I had my first brush with the buzz of Big Data while enjoying a margarita and some amazing Mexican food in San Francisco’s Mission District. The Wall Street Journal at my elbow described HANA, SAP’s Big Data initiative. It occurred to me that Big Data’s promise of end-users directly analysing transactional data in real time, perversely confirmed the need I was seeing and experiencing on the street. Mature corporations struggled to pull basic summary data about their supply chain together quickly.
Supply chain DNA is born
During Operational Cloning’s development phase, we sought opinions from many people in the know. “Sounds great,” they all said, “but what about the data?” They had a point. Anticipating this, we designed OC to reduce the data required to describe a supply chain network and its distribution facilities. The result? A format we call supply chain DNA.
Why is gathering profiling data slow?
Talking to global and domestic companies since Operational Cloning’s launch has confirmed that margarita fuelled insight many times over. They seemed to be in one of two camps:
- in a months-long project to gather data for an existing simulation or optimisation project. or
- aware that it would take them several months to gather their data if they chose to start a simulation or optimisation project.
Why were mature corporations not able to pull basic summary data about their supply chain together quickly? After all, Operational Cloning’s DNA format requires nothing exotic. It contains summary information about things like the network structure, suppliers, SKUs, order profile, transport rates, and facilities. A Google search on “why is it hard to gather profiling data for a simulation?” yielded no insights.
Know your DNA first
Big Data technologies promise high speed analysis of structured, unstructured and transactional data (read no data warehouse required). What is the benefit of another technology-based distraction if a company struggles to pull together the basics that describe its supply chain and logistics network due to dispersed or poorly maintained data sources?
Profiling is always the first step towards understanding what you have and how to improve your operations, and any profiling format – including our DNA format – is a straightforward composite report.
Before considering Big Data technologies, try and compile your DNA. I’ll bet you a margarita that it will yield unexpected insights into where your important data lives and how to improve your operation.