Consulting:
Specialties
Overview
The accuracy and accessibility of corporate data have become major issues in today's business environment. These issues are being driven by many factors.
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The accelerated pace of mergers and acquisitions has and is causing major data quality problems that are showing up as part of standard audits, regulatory audits, customer service reviews, and in some cases, litigation searches. In every merger and acquisition, each party’s corporate data must be combined as quickly as possible to meet required reporting and filing dates. In many cases, this data analysis effort has been performed by staff who really didn't understand the existing data and how and when it is used while trying to meet impossible target dates.
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The E-World has broken down corporate data "glass walls". In the old days, corporations had strict control of its data: who viewed it, who updated it, and what it contained. As part of new B to B and E-tailing business models, corporate data is now being shared by business partners and regulatory agencies on a real-time basis. Companies are now dependent on the quality of its business partner's data and its customer web entered data.
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Information about corporations and individuals has become big business. It is being proliferated, in many cases, without the approval and knowledge of the effected parties. In many cases this data is inaccurate.
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Corporate data is being accessed through various sources outside of a company's control. These sources are not all accurate.
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New and constantly changing Privacy legislation is requiring companies to manage access and use of customer data to a level that is not always available in their current "e" and core operational systems environment.
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Most companies don't have true Customer Master Files. In the real world, companies have pulled together data to serve as specific "e-tailing" and privacy function data sources (customer registration, web site accessibility, privacy, customer service history, etc.) very quickly. In many cases, the data is incomplete, inaccurate, and in many cases, missing.
Data problems can be divided into two categories: foreseen and ad-hoc.
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Foreseen data problems include ones that occur as part of a known event. Examples of such events are: merging of data from two or more systems (a merger or acquisition of a new business); installation of a major software package such as PeopleSoft, SalesLogix, Siebel, etc.; incorporating new data sources (including house holding to include geo codes) into existing as part of existing; and government regulation reporting changes (STP). Solving these varies according the scope of the problems uncovered as you work through the event.
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Ad-hoc data problems are the tough ones. These are the ones that the internal (and more unfortunate, the external) auditors, customers, or governmental agencies find. When the data problems are uncovered, their resolution is placed on the fast track. No one wants to admit that there are problems until they are forced to do so. No one plans or budgets for data problems. Critical resources are not always there when you need them.
Although there are many solutions being touted as the "one-step answer" to data problems, one must accept the fact that maintaining data quality is a never-ending and ever-evolving task. External and many internal data sources are changing as the business dictates. More data is being collected and stored. Companies have new business partner relationships that are forcing them to use data in new real-time business processes outside the corporate data center.
What do we do
Advantageware specializes in solving data centric problems. We do "what it takes" to find out exactly what is wrong so that we can accurately define and resolve the problem. "Data quality" problems are typically first presented in context of other things: the system doesn't work, the numbers don't match, things don't balance.
Our mission is to not only find and fix the immediate problem, but it also create and put audit controls into place so that data quality can be monitored on an on-going basis.
The trick to resolving these types of problems is careful and quick problem determination. This is not always an easy task, but performing this in a carefully defined way makes sure that we cover all the bases and communicate status and results.
We work our clients to first define and document all the symptoms of the data problem. We interview staff and review reports and related process media displays to undercover and document the symptoms. Using our checklists and myriad of tools, we examine processes and their related data sources, examining the actual data, reviewing software and all related documentation, and running the data through tools to discover data characteristics.
Next we identify and analyze of actual internal and outside data source content and processing to determine weaknesses and strengths. The results of this analysis are reviewed and a recommended solution is formulated. This solution is typically comprised of a data model, user scenarios, process, a technology architecture, measure, and control components. A strategy and plan to implement the solution is developed and presented to the client for approval.
Although our deliverables vary by engagement, in general we:
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Develop a Problem Definition and Impact Analysis Document
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Deliver Resolution Strategy and Related Implementation Plans
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Provide Status Reports and Deliverable Presentations
Advantageware gives its clients three options to implement the proposed solution.
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Advantageware can partner with the client and work with them on an "as-assigned" basis. The client would manage the project and Advantageware would supply resources on an as-assigned basis.
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Advantageware can also deliver the solution on a complete project basis. In this case, Advantageware would develop and install the proposed solution. Advantageware would also assist the client's staff to integrate the solution into their own environment and train the client's staff as required.
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The final alternative is having Advantageware deliver the solution on an "operational support" basis. In this case Advantageware would develop the necessary solution and deliver required information on a scheduled basis according to a mutually agreed to service level agreement.
How do we do this
Advantageware uses a structured work approach and solid project management practices which facilitate communication throughout the entire project effort. We also use various proprietary methodologies, techniques, and tools (MegaMorph) as we carefully work with our clients to define and document the exact data problem. These include process, function, data, and a definition of the client's business and technology environments.
Based upon the nature and scope of the problem, we present our findings and a proposed Resolution Strategy and associated tactical level work plans. These are reviewed with the client for concurrence and approval. Based upon the client's next-step decision, Advantageware can either correct and enhance the current operational systems and processes or build a customize solution using our own tools. We work closely with our clients to ensure that what we recommend and deliver actually solves the client's problem.
Success stories
Foreign Trade Reconciliation Processes
Participated in the examination and improvement of the reconciliation process for foreign trades. During an audit, balances of several major accounts were discovered to be inaccurate. Performed process and data flow analysis. Identified and analyzed all data associated with the processes. Identified the problems and created strategies and related plans to quickly correct the data and eliminate the problems. Help to define and implement audit measures and controls.
Bank's Customer Master File Integration
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Participated in the effort to produce a unified customer master file for use across several business units. This data quality effort required the definition and analysis of all the data used in 18 computer systems. Some of the issues that had to be resolved were the data quality , data definition in context of its timing in the targeted business processes, and data ownership. Identified business and technical issues. Developed a migration strategy and related plans. Supplied a "SWAT" team to perform the data clean up. Performed data verification activities. Developed the new master file meta data. Worked with the business unit Task Forces to help them identify what processes would be affected by these changes.
Property/Casualty Insurance Company Reserve Funding Audit
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Performed a Business/Data Analysis project effort to validate and improve the claims processing and reserve management processes and reporting. The company's Best rating had been downgraded. The project's goal was to provide the company's board of directors, the state insurance regulatory board, and auditors with a third party evaluation and improvement plan.
Telemarketing Center Service Level Performance Review
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Analyzed the performance data from 6 nationwide telemarketing centers. Helped uncover performance trends, areas of training, and inconsistency in reporting among the centers. Made recommendations for training and changes in scripts and organization structure. Built a performance data mart and related reporting tools.