Why MDM Holds the Key to the Automation of Business Processes

Timo Seppänen
Ineo Oy

Nowadays information management is an integral part of companies and organizations where work is channeled through systems and data networks. However, in most organizations, data plays a minor role and its potential to automate business processes is not yet fully understood.

Many companies have a customer database that can be used to collect basic customer information for use in areas such as invoicing. The database makes billing slightly faster, but often functions independently and does not connect up with the general corporate information management systems. Management cannot say, for instance, how useful it is to maintain the database, nor does it have the tools with which to develop it.

“Companies have a great desire to develop their business models, but this often proves difficult without the required information to validate the redesign. The relationship between the development of business models and information management is symbiotic. On their own, neither is sufficient if the objective is to create competitive business,” tells Timo Seppänen, CEO of Ineo.

When information management is at the core of business operations and encompasses all data within an organisation, the decision makers receive information about the effectiveness of the processes and the management can develop the business models.

“In assembly line factories, concrete work stages have for decades been increasingly automated. New innovations in the assembly line make manufacturing more efficient and provide competitive advantage. At the same time in the office resources can be wasted by using inefficient billing and order-delivery systems. What I want to highlight with this point is that, just like an assembly line, information management can be more efficient. Herein lies huge potential for creating a new competitive edge for the company.

Copying Best Practices

How can information management make business processes more efficient? The key term is best practices or the model of performance that will produce the optimal outcome, both from customer’s as well as the company’s point of view. When the company starts to replicate only the best practices in its business activities, processes become homogenous, faster and more profitable.

If processes are not modeled, each worker applies his/her personal best understanding to create a new practice. Resources are wasted to repeat the same practice and the same basic data is continuously used to create new, unequal variances. Information becomes open to interpretation, which brings confusion to the process chain and leaves room for misunderstanding.

“Poorly processed systems are used like typewriters. Every employee can generate a differently composed invoice to the same customer with varying customer data, payment terms and other details,” explains Seppänen.

“Where as in information management, which relies on best practices, there exists only one basic pro forma set of customer data. The accounting and control data is defined for the same customer, which for example always provide the same payment terms. When the billing team is guided only by the models of best practice, the outcome is qualified and predictable. Time is saved and there is no room for interpretation. At the same time commensurate data is generated, which leads to versatile BI reports for management. This increases functional capital.”

MDM is the Basis for Information Management

It is practically impossible to establish well-functioning information management without a qualified MDM solution, which encompasses the whole IT infrastructure. In Ineo’s solution, the centre is an MDM-star, where all master data is centrally stored and distributed commensurably to different systems. When master data goes through MDM, the result is scalable and unified information management, which measures the effectiveness of the processes.

The management of master data can be divided into three parts: accounting master data, reference information and configuration data of processes.

  1. Accounting master data

– Form the basis for the management system

– E.g. accounts, customer classifications, payment terms

  1. Reference information

– Form the connection of business to working environment

– E.g. customers, suppliers and headings

  1. Configuration data of processes

– Form guides, contracts, best business practices

– E.g. Contracts, price lists and manufacturing planning data

Information management in the best practices model is a step towards proactive management. Master data management organizes and creates meaning for data groups. Master data management that connects different systems becomes an organizational organ measuring the process effectiveness and modeling best practices for the business.

“In a well-processed task, humans can do 10% of the work, for example, whilst the system takes care of the remaining 90%. Repeating best practices is made easy and effortless for the worker, where as deviation from the controlled performance is made more challenging.”

Financial Impact for the Company

Master data management, which relies on best practices, increases competitiveness. When processes reap the maximum benefit from automation, human resources are directed towards value-driven work.

“In some industries the margin is so small that even the smallest deviation from best practice makes the whole supply chain unprofitable. The guidance for repeating best practices must therefore work so well that employees and also customers make minimal deviations from the effective process.”

At its best MDM generates information that is not otherwise available to the corporate decision makers. The better the automation works, the more foreseeable the business becomes. When making business more transparent, goal setting can be more detailed. Real-time reports provide instant information on which processes are inefficient and need more resource planning.

“Again we are talking about inheritance and enriching informational assets. When we have experience of processes conducted in the same way as well as exact statistics for long-term data, we can steer the company toward new directions. Predictions for the future become accurate.”