CFO Insights 2021 March

What is In-Memory Computing?

Dealing effectively with digital information requires a technical architecture that can handle massive data sets, without sacrificing availability or timeliness. That is what in-memory technology can deliver. Key applications include transaction processing, event processing, distributed caching, and scenario modelling.

In-Memory computing enables Finance organizations to have significantly high access speed to access and analyse high volume of concurrent transactions. It provides automated notifications in real-time to enable better decision-making. Further more advanced features enable dynamic big data calculations in milliseconds.

For many future data management needs, in-memory will likely be an indispensable tool. The explosion of information streaming in from the Internet of Things alone could make In-memory a critical capability for companies undergoing digital transformation.

From the hardware-based point of view, data analysis consists of three components; (1) the processor to perform the calculations, (2) the storage to store the (manipulated) data, and (3) a system that transfers data between the two. Naturally, the slowest of these components is the bottle-neck for the performance of IT-based data analysis. More specifically, it is not the latency of random-access memory but the latency of hard discs. Processing power is not used to full capacity because the data to be processes is not retrieved fast enough from hard discs. In Memory Computing (IMC), in a nutshell, is moving data which has traditionally been stored on hard discs into memory. By focusing on pure hardware characteristics latency is dramatically reduced. Consequently, the process of data analysis is subject to a tremendous speed-up.

“In-Memory computing” in the CFO’s office:

While significant complexity is typically encountered across Finance, there are some areas in which it can be crippling. Multiple ERP systems are one culprit, for example, impeding the organization’s ability to pursue swift, focused innovation cycles. Managing working capital— including DSO (day sales outstanding), cash flow, and cash position—are perennial challenges. Complexity also plays a major role in long closing cycles and can thwart the finance team’s ambitions to tap reliable finance data at any time, on demand.
IMC can be effectively used in a finance function to work with detailed projections for unit sales and revenues at the stock-keeping unit (SKU) level. IMC systems allow multi-dimensional scenario testing by interactively exploring the financial and volume implications of price changes in specific geographic markets or channels. Analysts are able to determine almost instantly the impact on profitability, inventories and cash flow of specific actions. An IMC analytics system can run several different sets of assumptions or scenarios in a matter of minutes, compare results and enable those involved to knowledgeably discuss the best approach.

Additional resources

• In-memory: A New Tool for Business Process Transformation (CIO Journal / The Wall Street Journal)
  
• Crunch Time - 決断の時 (Japanese)
  
  • What kind of roadmap do we need to draw to benefit from the digital transformation?