We have come across big data to be more of making insights of past, but past is past, no one can change it. How can big data drive the business forward…for any manufacturing company the “Big” use case for leveraging Big Data is Sales & Operations Planning. Let’s see how?
Simply one of the most complex calculation intense activities that span different teams across the business value chain is Sales & Operations Planning. Often referred to as the Planning Points, the below picture represents how different planning points normally leads to Big Data (billions of total planning points) :
Let’s consider an example of global automobile giant I used to work for to understand the above BigData context by multiple planning points.
There were 2 sets of planning that got done across different time horizons, one the near term plans and that were rolling every month for next 18 months. The immediate next month plan got done at a very detailed product variant level, while the other months beyond that were done at the product level. The other plan that gets done is for a longer horizon 1-3 years. In this plan, things like New Product Introduction (NPI), End of Life (EOL) plans are included. These also considers bringing in economic situation, demographics to determine the launch of new cars and what it takes to get the supply chain determined for launching the same, all firmed up in to detailed plan that runs across months, with multiple scenarios. As you can imagine, you can’t design and launch a new car in less than 3 years, so you need to plan for the same well ahead, and with some necessary details.
Their customers were essentially a wide dealer network spread across the country, 100s of them. Dealers in turn came up with sales projections that were by Product variants. The Sales managers for the each territory made their own adjustments to these sales projections. And on top of this the Sales VPs challenged these numbers and always expected couple of additional scenarios that can be modeled, to get closer to the company sales goals. In addition, there were data coming in from marketing based on their assessment on the programs they are running, and other time trend sales forecasts generated as well. Already the Sales & Operations Planner has multiple massive data sets, coming from different stakeholders, and essentially leading to consensus demand plan.
The S&OP planner also had to run through this demand plan and build a supply plan that can realize this against different planning measures. Essentially they identify the locations from where this demand can be met, and also have to run through the various constraints with the Operations (Supply) VP, essentially against critical resources to ensure the plan can be met. The car goes through stamping (where the steel is molded into a car), body shop (where the car is further given shape through welding), paint (where the car is painted) and assembly (where most of the car parts like seats are assembled together). There are people deployed to handle each of this, and some of the skilled people are also a constraint. Usually paint shop is often a critical resource and can hit capacity limit. Often in a demand driven context, additional shifts are planned. Things like plant shutdowns have to be considered in the overall plan. In addition to this, the plan should also be run through against key material constraints. Usually Engines are a critical material for Cars. S&OP planner gets all these planning points to meet demand and supply, and when he finally presents this in a S&OP meeting, in comes the finance colleagues questioning the viability of the plan against financial planning measures – Revenue, Cost, Profits, Inventory – and additional scenarios are considered to profitably align demand and supply.
As you saw in the example above, there is huge number of planning points with lot of interdependency and it’s highly calculations intensive, with need for building multiple scenarios, and truly why –
S&OP planning = Big Data.
Any manufacturing company that moves goods around – CPG, High Tech, O&G, Chemicals etc. go through Big data during S&OP planning process.
Often planners using disjointed excel spreadsheets are really not able to quickly simulate the impact of changing critical planning points on the overall impact of demand, supply and profitability, as the technology could not scale. Many decisions were made on gut than based on factual data.
This is where SAP HANA has a significant edge to fulfill the needs of Sales & Operations Planning, that needs real time planning and calculations on the fly (especially to simulate based on change across big data), to handle billions of total planning points. SAP Sales & Operations Planning built on SAP HANA can handle
-460 billion records analyzed in a sec
-18 million S&OP calculations per sec
Learn more and try 3 day free trial of SAP Sales & Operations Planning on HANA – http://www.saphana.com/docs/DOC-3545
Share your experiences on how big data is significant for Sales & Operations Planning
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