“Without data, you’re just another
person with an opinion.”
- W. Edwards Deming
This quote by American engineer and statistician W. Edwards Deming is memorable because it’s true. Without the evidence of data, how can you justify your business decisions?
Deming believed in the importance of data—especially data that helps reveal or improve the quality of a business’s products, processes, services, and management. He’s respected today as the father of quality control.
Sourcing data relevant to your business goals gives you the raw materials for useful information. Analyzing that information to detect trends, anomalies, and insights can then help you create business intelligence for better decision-making. Deming foresaw this truth over 60 years ago.
Today, with our abundance of innovative technologies, cloud systems, and APIs, the right data integration can deliver the data to implement and apply Deming’s dreams of quality.
But what happens when your purpose or business goals change? Does that mean you should change your integration solution, too?
Suppose, for example, you want to offer new products, pursue innovations, or use cloud systems and apps. Those choices may require an entirely different approach to your data and how you connect your computing processing systems.
There are many circumstances in which you’d need to rethink or adjust your data integration solution. Here are just a few to consider.
If you’ve grown in size from a small firm to a larger organization, chances are you need to either update your current integrations, integrate old systems with new ones, or adopt a more efficient and scalable solution.
Merging organizations must develop efficient, repeatable processes that embrace the methods and technologies of each firm. An integration and optimization approach will avoid inefficiencies and frustrations.
If you operated in a bricks-and-mortar venue but had to adapt your entire business to online e-commerce just to survive during the pandemic, you embraced new data connectivity needs that required robust integration. You may even adopt cloud-native platforms that use distributed computing, a major tech trend according to Gartner.
Many firms are busy transitioning to modern technologies. Data integration can actively aid the transition. For instance, you can integrate legacy systems into a hybrid system that also enables new cloud technologies.
Data integration is a prerequisite for these functions. Data integration is ideal for empowering analytical use cases and is the anchor for any analytics strategy.
With so many people using apps for business, a lot of data is moving back and forth between individual applications to keep them in sync.
Application integration (distinct from data integration) is good for running operational use cases.
Also, if you find your employees use lots of disconnected apps, it may be time to rethink an integration governance policy.
More than ever, firms realize that collaboration between skilled employees and among cross-disciplinary teams drives better engagement, ideas, and innovation.
Data integration enables the use of many helpful tools and platforms for enhanced collaboration. It can provide a self-service solution to access data stored across disparate systems.
With unified data access, professionals can collaborate better, brainstorm, and achieve results faster.
Many organizations need to make decisions quickly based on the most recent information available. They need streaming data generated by many data sources, often simultaneously.
That will require stream data integration, which ingests event data from many sources to improve customer experience, minimize fraud, and optimize operations and resource use.
Integration underpins context-enriched services that can capture and analyze online customer behavioral data, fueling features for creating individualized customer experiences. This is popular in retail, where it helps drive sales conversions while creating more satisfied, loyal customers.
If you have new or changed business goals, you may wonder if you need an entirely new integration approach. To answer that, start by asking yourself some or all of these questions.
Let’s return to Edwards Deming, whose quote we began with.
Deming, educated in mathematical physics, is best known for his scientific business management methods that helped Japan recover after World War Two. He applied statistical process control methods to improve many business and management operations. His approach also improved the design of many products and services.
He was a man who believed in fixing things.
His methods helped the Japanese auto industry rise to a position of manufacturing excellence and global market penetration from the 1950s onwards.
So, what does Deming have to do with data integration?
In a word, data. Over a half-century ago, he saw the value of applying data to help measure, inform and improve many systems, processes, and products.
Deming wasn’t just a data-obsessed analyst, however. He also cared a great deal about the needs of employees. Deming was a passionate believer in breaking down the barriers that divided departments and eliminating fear in the workplace.
He also believed regular on-the-job training, education, and self-improvement were essential supports to help managers and workers thrive and excel.
Above all, Deming believed in a philosophy of continual improvement—for people and for organizations.
Deming died in 1993 at 93. But his ideas live on, and today, technologies and tools for data integration are helping to advance his vision for
Even if you may need to reconsider your integration solution due to changing circumstances, the core value of data integration is vital.
Data integration not only drives efficiency, but also breaks down organizational silos, and helps people discover new ways to connect and collaborate. It also helps enable people to be more innovative—all goals Deming would have loved.
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