IBM Cognos leading the way for big data analytics

Introduction

IBM has multiple software business intelligence products including Cognos Analytics (formerly Cognos Business Intelligence), Cognos TM1, Cognos Express, and Cognos Disclosure Management. IBM Cognos Business Intelligence front-end can connect to SAP for HANA integration from IBM Cognos 10.2.1.9 onwards through JDBC data source connectivity (IBM, n.d.). Established in 1966, Jabil Circuit, Inc is one of the largest electronic components manufacturing services corporations covering a wide-range of business areas such as supply chain management, electronic circuits, design engineering, logistics, telecommunications, and semiconductor components for computing. GE is one of the largest customers for Jabil Circuit (Universe, n.d.).

Background of the problem

Corporations need last mile data analytics on their financial operations. After performing procurement of materials, production of finished goods, inventory management, supply chain management, creating sales orders, deliveries, transportation management, advanced shipping notifications, shipping, handling units management, invoice creation, finally the company has to perform the financial close taking the refined data from the disparate data sources of the aforementioned business processes. In an Enterprise Resource Planning system, all of the above business processes are unified in one database with a structured format. However, corporations conducting the business transactions in multiple database systems and spreadsheets will have to spend a number of hours to compile the data to consolidate the general ledger postings, cash flow, and funds flow (Srilu, 2013).

The data that comes into Excel spreadsheets may not have validation system to check the input of the values except checking numeric, alphanumeric combinations. There is no typical pre-defined configuration set up in Excel Spreadsheet migrated from another system. This can create complications for a corporation to consolidate and migrate the data from Excel spreadsheets into financial statements for each month end. Excel spreadsheets can drastically slow down the business growth and the revenues of the enterprise. If the company cannot visualize the earnings and regional breakdown of the key performance indicators, they will not be able to predict the growth plan for the next quarter or next month. This can impact supply chain operations, advanced planning optimization, and supplier network collaboration, supplier network planning. In the end, the corporation will suffer losses. Jabil was plagued by these fundamental problems to close the finance of the corporations on time (Thomson, 2012).

Key solutions

Jabil implemented IBM Business Analytics, IBM Cognos Business Intelligence, IBM Cognos Business Viewpoint, IBM Cognos Controller, and IBM Cognos TM1 to overcome the financial close conundrums. IBM Business Analytics contains a bevy of analytics solutions for corporations.

Intelligent and Intuitive Analytics

Jabil implemented IBM Cognos Analytics, the right arm of IBM Business Analytics Business Intelligence Analytics. The solution from Cognos Analytics offers the financial business teams to create the analytics reports on their own. They can access the data points from BI Analytics through multiple sources, and with simple drag and drop techniques they can build the self-serviceable reports. Business teams can access IBM Cognos even when they are mobile or running browser-based tools on the Internet. Streamlined workflow provides various notifications for the corporation teams to action their specific tasks (IBM, n.d.).

Enterprise Key Performance Indicators

IBM Enterprise Performance Management provides the insights to measure the performance of the enterprise in entirety by bridging the gaps found between the supply chain management operations and the financial closing of the corporate books. It provides options to build advanced planning for the organization to incorporate techniques to project the trends of the data into the future by observing the historical patterns of the data in each business group. This provides forecasting for supply chain operations to manufacture the products into the market for various segments and customers. Companies that can observe the premonitory watch alerts notifications and trends can set the pace for business growth for every quarter to turn the data insights into revenues. EPM also can monitor the project plans built with specific financial budgets for a bevy of a portfolio of project solutions spanning several products to establish a data-driven organization. The scorecards of EPM also shows the areas where the legal and regulatory requirements for the enterprises in preparing the financial statements (IBM, n.d.).

Definitive Analytics

IBM Prescriptive Analytics performs diagnosis on the corporation overall performance with strategic management techniques. The diagnosis leads to providing recommended options to describe, observe, report, and act. Business workflow optimization drives automation of some decisions. C-Level executives can manage the enterprise-oriented decisions. These decisions can potentially arise on reviewing the brand loyalty of the customers related to specific products for either launching a new product or improve an existing product in the organization. The prescriptive analysis also can tap into the localization of the events organized by the business catering a bevy of local markets (IBM, n.d.).

Presaging Analytics

IBM Business Intelligence provides predictive analytics for performing last mile data mining analytics by wrangling the data with exploratory techniques to understand the business perspectives from various key performance indicators of business processes spawning from procuring the raw materials through financial close. Corporations need insights to plan at least 18 months ahead of their advanced planning optimization for supply chain management processes. This can be achieved through several forecasting models and applied statistical methods on the data and glean the data through text-based analytics to create trend-based models for the future. This helps to predict and forecast the number of products to launch on the commercial shelves for each retailer in the market with who Jabil is conducting the business transactions. Primarily, Jabil manufactures electronic components to assemble various electronic devices, telecommunication, and network equipment. This requires granularity of the market trends and the predictive analytics also can hook up to connect to R language for leveraging any additional statistical packages. IBM’s Apache Spark can perform the analytics in-memory in contrast to Apache Hadoop that puts IBM ahead of the pack on file-based systems. Integration of Apache Spark with IBM predictive analytics and R can boost the system further (IBM, n.d.).

Governance, Compliance, and Risk Management

Corporations performing businesses across the globe need to meet regulatory compliance requirements when trading with other countries. The risks can arise from the tax laws or customs duties levied by other countries across the globe. To balance the trade risks, the business transactions conducted in the enterprise resource planning system or through multiple database systems need to be audited. IBM has the analytics solutions for managing the risk. The risk management analytics will scan through the database of the corporation and find out the risks involved through real-time analytics for understanding the ever-increasing risks in the transactions (IBM, n.d.).

Though, Jabil implemented not all the above solutions. However, a majority of the IBM Analytics solutions were implemented. The benefits derived by Jabil through IBM Analytics solutions provided extraordinary insights to achieve the operational excellence for financial close and manufacturing plants to run their business efficiently. The solution can be applied to several other industries that are in the manufacturing of semiconductor, high-tech, telecommunications, storage devices, and network equipment. The manufacturing process involves a particular process model to prepare the integrated design of the circuits and chips. The master data management built by Jabil through their analytics, and enterprise performance management to monitor the key performance indicators can be applied to various other industries that are under a similar category. The success of Jabil can be a potential opportunity for rest of the industries in that segment to follow based on the requirements analysis and implementation of Jabil.

References

IBM (n.d.). Cognos Analytics. Retrieved November 9, 2015, from http://www.ibm.com/analytics/us/en/technology/products/cognos-analytics/
IBM (n.d.). Cognos Business Intelligence 10.2.1. Retrieved December 28, 2015, from http://www-969.ibm.com/software/reports/compatibility/clarity-reports/report/html/prereqsForProduct?deliverableId=1330380859450#!
IBM (n.d.). Enterprise performance management. Retrieved November 9, 2015, from http://www-03.ibm.com/software/products/en/category/performance-management
IBM (n.d.). Predictive Analytics. Retrieved November 10, 2015, from http://www.ibm.com/analytics/us/en/technology/predictive-analytics/
IBM (n.d.). Prescriptive analytics. Retrieved November 9, 2015, from http://www-03.ibm.com/software/products/en/category/prescriptive-analytics
IBM (n.d.). Risk management. Retrieved November 10, 2015, from http://www.ibm.com/analytics/us/en/business/risk-management.html
Srilu (2013). SAP modules overview and business processes. Retrieved November 9, 2015, from http://www.slideshare.net/srilu999/sap-modules-overview-and-business-processes
Thomson, S. (2012). IBM Analytics Gives Jabil Better Insight Into Financial Performance. Retrieved November 9, 2015, from http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=M525334P42483U27
Universe, F. (n.d.). Jabil Circuit, Inc. History. Retrieved November 9, 2015, from http://www.fundinguniverse.com/company-histories/jabil-circuit-inc-history/

One thought on “IBM Cognos leading the way for big data analytics

  1. Terrysag Posted On

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