Improving ERP Data With Data Science
Tags: Data Analytics, Erp Solutions, Data Visualization, Erp, Data Science

Enterprise resource planning (ERP) data helps companies manage their day-to-day operations with help from specialized platforms that compile information from multiple streams and allow companies to get real-time feedback for better decision-making.

Businesses can enhance their ERP usage by hiring data scientists who understand how to make sense of the information from an ERP interface and use it to drive profitable actions.

Enabling Better Demand Forecasting

Data scientists have a thorough understanding of how to identify patterns within historical data. Considering that ERP platforms typically contain information about sales fluctuations over time, data scientists can dig deeper to find the trends that could help companies determine how soon to order more products and which items customers will want most.

The data scientists hired by a company can assess yearly, monthly and weekly seasonality factors and give guidance to business leaders about keeping products in stock that range from sunscreen to snow shovels. Plus, it’s important to remember some of the other things that could influence customer demand.

If a celebrity carries a widely available purse while strolling down the red carpet at an awards show, that visibility could make consumers want to buy it. Or, if a respected thought leader posts a tweet about a product, that mention could spur desirability, too. ERP software provides the hard data that companies need, and it’s data scientists who help connect the dots by determining both the obvious and less evident factors that make people want products.

It’s easy to see the benefits of this in the retail world, but the advantages expand to manufacturing and customer service, too. For example, increased demand for a consumable item containing a difficult-to-acquire ingredient might cause a company or its supply chain partners to expand their network to source the item or look for alternative ways to formulate the product.

Or, a rapid uptick in the number of people buying a newly released smartphone may require a brand’s customer support team members to go through additional training before handling the barrage of questions about that tech item. Once businesses rely on data scientists to better understand demand-related patterns, they should be better equipped to anticipate and cater to ever-changing requirements.

Helping Companies Feel More Confident About Solving Problems

Business leaders frequently encounter situations that require them to assess the options and make the most appropriate choice for a given scenario. That often starts when company representatives select ERP software. For example, they evaluate whether an on-site or cloud-based ERP solution is better, then conclude that the answer depends on the enterprise’s needs.

The previous section discussed how predicting future needs with help from data scientists could help businesses succeed. Companies can also excel if they rely on data scientists to assist in the area of prescriptive analytics — or figuring out the best approach to take when tackling a known problem. That’s because getting the necessary insights to proceed with prescriptive analytics requires focusing on data quantity and quality.

Fortunately for companies already using ERP software, most or all of the data they need will be within that platform. However, data scientists come into the picture by assessing the data to ensure it’s free from errors or duplicate records that could skew the results if not removed from the database before analysis begins.

KPMG carried out a CEO survey and found that 67% of respondents did not trust the conclusions drawn from data analysis or computer-driven models in the last several years. They said they failed to act on what the data indicated because it contradicted their intuition or experience. Leaders could feel even more doubtful if they suspect the database contains mistakes that could lead to improper conclusions.

Letting data scientists carefully prepare the data before scrutinizing it is not a guaranteed fix for company leadership’s lack of confidence in the available information. But data professionals clean the data to reduce inaccurate results. That means company executives could more authoritatively act on information in an ERP if data scientists handle it first and check for problems and usefulness.

Assisting in Compiling Data From Multiple ERP Tools

Working with company data from ERP interfaces gets exceptionally complicated when a multinational company reaches the point of using multiple ERP systems around the world and needs to combine the information into a single platform. Such was the case with Anheuser-Busch InBev, the world’s biggest name in beer.

The brand formerly used nearly 30 individual ERP platforms across its global subsidiaries but is now in the process of transitioning to a single standardized system that will primarily function in the cloud within the next five years or less. In the last year and a half, the brand’s team of 80 engineers took part in 30 data projects, all of which factor into the company’s digital transformation.

When companies are in similar situations where they want to begin using one ERP solution instead of dozens or more, data scientists can ease what could otherwise be a tricky transition.

However, since analysts predict the demand for data scientists to increase, company leaders should not delay in making their hiring decisions and offering attractive employment packages to candidates.

Data Scientists and ERP Tools: A Practical Pairing

This overview emphasizes how the expertise of data scientists can improve how companies use their ERPs. Moreover, it shows why company leaders increasingly see bringing data scientists onto their teams as a smart investment.