Organizations are constantly seeking ways to improve their manufacturing operations. We have seen various quality systems implemented such as CMMI, Total Quality Management and ISO. We have seen methods to improve production like Just in Time, Lean,and Agile. And most recently, companies have been leveraging business intelligence (BI) systems to improve their operations and performance.
However, to improve your company’s overall efficiency, rather than looking at the next big program that hits the market, the answer to better gains might very well be to simply re-organize your existing BI system.
Time for Changes
While BI provides many benefits to the success of the organization, a remake of its infrastructure could substantially improve your company’s overall success. The key could lie in re-engineering your BI system through data warehouse automation (DWA) by transforming parallel data sources and various platforms, to one of a centralized, unified system. And, of course, it goes without saying, for those companies looking to deploy a BI program from the ground up, it would be ideal to do it right the first time with a centralized BI platform.
BI has proven to be a competitive advantage for many organizations focused on manufacturing as they look at data across the supply chain and within its many operations such as, inventory, finance, production, and other stakeholder groups. Companies can attest that BI can greatly help to increase corporate reporting and overall business performance for the short and long terms.
With that all being said, approximately 60% of users are using data from two or more different environments. Having reporting systems reside in various places within a company is very cumbersome and at times leads to flat-out inaccuracy. This could mean that a company and its users are storing data and information in various data warehouses, data marts, Excel spreadsheets, portals, databases, and other systems. These various sources often cause: inaccurate reporting, replication of information, incongruent goals, having components in existence that aren’t tied to the BI ecosystem, and increased maintenance and upgrade time and resources. Often times, the two or more reports do not coincide with each other, and this can lead to project owners arguing on behalf of the validity of their data source. With that in mind, it is virtually impossible to have a true version of the company’s performance when departments and functions can’t agree on what constitutes accurate information.
A company can build a more strategic BI system through data warehouse automation that will enable users to have a holistic view of the company, thereby helping users to take advantage of more accurate reporting and analytics. Here are a few considerations that organizations should consider regarding improving their BI system by going from parallel reporting to a more centralized, single view.
From Silos to Centralization
Many companies have various data stored within discrete departments and groups, using various technology programs, stored at different locations. Having local control might make the department head more comfortable, but it has many limitations and liabilities across the enterprise. BI consolidation enables a company to centralize all its data within a data warehouse and to have one organized BI platform for the company. Having a centralized BI system significantly helps an organization discover hidden business patterns and trends that individual systems often do not uncover.
True Reporting and Analytics
With a single, centralized data system in place, a company can also integrate data from all its various technology sources such as ERP, CRM, payroll and others. The full and complete view of the business as shown from analytics and generated reports, enables all staff members, from users to executive management, to have a much more accurate picture of how the organization is performing, and where it’s falling short with key performance indicators.
Single Version of the Truth
With multiple data systems, companies waste a lot of time trying to determine what the correct numbers are for its business. Manufacturing might issue a report on sales that doesn’t match up with the sales report the accounting department has issued. The centralized BI system removes this problem and allows the organization to have one single source for reporting and analytics that can be considered true and accurate. Rather than spending time on trying to determine which report is correct, staff can spend their time on analyzing the report and making more trustworthy decisions from the data.
Enterprise Productivity is Greatly Improved
Organizations that use analytics are more nimble, faster -- and can make clearer, more strategic decisions. Having better data quality as evidenced by the centralized reporting, enables the company to determine its strengths and weaknesses, and to identify trends to capitalize on opportunities, while avoiding potential risks. Companies can find the root causes of problems and take immediate corrective action, much faster than an organization with various, disparate data sources. In this case, potential pitfalls are often hidden behind the several layers of data systems and sources.
Considerations When Implementing A BI System
With the proper data warehouse tools, historical system or legacy system data can easily and quickly be integrated into the centralized data warehouse. These tools allow users to use drag and drop features to maintain the system, provide maintenance, and scale over time. Selecting the right tool can also help increase ease-of-use, empower end-users without technology support staff, and decrease downtime during implementation and maintenance.
In the end, organizations are constantly looking at ways to improve revenue and decrease costs. Technology and modern business practices play a significant role in helping to do so. This outcome of maximizing the bottom line is derived from better performance and stronger decision making. Business intelligence can be a main factor in helping to accomplish these objectives; especially, if it is implemented in a way that allows users to fully leverage its capability, and to see information that is often hidden due to the fragmentation and decentralization of its platform.
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