Master Data Management: Why You're Doing It Wrong and How to Fix It

MASTER DATAMANAGEMENTWHY YOU'RE DOING IT WRONG AND HOW TO FIX IT © Spend Matters. All rights reserved. 1Master Data ManagementWhy You're Doing It Wrong and How to Fix ItThis content was originally published on Spend Matters. It has been reprinted with permission. More than 2.5 quintillion bytes of data is generated worldwide every day and that number is set to grow rapidly, according to business intelligence provider Domo. The impending increase in data traffic will come from mobile and cloud computing sources, and from developments in AI, IOT and machine learning. Insightful business decisions derived from big data can provide organisations with a 23x uplift in customer acquisition compared to those contemporaries who do not use complex data sets. In fact, companies making insight-led business decisions from intelligent data are predicted to take $1.8 trillion annually from competitors who lack data-driven capabilities. It’s not surprising that businesses were estimated to spend $187 billion on big data and analytics in 2019 alone, finds Leftronic.Of course, data comes in many forms and from many sources, how you use it as an organisation depends on your department and your business goals. What is certain is that the movement toward SOA and SaaS is making master data management (MDM) a critical issue. It’s also irrefutable that the data must be clean and correct from the outset in order to perform relevant and purposeful analysis. So, it’s imperative that firms build strong master data management practices into their data strategies to move forward with data analysis primed for meaningful results. Alongside customer master data, supplier (aka vendor) master data is one of the biggest areas where procurement departments will find the most opportunity for insight-driven strategy and decision making. But there are challenges associated with how master data can be managed for it to accurately feed the data analysis machine. Part of the problemMany firms are moving onto their next stage of digital transformation, but are grappling with supplier data buried in multiple system infrastructures. HR, marketing, logistics, finance, IT -- they all may be using their own versions of supplier data and maintaining individual records. In effect, they are all keeping their own version of the truth and using a narrow, departmental view as the basis for decisions. The anomalies can stack up, especially if this scenario spans different locations, countries or entire regions. Errors and gaps in information are often duplicated across organisations which is further exacerbated when multiple ERP systems exist. What should be a shared or common asset within an entire organisation is instead a source of inaccurate or obscured output. Master data ought to be accurate and provide useful results in spend analytics, sourcing optimisation and centralised contract management. © Spend Matters. All rights reserved. 2The fact is you can make use of the most recent AI or algorithm-based developments, but you will not reap the true benefits they can offer unless the core data on which they depend is complete, correct and rationalised. If the judgements you make as a business are based on inaccurate, out-of-date or false information, then you are creating more risk in your decisions by not having the full picture of the truth.Risk is what you get when you make the wrong business decisions. So how do you make the right ones? How do we trust our core data so that we can take it into a meaningful business context?Trusting your master data means moving beyond ERP ...Data has long been the bane of procurement organisations. Where do you keep your master data? Who is responsible for it? Which master data can you trust? How do you know if your forecasts, what-if scenarios, supplier measurements and spend analyses are correct when you submit them to your board? Many organisations have struggled to get full value out of their spend analytics or optimisation investments because of lack of high-quality, granular data. Firms have embraced 25 years of ERP systems to help them manage their internal operations, but now our third-party relationships, including supplier management and contract management, need nurturing. If we are to fulfil today’s demands for CSR, sustainability and social impact while building balanced and trusted relationships with our supplier ecosystems, we need systems that are fit-for-purpose. But in today’s landscape of often globally segregated ERP systems, bolt-on tools, hybrid collections of solutions, there is no one full picture or validation of data. So, for trustworthy supplier master data, we are starting to look beyond our ERP system towards AI-powered solutions that are more fully equipped and better designed to do that job. ... to a single source of truth Tools that help us to master MDM are becoming more sophisticated, faster and rich in capabilities. There are now unified platforms using