How do you bring together data from many, different systems and enable a global sales team to be on the same page?
We were presented with a unique challenge and decided to take an unusual approach to tackle a common problem.
The challenge
The Vice President of Global Applications IT did not want to transition her business units onto the SAP platform for the sole purpose of reporting.
For a small IT team with limited options, we were keenly aware of the available possibilities.
We had a data warehouse with SAP BW on HANA and all roads would eventually lead to a single instance for consolidated data.
How do we reach our goal without spending months (possibly years) on building pipes and connectors only to find that our assumptions may be wrong?
The approach
Luckily, two things came into play at around the same time.
First, we were researching SAP Analytics Cloud as a possibly replacement for legacy tools and as a new front-end solution for enterprise reporting.
Second, the business entities had started to outline key components of their global reporting structure such as required fields and calculations.
These two things gave us an idea. ?
The solution
Fast forward a couple of weeks, we had a series of interactive dashboards for each of the 7 business units.
We used the modeling tools in SAP Analytics Cloud to quickly build charts and tiles based upon real data from each of the systems.
Users were able to easily navigate through their stories and validate the figures against their own systems. This allowed our teams to identify problems early on in the project such as …
- definition of net sales (does it include inter-company sales?)
- definition of costs (does it include freight charges?)
- aggregation issues among the 7 entities
The outcome
Instead of waiting months to see the results, we gave the business units a working “prototype” of their dashboards at the start of the project.
This led to a fascinating in-person workshop where we discussed issues such as reconciliation rules that rarely surface without “seeing” the data. Often, these conversations surface after most projects have ended and the budget has been spent.
