Data is a pivotal aspect of every modern manufacturing and distribution business. It helps inform decisions, indicate areas of success and failure, and create unique insights to improve and innovate. Yet the collection and use of data can quickly get messy. Without a means to extract, aggregate, and sort through your data, gleaning meaningful insight will become next to impossible.
So, how can you effectively manage your data? Many manufacturers, distributors, and supply chain organizations use data integration tools to gain meaningful insights from their ERPs.
What Is Data Integration and Why is it So Important?
Data integration is the process of unifying data from multiple (often disparate) sources, systems, and applications. Across an organization, integration is a vital step in keeping data consistent. By unifying data from previously disconnected or disparate sources, it allows an organization’s data to be effectively assessed and analyzed. In essence, data integration keeps your ERP connected, providing your organization with a robust and holistic view of your data.
Despite this, integration can pose problems for manufacturers and distributors. The most prominent issue? Manual data integration.
A recent study from Intowave [1] stated that around 74% of manufacturers are still relying on manual data integration techniques. This means using employees for data extraction, transformation, and aggregation to keep outdated systems operating. While manual integration can function, it is often at the expense of wild inefficiency. It drives up costs, takes copious amounts of time, and can damage the accuracy and reliability of data. As well, it often becomes a crutch to keep legacy ERPs connected and up to date.
Overall, manual data integration can become a major roadblock for any manufacturer or distributor looking to sustainably scale and improve. To combat this, many organizations turn to data integration tools to provide data automation capabilities. As an automation solution, using a data integration tool can be extremely effective in fixing the inefficiencies of manual data integration.
Top 3 Reasons You Should Adopt Data Integration Tools
A recent study from Fivetran concluded that companies spend an average of $520K per year on data engineers that manually build and maintain data pipelines [2]. As such, finding a way to automate the integration process can result in huge cost-benefits. With such a massive margin to save, you may consider some of the many benefits provided by data integration tools:
1. Improvement of Data Accuracy
Bad data, according to Christina R. Fritsch of The National Law Review [3], costs US companies upwards of 3 trillion dollars every year. This isn’t a number to take lightly. With modern business strategies putting huge reliance on data analysis, poor data management is a massive hindrance. Yet with data integration tools, you can significantly improve your organization’s data quality. For one, integration tools remove the potential for human error. Moreover, they can provide more reliable information on inventories, customers, sales, and other important metrics. With improved accuracy, you can put far more trust into your data, and in turn, your business decisions.
2. Superior Decision Making
From stronger data accuracy, intelligence, and accessibility, you can ensure more informed decisions within your organization. In addition, integration tools make the speed at which data can be accessed and analyzed significantly faster. According to Agility PR [4], around 9 out of 10 companies cannot conduct real-time analytics from their ERPs. This problem, however, is largely mitigated by effective automation with data integration tools. Automating integration tasks previously done manually, you can ensure much quicker data analysis capabilities, helping you make timely decisions. Thus, with faster, more informative, and more reliable data, you can ensure superior decision making.
3. Greater Efficiency and Productivity
Without data integration tools, companies spend around 44% of their time hiring engineers to build and maintain data pipelines [2]. Integration tools prevent this by eliminating costly errors and saving time, effort, and labor costs spent manually integrating data. Using data automation to perfect integration tasks previously executed by employees, integration tools improve the efficiency and productivity of your operation. More importantly, freeing employees from these manual tasks can be greatly proactive. Instead of wasting their talent, employees will be able to focus on scaling, improving, and innovating.
The #1 Data Integration and Warehousing Tool for Rocket U2 Back-Office Systems
When looking to implement ERP integration effectively, you should consider which tool works best for the job. Luckily, Kore Integrate is the perfect tool to integrate your disparate systems.
Kore Integrate is a data warehousing solution that will improve your data reporting, scalability, functionality, and speed. For those who use Rocket Software’s UniVerse and UniData MultiValue databases, Kore Integrate is the best in the industry. Kore’s data integration tool can also pull from ODBC-enabled data sources like SQL, Postgres, Oracle, etc. By connecting disparate sources, you can create a unified view of the important data within your organization, while reducing operational costs.
The Bottom Line for Supply Chain Organizations, Manufacturers and Distributors
As data becomes increasingly important for modern manufacturers and distributors, being able to manage your data effectively is vital. The bottom line is that data integration tools are a necessary step to modernize your organization’s data systems. Ultimately, integration tools like Kore Integrate will save you time, money, and resources to put toward proactive aspects of your business.
References:
[1] Intoware, I. (2022, July). Break Free From Disconnected Data – Process & Control July Issue 2022.
https://www.intoware.com/resources/break-free-from-disconnected-data
[2] Fivetran (2021) Wakefield Research Analysis of Results for Fivetran. Fivetran https://get.fivetran.com/rs/353-UTB-444/images/2021-CDL-Wakefield-Research.pdf
[3] Fritsch, C. R. (2022, December 23). 12 days of CRM: Day 9 – how much does bad data actually cost?. The National Law Review. https://natlawreview.com/article/12-days-crm-day-9-how-much-does-bad-data-actually-cost
[4] Carufel, R. (2022, May 19). Data Disconnect: Over 80 percent of companies rely on stale data for decision-making. Agility PR Solutions.https://www.agilitypr.com/pr-news/public-relations/data-disconnect-over-80-percent-of-companies-rely-on-stale-data-for-decision-making/
