WHITE PAPER BEsT PRAcTIcEs: PusHIng ExcEl BEyond ITs limits WITH InfoRmATIon optimization

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1 Best Practices: Pushing Exce Beyond Its Limits with Information Optimization WHITE

2 Best Practices: Pushing Exce Beyond Its Limits with Information Optimization Executive Overview Microsoft Exce is the most widey used business inteigence and reporting too in enterprises today. Despite its origina use as just a spreadsheet, it now acts as a data coection/ integration too, as we as an anaysis and reporting too. It is the defacto soution for both business anaysis and reporting. However, Exce aso has its imits. These imits impact organizations by adding cost and risk when anaytics requirements outgrow the too. However, thousands of users wordwide have discovered a way to overcome these imitations. This paper iustrates how an Information Optimization soution can overcome Exce s imitations and provide true business vaue such as: Timey, continuous operations improvement; Rapid, efficient and effective consoidation of acquisitions; Detection of frauduent activity across miions of transactions; Reduction of direct operating costs for critica business processes; Risk reduction and poicy compiance using trustworthy data and more. Lack of Data Integrity: Exce never provides a singe version of the truth for the organization since it can be atered so easiy. Human invovement introduces errors, and as time passes, spreadsheets become error prone. Origina data sources may or may not be identified. Maintenance Issues: Spreadsheets can be difficut to maintain if the data is gathered from mutipe sources. Each time anaysis or reports are updated new source data imports add time, cost and potentia human error. Visua Basic scripts can hep in some cases; however, programming skis are required, creating a need to invove spreadsheet jockeys or IT departments. Limited Accessibiity: Access to spreadsheets is generay imited to individuas. Windows fie sharing is cumbersome at best. Onine soutions hep overcome these imitations but introduce security concerns. Lack of Data Security: As ocay stored fies, spreadsheets are prone to theft and data oss. There is no notion of controing access privieges among various users ony a one size fits a poicy which can ony be managed on the honor system. Reduced Querying Capabiity: Anayzing data spanning mutipe sources is compex and very difficut to maintain. Less Scaabiity: Enterprise anaytics often requires queries run over data sets exceeding maximum spreadsheet fie size imits. Auditors often resort to testing data subsets instead which reduces accuracy and increases risk that anomaies or trends wi be missed. What Users Reay Like About Exce However, as 500 miion Exce users wordwide know, Exce has some hard to beat advantages: Easy to Learn: Spreadsheets are as common as computers or the Internet. These instinctive, powerfu anaytic toos aow users to start with simpe math and advance as they experience the appication itsef. Exce s Limitations When Exce data anaysis activities morph into business anaytics, auditing and reporting for poicy compiance, Exce strugges to keep up. This causes unforeseen time, costs, frustration, added risks and errors. Key Exce imitations incude: Version Contro Issues: Originay designed for persona use and singe-user access, Exce coaboration, most often, is via emai. Users typicay retain dupicates, often with conficting data and formats essentiay creating massive version contro issues. Readiy Avaiabe: Because the program comes with Microsoft Office, it s widey avaiabe to most computer users. Advanced Anaytic Functions: Exce does a great job handing data, sicing and dicing using pivot tabes, and then running data anaysis using macros and Visua Basic scripts. According to one survey, 9 out of 10 users don t ever use the advanced functionaity avaiabe to them. Appication Integration: Embedding Exce reports in other programs, particuary Microsoft Office programs ike Word, PowerPoint, and Outook is extremey easy and highy productive. No IT Invovement: Spreadsheets have been around so ong, no IT invovement is required to use and maintain them.

3 Best Practices: Pushing Exce Beyond Its Limits with Information Optimization What Users Love about Exce and Information Optimization: Many Exce users recognize the shortcomings of the software and therefore have turned to Information Optimization to augment Exce s imitations. One of these patforms is the Information Optimization soution from Datawatch a system that has been used by sma and arge, Fortune 500 companies for over 20 years. In fact, over 90% of Datawatch s 40,000+ users aso use Exce. Datawatch compements Exce by adding key capabiities: Extracts data from across the organization, incuding unstructured and semi-structured formats; Acts ike a porta bringing together access to seect data sets from deimited ASCII text, EDI streams, pain text, PDF, HTML, XPS, database tabes, queries and more; Is an expediter, compiing reports on the fy, anytime; Eiminates repetitive work, sorting, grouping, sub-totaing a automated to save time and money and increase accuracy and trustworthiness. Information Optimization fis Exce s data integrity gap by becoming the singe version of the truth for fies it exports to Exce by handing versions and tracking data back to its origina sources. Information Optimization has emerged as a new category that turns disparate data into dynamic reports for easy anaysis and visuaization. Information Optimization aows end users to easiy access, extract and incorporate data from any combination of existing reports aready pubished inside or outside the enterprise, then create, distribute and pubish dynamic, interactive, and higher eve reports without requiring the time or expense of IT invovement. Pervasive Performance Group The Power of Information Optimization Information Optimization heps organizations save time and money, improve operating effectiveness, and reduce risk by empowering business anaysts and auditors with: Timey access to data in the right form Increased trust in data Continuous detection of anomaies, fraud and trends across comprehensive data sets Minima IT invovement This whitepaper expores how thousands of business anaysts and auditors are using Datawatch aong with Exce to create significant business vaue whie improving the quaity of their work. Timey Access to Data in the Right Form Data anaysts and auditors often say they spend too much time working with data instead of anayzing it. And it s not just about coecting data, it s about deivering the right information to the right paces, at the right time, to drive the right actions. This is especiay difficut when using Exce as the primary means of performing data anaysis. Unfortunatey, most anaysts have no direct access to data sources across the organization. This eads to IT requests, added time, cost and deays in decisionmaking and detection of inefficiencies and fraud. According to a survey sponsored by Datawatch, neary a (97%) respondents reported they must work with data from mutipe sources incuding: Exce 77% Databases 54.3% ERP systems 42.9% Accounting and Genera Ledger appications 77.1% Mainframe and egacy systems 5.7% Network fies 14.3% Respondents aso stated they must work with data in oosey structured and unstructured or semi-structured formats such as EDI streams, PDF fies, reports or text fies. When using Exce, the entire inefficient data gathering process is repeated each time anaysts need to update their work, promoting human error and further deays in critica business decisions, and performance improvements. How It s Done: Datawatch simpifies data preparation and ongoing access to business critica information by providing direct access to virtuay any existing report or fie format in the organization incuding ODBC/OLEDB, Exce, deimited ASCII and other non-report data sources. The soution aggregates data from these mutipe sources into a singe, comprehensive, indexed view, and provides on-going access to updated, secure, web-based, interactive reports and dashboards for further anaysis and performance monitoring. Users simpy appy an existing Datawatch mode to mutipe iterations of a given report to easiy consoidate data generated over the ong term. From a singe copy, to hundreds of updates, the same mode handes the task, with no copying or re-engineering needed. The resut is direct cost savings in time spent accessing data and improved operationa decision-making with timey access to business critica information.

4 Best Practices: Pushing Exce Beyond Its Limits with Information Optimization Use Case Exampe: A top 10 goba audit firm uses Datawatch to vasty simpify data preparation for its cients. Our audit procedures incude a range of anaytica techniques that require us to capture financia data from our cients. With oder and bespoke (custom) systems, the main means of extracting information is in printed reports. By faciitating the capture of information, we coud perform our procedures more efficienty, aowing us to provide greater insight, vaue and quaity to our cients. Senior Manager, Auditing firm. The firm uses Datawatch specificay to: Gain direct access to mainframes and server data for oading into a custom audit software package; Combine mainframe and server data with data from past reports, covering account baances, transactions and ratios; Transform the current and historica data trapped in reports into ive data; Better access and everage a bank s ibrary of mission critica reports, whether from a transaction processing service bureau or a document and report storage system; and Extract information from oan records and oad the data into an Exce tempate to identify various factors and buid a comprehensive oad review, turning a three to four day data-gathering task into one hour. Use Case Exampe: A goba retaier uses Datawatch to consoidate acquisitions and communicate on-going operationa performance data. Specifics incude: Convert static, egacy data into dynamic reports made avaiabe to a key departments throughout the parent company Access critica data for demand panning such as customer totas, item totas, and customer item history which woud otherwise have to be obtained by searching through an item cataogue Aow accounts receivabes to set up new vendors by seeing the acquired company s vendor data down to the detaied record eve Run other queries as needed on an ongoing basis to integrate business operations and processes. Increasing Trustworthy Data The vaue of trusted data to an organization is in the reduction of risk. Reducing business risk resuts in savings in fines, theft, brand vaue and the abiity of the organization to obtain credit. What Information Optimization provides that Exce does not is a trusted means of consoidating data for use by the organization. A data used by business anaysts and auditors, whether it s, unstructured or semi-structured data, data from custom inhouse systems or widey used enterprise appications (i.e., ERP systems), or from Exce itsef, must aways be tracked back to its origina source to avoid questions of data ineage and accuracy. How it s done: By tracing a data back to its origina sources, Datawatch provides a singe version of the truth for the organization and embeds digita signatures to confirm data ineage and authenticity. It aows changes to be tracked by author, event and date/time stamp. Furthermore, the origina source data report or otherwise is absoutey sacrosanct. Users can manipuate it with cac fieds, fiters and other operations; however, they can t directy change or destroy it. A these features are key to heping the business manage risk and compy with poicies and reguations. Use Case Exampe: A arge credit union, serving more than 102,000 members was chaenged to effectivey understand, anayze and audit their oan portfoio. The organization is very active in car oans, home equity ines of credit, credit cards and business oans. Management wanted to ensure they had the right, trusted data for a wide variety of projects. The anaysis incuded actua versus expected risk eves for oans, and for measuring the work performance of the interna audit department itsef. It is critica to our credit union s success to proactivey manage the actua risk of our oan portfoio, and manage the everyday performance and workfow of our interna audit department, with the best possibe information avaiabe. AVP for a arge credit union The company was unabe to use Exce to meet their needs, because they required: Easy access to oan origination reports from their transaction processing system, Symitar, without the need to turn to costy IT resources; Access to the data without using compex database toos or a report writer; Expedited workfow of interna audit activity; Reduction in the amount of oan fies with missing, erroneous or non-compiant data; and Eimination of the backog of work stymied by bad data. The company achieved the desired business insight into its oan business and increased its operationa performance by using Information Optimization to: Mine and customize data coming directy from Symitar, incuding oan origination reports from historica report data; Transform the data into a data tabe, enabing the credit union to sort and fiter, adding new cacuations as needed;

5 Best Practices: Pushing Exce Beyond Its Limits with Information Optimization Stratify the data with subtotas and grand totas that incude many eves of detai; Create Exce-based summaries of the top ten auto deaers and top ten in-house oan products; Buid reports using empirica, trusted data that shows which oan groups were riskier than expected and assessing the eve of oan charge-offs by auto deaer to identify oan quaity probems; Audit 100% of oans processed by the Loan Center more efficienty and cost effectivey; Create interna team performance scorecards based on the number of oans funded each day, the number of days between approvas and oan competions, the number of corrections made to oan data by oan and oan officer, and other metrics. high voume transaction testing. Foowing are some exampes of how the team uses the soution to save time and money and better manage risk. Perhaps the most important project achieved using the Datawatch Information Optimization Patform is our oan portfoio review project. Datawatch heps our executive management team proactivey manage our oan portfoio. AVP for a arge credit union Continuousy Detect Anomaies, Fraud and Trends across Comprehensive Data Major opportunities to improve data anaysis and audit effectiveness ay in an anayst or auditor s abiity to more quicky identify data anomaies, fraud and trends. More than 66% of auditors surveyed state they do not have the abiity to identify trends. This is due to the inabiity of toos ike Exce to hande checks across datasets with miions of ines and rows. How it s done: Datawatch aows comprehensive data sets to be assessed, incuding thousands of report pages and arge data scaabe up to miions of ines and rows and across mutipe data sources. It aso aows auditors to buid report modes, or custom data assemby rues, for ater reuse by others. Modes mine and match data from among various reports to spot operationa or report needes in the haystack. Finay, it aows users to perform additiona cacuations and anaysis on the mined data and the abiity to export it to Exce as needed. Use Case Exampe: A hospita business anayst team uses Information Optimization with Exce to perform a variety of advanced anaytics and auditing activities for operations improvement, insurance caims and payment processing, and The team uses Datawatch as an intermediary between their interna transaction system MEDITECH and other programs ike Exce for communicating resuts. The MEDITECH system doesn t aow them to see how individua coectors are performing on a monthy basis. They use Information Optimization to identify trends at the individua coector eve and see where improvements are occurring. The team can run executive summary reports in MEDITECH on aging receivabes by payer or coector, but can t get it down to the patient eve. They can access the detaied data, however, it is quite arge 130,000 rows and 18 coumns. With Information Optimization they are abe to manipuate the detaied data and get down to specific patients and individua transactions that aow them to take action. Before, they coud see the probem areas but it was extremey difficut to identify the root cause. For exampe, they might think someone was sow to pay when in reaity they were never sent a bi. The team was aso asked to hep check the quaity of a major migration of MEDITECH to a new version. It was the argest upgrade they had ever done. They were asked to do testing before and after the instaation to make sure the system was propery baanced. They took a report with 18 coumns and 129,200 rows before and after, and ran a match on 2,329,000 ces. They detected things that were off and were abe to fix them. The software vendor said they had never experienced the eve of testing the team provided using Datawatch s Information Optimization Patform. In our business we dea in such a high voume of transactions, it can be the neede in the haystack that kis you on a compiance issue. Information Optimization aows you to focus on what reay matters most. Team Leader, hospita business anayst

6 Best Practices: Pushing Exce Beyond Its Limits with Information Optimization Minima Direct IT invovement A of the use case stories described required itte to no IT invovement in conducting audits. Auditors found that the Information Optimization soution: Minimizes anaysis and audit process disruption which saves time and money; and Promotes transparency in data anaysis and increases audit effectiveness. The business endorses Information Optimization because it works we with existing systems and addresses many critica imitations of Exce and other packaged software, without direct IT invovement: Coaboration: Aows coaboration to occur using existing systems. Data Integrity: Provides a singe version of the truth for the organization since it traces a data back to origina, trusted sources incuding timestamps. Maintenance: Maintains data is easy, using modes that automate the coection of source data gathering. Human error is virtuay eiminated. Access to reports is easy directy via the patform or via export to Exce or other programs. Data Security: Unike Exce, the Information Optimization soution provides deegated administrative access privieges to ensure ony those aowed to see specific data have access to it and easiy integrates with Active Directory and NTFS to ensure compiance with IT data security poicies. It aso password protects and encrypts PRFs (portabe report fies) and accepts passwords to direct database, PDF, FTP / HTTP access attempts. Querying Capabiity: Provides powerfu anaytic capabiities simiar to what Exce provides but without the need for Visua Basic programming. A few power features Exce users ove incude: Tabe exports arrive in Exce as competed Pivot Tabes Easy data manipuation sorting, grouping, subtotaing, conditiona formatting and other data aggregation is easier to perform than in Exce Data format updates to dupicates changes such as fiters, sorts, and other modifications are automaticay carried over to dupicate copies. Summary formuas, dri up/down features and conditiona formatting aso transate into fuy functiona modes in Exce. Scaabiity: Scaes far beyond Exce or other programs, up to 10 miion rows, as needed. Concusions Thousands of data anaysts and auditors wordwide take their Exce spreadsheet to the next eve with the Datawatch Information Optimization Patform. Using Information Optimization aows business anaysts and auditors to do more with fewer resources whie increasing anaysis output quaity. It aows data to be accessed in the right format, estabishes trustworthy data, and enabes detection of anomaies, fraud and trends across massive, compete data sets, a whie minimizing direct IT invovement. About Datawatch Corporation Datawatch Corporation is a eader in providing information optimization products and soutions that aow organizations to deiver the greatest data variety possibe into their big data and anaytic appications. Datawatch provides organizations the abiity to integrate structured, unstructured, and semi-structured sources ike reports, PDF fies, and EDI streams into these appications to provide a 360 degree perspective of the issues and opportunities that exist in their businesses. More than 40,000 organizations wordwide use Datawatch s products and services, incuding 99 of the Fortune 100, and businesses of every type can benefit from the power and fexibiity of Datawatch s industry eading soutions. Datawatch is headquartered in Chemsford, Massachusetts with offices in London, Munich, Singapore, Sydney and Mania, and with partners and customers in more than 100 countries wordwide. For more information, visit Contact Datawatch For more information about Datawatch, contact us directy, , or Datawatch Corporation, 271 Mi Road, Quorum Office Park, Chemsford, MA 01824, USA To free US (800) or Datawatch Corporation. A rights reserved. Datawatch, the Datawatch ogo, Datawatch Monarch Professiona and other product names, ogos, and tag ines are trademarks of Datawatch Corporation. A other trademarks or registered trademarks are properties of their respective owners.

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