Think about introducing any new software solution into an organization’s IT landscape is like introducing a non-native species into an existing ecosystem. The ecosystem already enjoys a balance between the complex biodiversity that exists there. Introducing any non-native species raises the potential for negative and unintended consequences. As such, one might think introducing GreatVines beverage selling software platform into a client’s existing IT landscape raises the risk of disrupting the existing and harmonious balance. This post focuses on the replicable, proven implementation and integration processes GreatVines has developed over the years which makes them anything but an “invasive species”.
Between differing ERP systems (or lack thereof), data warehousing variations, various email/networking environments, and the wide array of end-user device and antivirus deployments, the potential for disruption when implementing a new application is real. To be successful in seamlessly inserting a non-native solution into these varying environments, GreatVines has had to evolve flexibility in its ability to get data into and out of the platform, and in its ability to support many processes and measurements.
Basic Building Blocks – ERP Setup Information
A foundational component for GreatVines is the interface with client ERP or financial systems. Control data, like customer and product information, needs to come regularly from these external systems, ensuring data hygiene and eliminating any duplicate data entry. Client systems must feed GreatVines master product and customer hierarchies. Ideally this should include customer geographies, salesperson assignments, internal inventory levels, shipments to customers and other key data points. Properly integrated, GreatVines provides sales end-users a window into the data within their ERP, directly from the GV interface. No need to login to the ERP separately or bother HQ staff. Automating all this information also greatly simplifies GreatVines setup. GreatVines’ successful ERP integration process has enabled smooth interfacing with SAP, Oracle JD Edwards, MS Dynamics GP/AX/NAV, AMS, Quickbooks, MAS, Sage, and Plex among others.
Delivering Decision-Support Data to Clients
Measuring and acting upon leading and lagging indicators is a big part of our methodology and is well documented in past posts. GreatVines users can gather some of this information via completing call info fields or surveying. However, components of it also must come from external data feeds. Those feeds need to be normalized and mapped to corresponding data in GreatVines.
A major need in the US Beverage Alcohol industry is a feed of distributor depletion information describing the what/when/where of sales, from distributors to on- and off- premise accounts. Larger suppliers pay for feeds of this information from services like VIP/BDN or Trade Pulse. Smaller producers with relatively small market penetration may opt to get data directly from their distributor partners and load it into our tool themselves. Having a depletion feed allows supplier partners to compare leading indicator sales activities such as product displays or staff training with lagging indicator depletion sales in order to directly correlate activities to sales results.
Another key lagging sales indicator clients often need is Retail Scan Data from IRI or Nielsen to compare sales of client products against those of their competitive set. GreatVines has a working prototype to include this data in our dashboards and is on track for the upcoming launch of an innovative new product in this space. (Stay tuned for announcements!)
Some clients want to highly segment end accounts and maintain complex chain account hierarchies. Nielsen TDLinx serves as a basis for this. Many of our clients choose to integrate TDLinx as the backbone of their account universe. Again, proper integration of GreatVines is critical to minimizing disruption in these processes.
Ways and Means
To access and interpret all this outside information, GreatVines has invested heavily in interface and monitoring capabilities. For batch interface work, GreatVines uses a tool called Pentaho Data Integration (Kettle) that is hosted in the Amazon Cloud. It scales from a few servers to dozens on an as-needed basis. GreatVines’ management tool, dubbed the “Elastic Jobs Manager” schedules jobs, spins up ad-hoc Amazon servers, and monitors/reports job results. We also use Amazon Redshift, a petabyte scale parallelized columnar data store to parse extremely large data sets and enable the Change Data Capture (CDC) we need to move around only truly incremental results.
If that last technical bit is as difficult to parse as this sentence from an environmental biology text:
“Discussion focuses on acclimatization of acoelomates to disparate benthic zones”
then just take solace in the knowledge that the experts at GreatVines have invested countless hours of hard work and expertise into ensuring their integrations are harmonious and minimally disruptive to your existing IT ecosystems.
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