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CFO Insights 2021 March
IN-MEMORY COMPUTING: “Promises a massive gain in speed”
CFO Insights is a monthly publication to deliver an easily digestible and regular stream of perspectives on the challenges confronting CFOs. In this article, we describe "In Memory Computing" and its effective use in a finance function.
Explore Content
- What is In-Memory Computing?
- In Memory Computing in Action
- “In-Memory computing” in the CFO’s office
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 Action:
Case 1:
A transportation company carried more than 23 million passengers each day on more than 12,000 trains. Using legacy technology, the company could handle no more than 40,000 concurrent Internet users, many of whom spent up to 30 minutes trying to book tickets online. With in-memory technology they can now handle more than 120,000 concurrent users. Completing a reservation now takes mere seconds.
Case 2:
A retailer used in-memory as part of a multi-year program to modernize their aging financial systems environment. The company’s legacy budgeting and forecasting system was more than 20 years old, and was heavily dependent on spreadsheet templates and supplementary schedules. Their solution was a new system with the ability to drill down from totals to transactional detail. The system delivered better analysis, reduced time spent on financial processes, and enhanced output view options.
Case 3:
An insurance company wanted to transition to a new finance platform to improve and standardize financial processes. Using in-memory technology, the company was able to gain near real-time access to data to enable analysis and support decision-making.
“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?
- What kind of roadmap do we need to draw to benefit from the digital transformation?