Master data management is on the rise across the globe as businesses are increasingly experiencing troubles with their enormous databases set to grow in the future. Hopefully, you will choose to govern your data with Synopps, but even if it’s not so, we’d be glad to share our views on why MDM is now badly needed and why more organizations opt to pour resources into it.
Digitalization As Biggest Driver For Change
For years, master data management had not been a top priority for corporations. Senior management tended to think that it’s a purely technical thing that lies in an area of competence of an IT department. Other staff should just follow instructions issued by the IT unit. Note we describe a company where a master data strategy existed, while in most entities it was not even considered with data flows left to ride.
Things have changed a bit more than 10 years ago, the time when Marc Andreessen, the co-founder of the venture capital company Andreessen Horowitz, published his milestone op-ed article “Why Software Is Eating The World” in the Wall Street Journal. “Software first” is a synopsis of the article. The success of any business with rare exceptions strongly depends on how a company implements hi-tech achievements.
A lot of software products lead to a lot of data. Inflows of records, the exponential growth of bytes and kilobytes, started to turn into a problem. The problem was worsened by a variety of formats, not always compatible with each other, that have emerged and developed over years.
An increasing amount of master data is being translated into an increasing rate of chaos caused by the lack of order or flaws in corporate data architecture. So taking to master data management became a necessity, not just an ordinary thing from a management textbook. MDM also went beyond the IT department’s walls and walked into senior management’s rooms.
Cost-Cut Solutions: Wanted
Prices for everything are rising everywhere as if inviting a recession to come and stay even in developed countries. Headlines of mass media are calling for governments to act. But businesses need to act too and need to do it fast. Companies are forced to optimize costs in order to stay afloat or keep returns on investments for their shareholders.
Master data management lays the ground for a savings plan. A well-architectured data system allows for an efficient track of purchases, suppliers, and inventories resulting in a good understanding of which expenses can be reduced or optimized.
ESG: How Master Data Management Can Help
Environmental, Social, and Governance (ESG) is a trend that nearly all global corporations follow. The acronym put on brands and included in corporate slogans says that an organization clings to socially responsible business and pushes for sustainability.
But the slogans and touting corporate values must be confirmed by practices, at least those reflected in reports. The minimum demand for such reports that are meant to be trusted by the public is the absence of internal contradictions or contradictions with government watchdogs’ data. Contradictions that can cause public scandals and damage reputation usually arise due to different data contained in the company’s different departments. While a financial unit reports some figures, a production unit may give other figures. Inconsistency can be noted and trumpeted by the media or the company’s opponents.
Master data management ensures that data is reliable, updated, consistent, and sufficient.
Pressure from society and governments is getting stronger over various issues, first of all, human rights, equal rights, and protection of the environment. Scrutiny is set to increase so the quality of the company’s reports – based on corporate data — will be playing the first fiddle to reputation.
Advanced Technologies: MDM Is Necessary
Highly advanced technologies that emerged in recent years are the best proof of Andreessen’s statements. Since 2011 when the article was published artificial intelligence (AI), machine learning, and big data science have been gaining traction. They are forming the shape of modern automation, a trend that has been accelerating due to a variety of reasons, including the enhancement of the speed of operations, the quality of services, and cost reduction.
Data is what all these technologies consume to yield results. Be it machine learning or big data, you need refined, clean, high-quality accurate data in order to get the right results from the new methods.
For example, a machine learning approach is based on the evaluations of the result a machine gets, correction of algorithms based on these evaluations, then giving new — adjusted — results, and a further correction if needed. This cycle repeats until the needed result is achieved. As you can easily see, the wrong data will lead to the wrong result from the start, and machine learning capabilities will be wasted. No MDM — no advantage of what modern software can offer to businesses to earn more money or save on purchases.
Visit Synopps’s blog to get more insights into the best practices of master data management.