#masterdata

MDM implementation requires a clear strategy

Digital transformation has forced management to rethink current business models to accelerate the digitalization process and update analytics tools. However, this process is not fast.

Now, data collection and management are a usual business practice. Despite this, there is a high probability that the data is scattered, fragmented, and uncleaned. Inaccurate data and flawed data management can play against business and hinder effective decision making and development. Therefore, this leads the company to poor performance indicators.

Master data management (MDM) plays an important role in enabling intelligent business processes (providing datasets with the correct structure, hierarchy and management). MDM manages critical data across multiple sources, channels, and departments. Master data management implementation requires a well-defined strategy. Let’s look at several important steps in developing a successful master data management strategy.

  1. MDM clear objectives setting

The master data vision must be consistent with the whole business vision. This contributes to the success factors identification and objectives achievement in functional, technical and financial terms. First, the MDM economic model should answer the questions “Why?”, “How?”, “Who?”. This will help identify business pains and data problems. Solving these problems at early stages ensures all business stakeholders support and approval.

  1. Focus on a holistic approach to master data management

Using a multiphase approach to an MDM strategy can be more effective by working with a minimal set of phase objects and scaling it into the next phase. Ignoring such a detailed model when building an MDM solution further can lead to the master data creation from isolated and disparate sources.

  1. Determining the most relevant implementation style in accordance with the existing IT architecture

Companies should clearly define their target architecture, existing technologies, and select a system integrator. Effective MDM technology must support real-time analytics and operational processes to align with the overall the organization’s IT architecture and ecosystem.

  1. Data management rules defining

Business owners need to manage data across all processes and departments. The effective master data management process should identify, measure, record and correct data quality problems in the source system. A formal data governance model should include detailed business rules, governance mechanisms, controls, and data compliance.

  1. Implementation with a strategic plan

The strategic plan can demonstrate the steps implementation in accordance with the business objectives. This prevents MDM solutions from failing as a result of structural flaws that damage the entire data system.

  1. Stagewise ROI verification

First, it is necessary to determine the parameters and indicators that determine the data management success throughout the entire life cycle. MDM stakeholders can be from different organization parts and have different goals. In that situation, it makes sense to check ROI in stages. For example, when custom domain is implemented into a strategy, you need to check your ROI in terms of increasing cross-selling, sales, etc.

  1. Tracking results after implementation

The MDM strategy requires analysis before implementation and monitoring afterwards. All employees, company’s management and stakeholders must work together to achieve their business goals.

  1. Regular improvement

All company staff must be trained in how to format, enter, store and access data. Regularly checking configuration, installation, data models, data management tools, hierarchy helps to avoid problems.

Master data: Compliance and Collaboration

Continuing to get acquainted with the «6C» conception, today we will consider 2 elements: compliance and collaboration.

Currently every industry has special regulations and restrictions according to which companies must operate.

For example,

In the process of data ecosystem studying, it is necessary to understand what information you need to provide the compliance with the requirements. A clear understanding what data you have, how it is collected and processed gives an ability to improve data management system.

Moreover, it is critically important to identify all lags in master data management system. An effective decision is to make complex examination and analysis of the next business processes:

A proper analysis gives a possibility to identify all system weaknesses and create an effective corrective actions strategy. Also, an essence understanding of all 6 conception elements provide an ability to easily evaluate a present data management system state, define merits and demerits, define goals and tasks of the business. After such analysis it makes sense to address to the responsible partner, who has decades of MDM experience and understands how to rectify deficiencies and achieve the best result.

Previous #fridaypost “Business in clouds”

Business in clouds

In the previous chapters 3 elements of the «6C» conception were brought to the  light – complexity, commitment, culture. The next conception element is a cloud.

Cloud technologies appearing have influenced business strongly. Small, medium and big business use cloud actively for data storage and processing. Different organizations transfer to the cloud their accountancy, mail, data exchange applications, organize virtual offices and contact center. Cloud technologies practice in the operational business activity, particularly in master data management promotes adding flexibility and scalability, and reduction in expenditure. But it should be kept in mind that all cloud decisions have to be aligned with master data management (MDM).

To get all benefits from cloud business transfer it is necessary to develop proper strategy. Liability for the strategy development shall be borne by company’s management and professional outsourcer. In addition to being fast, flexible and safety, the cloud deployment process should also include:

Previous #fridaypost “Corporate culture as one of the key elements of business success ” 

Corporate culture as one of the key elements of business success

This post is related to the third «C» of master data enlightenment – culture. It may seem surprise, but company culture plays a key role in the process of master data enlightenment. Moreover, it can compete with technologies and processes.

No culture – no company! 

With any confidence everyone used different companies’ services and noted discrepancies in service, rules, staff behavior, different «life hack» etc. All discrepancies are a company culture product. Company culture is an individual complex of behavioral models that identify company rules, work algorithms, hierarchy, leader system, distributions of roles, communicative and interaction system, traditions, philosophy, foundations and policy.

Company culture affects whole business and serves different functions from image-building, motivational, adaptive to managemental and systemic. New process implementation into operational business activity, its preliminary preparation, passing and success are determined by the corporate culture. It also affects the process of master data enlightenment and DataLabs team can help to realize it. For sure such companies are the key participant of process realization, but management don’t need to shift all responsibilities to them. Their task is limited to technical organization and process support.

No one outsourcer can know business requirements, set goals and organize processes inside company. This is the responsibility of company’s management who owns processing information, knows what data is available now and what data is missed. The first management task is to identify goals and link together all information for strategy discussion and development with outsourcer. Moreover, the corporate culture changing or improving including necessary departments and teams creation, leaders and competent persons assignment, remains management task.

Effective process of master data enlightenment is a subject of new participants involvement:

A smoothly running mechanism of the corporate culture including a communication process between participants inside company, roles and task distribution, promote the effective master data enlightenment process.

Previous #fridaypost “Master data: take responsibility”

Master data: take responsibility

Let’s continue to elaborate on «6C» concept of the product master data enlightenment and today we’ll distinguish the second element – commitment. It means that every organization has to take over the responsibility for management, collecting and storage of truth data. The right approach to master data management provides with effective operational activity.

Let’s provide insight into why it is important to fix attention on product master data.

Product master data – this is the company, specifically:

Master data has impact on follow processes:

1. supply chain processes:

2. operational activity:

Besides high data value for a specific company it promotes the development and new ideas. Consequently, the winners are both sides. Such situation could be explained by the active evolution of cloud, mobile, analytics and IoT decisions that promote appearing of huge amount of important, but sparse data. Therefore, it motivates IT-companies, in particular DataLabs to create unique capabilities for challenges solving uncovering and expanding data value for business. DataLabs specialists will help to effectively organize the master data manage process including extracting, analysis, visualization, accessibility. It allows to solve important product tasks like scope of supply, sales geography, demand and supply information, expense tracking etc. The right approach and attitude to master data allows to arrange the efficient company activity and improve the operational performance.

Previous #fridaypost “Master data: the first step for enlightenment” 

Master data: the main business weapon

The technologic advance gave enterprises a possibility to implement more different information systems into operational activity (staff management, customer service, accounting, logistics etc.). All too often these systems are in a parallel progress, and to satisfy request of an aggregate picture is not possible. It is explained by the fact that data amount achieves the highest point and it is not possible to put together and compare it in manual way. Using of ineffective and irrelevant data management has risks to make wrong decisions and mistakes. However, there is a proven method to solve this task – master data management.

What is master data management?

Master data (the main data) – is the key company data and used to make business decisions as a foundation. Such data group includes information about customers, products, services, stockhouses, staff, materials, technologies etc. The master data changes rarely, and it is non-transactional data – this is the specific feature.

Master Data Management (MDM) is the key tool for correct and critically important information delivering. MDM has the form of the tools, processes and systems mix to organize a continuous key data control. This process is used to manage, centralize, organize, categorize, synchronize and renew the main data. Effective master data management in the central repository creates a distinct situation vision and removes «too expansive» inefficiency as a result of disembodied data.

Every team member (should it be a high-level executive or a member of different departments like marketing, logistics, export etc.) counts on getting exact product information to make decisions in their daily work.

The importance of exact information reception doesn’t stir up a dispute. Nevertheless, many companies practice a systemless style of the intellectual property management. Organizations often needs key product data, and it is a defect of their business model. This situation could be characterized by overstock, late market entry, high costs, incorrect forecasts.

There is no the one magic way to match data with business needs and strategy. As opposite to solve this fundamental task companies spend their resources to remedy effects and it is completely wrong.

In this case let’s consider «6 C» concept – the first step to master data enlightment:

Next #fridaypost will consider each of these elements in detail.
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