. One of the most pervasive is the "BI and Reporting as an After-Thought" theme.

This is the one where a customer goes through the process of evaluating, selecting and implementing an ERP solution only to learn that after the go-live the end users are left with "bare bones" minimal reporting. In many of these cases, users have complained that they have less reporting now than before (the ERP implementation) and that they have taken a step backward in terms of visibility into the business, functionality, etc.

Part of the reason for this is that ERP implementations are often so disruptive to an organization. In many cases there is a ton of energy and focus (rightly so, I would argue) that goes into the examination of business processes (existing and desired end-state), the blue printing of the solution and the physical deployment. Most organizations struggle to "keep the lights on" during these ERP implementations. So it is no wonder that something like BI and Reporting are put on the back burner.
In the past, traditional BI and Reporting deployments were not unlike ERP projects. If not quite on the same scale, the process is very similar. The following outline is an example of the potential steps involved in deploying a BI solution (note that these steps occur AFTER a solution has been selected - a process that has its own lifecycle):

  • Project Prep
  • Blue Print
  • Infrastructure Build
  • Software Installation and Configuration
  • Data Warehouse Development
  • Content Development
  • Security Definition
  • Training, Education
  • Go-Live Planning
  • Testing
  • Support

So it's no wonder that these projects get put off until sometime after the ERP deployment.

But does this still need to be the case?

I recently had a conversation with a partner about a prospect for our SaaS BI solution. He told me that the client was about to finalize their ERP decision and execute a purchase and in 6-9 months they would want to start looking at reporting. Why do they have to wait???

With the advent of Software-as-a-Service BI, I would argue that a robust operational Reporting and BI solution could be delivered in parallel to an ERP go-live as opposed to many months, if not years later. Requirements definition could take place during the ERP blueprinting phase. During the QA phase of an ERP implementation the data could be fed to the SaaS BI environment in parallel. Since there is no requirement to provision hardware, install software, etc. with a SaaS BI solution, the provider could perform their data integration work (incorporating non-ERP data as needed in their data model) almost in parallel. Then the QA of the solution could take place in concert as part of the ERP QA cycle. This would provide the end users with a fully functional reporting and BI solution as part of the overall ERP go-live vs. after the fact.

What is your opinion?

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COMMENTS

Sasha 
I agree with you that reporting and BI are more of an after thought in most ERP implementations. I think part of the reason (with some truth to it) is because the genesis of BI has been from a Data Warehousing world where BI need has only arisen when there is a critical mass of transactional data. But I think that is only partly right. As we have seen in recent times - decision making based on historical data is only correct sometimes it is no longer the indicator for future given the rapid changes in business models and conditions. But I think as part of maturity around BI and BI itself goes from Historical analysis to Predictive analysis area, things will change and BI will get embedded into Operational Business Process. 
 
Subraya Mallya

posted @ Monday, July 13, 2009 9:29 PM by Subraya Mallya


Subraya, 
 
 
 
You raise an excellent point and one that I fully agree with. We are seeing a lot of interest in being able to combine past/historical data and metrics with forward looking data and metrics to better predict things as well as manage risk. One example is taking revenue and sales metrics from ERP (past customer purchases) and merging that with CRM data (forcast/weighted revenue opportunity) to get a more comprehensive view. This is just one example and the use of predictive analytics (as you suggest) can certainly add more value in this area. 
 
 
 
Joe

posted @ Tuesday, July 14, 2009 6:27 AM by Joe Schramm


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