During this past decade, engineers made real progress toward revolutionizing the automobile driveline from an internal combustion engine to an electric direct drive. Even today, the internal combustion engine continued improving through a progression of enhancements and refinements that included both mechanical and electronic modifications. Much like the history of the internal combustion engine, the brief history of cell phones, tablets and laptops has not changed much from accepted shape or purpose in recent years. However, these items experienced a technological revolution that continues to march forward based on changes occurring inside the devices.
From using individually installed software to a fully connected app/site ecosystem on every device fine-tuned for a specific designated purpose, these advancements created a wonderful time to be alive. Just think, an entire generation of young people exists who have not known a world prior to the internet, GPS location and instant messaging enhancements all delivered through a portable device.
With all the apps and sites that users engage in, individuals and businesses, in general, are most likely overwhelmed. The challenge within each organization remains to create a greater understanding of using these interconnected technologies and the role and purpose each performs in an organization’s roles and responsibilities. Due to this, data visibility plays an emerging and particularly key role in communicating the importance of integrated software. Data visibility, for all intents and purposes, is the ease through which an enterprise can monitor, display, and analyze data from disparate sources. The key word is disparate as now companies can engineer, maintain and manage one source of data across multiple systems whether inside an ERP, OMS, TMS, WMS or other software platform used to execute daily responsibilities.
When creating a viable data source, the integrity of the data source and the quality of the data are key priorities to ensure trust in the data illustrated and managed within the organization. The temporal aspect of the data is critical to generate acceptance across the organization, suppliers and customers. If the data is out of alignment, multiple issues may arise in all areas of reporting and potentially have business resources making poor decisions that are not relevant to the business. Overcoming this means creating quality control checks and audits, establishing proper baselines, and tracking changes over time.
The display of the data is just as important; however, a balance exists for the end consumer. Keeping the data at a summary level may not support user acceptance in trusting what users see displayed. In order to support trust, engineering the capability for a deep drill down into the data is a valuable trait when looking to build user acceptance, conversely, too much granularity in the display may lead to “paralysis by analysis” for the users. However, when users properly understand the requirements of representing the data to the organization, the journey to greater data visibility within the organization has wide-ranging and positive implications. The top stated benefits are:
The final, critical component of data visibility is analysis. A company may have all the data in the world, have the data accurate due to monitoring, and display the data in an acceptable manner; however, a massive opportunity may elude the business without proper interpretation of the illustrated data. Data analytics takes on many forms within an organization. One form, data mining, is a process of taking large amounts of data, identifying outliers, and excluding these outliers from moving forward to a decision-making step. The main goal of this process is to turn the data into actionable intelligence that enables positive business decisions.
Another form, business intelligence, takes a step forward and moves towards driving business decisions based on sound data. This is where the organization transforms data into intelligence to use to make business decisions. An organization may use this intelligence in strategic or tactical decision-making. Essentially, intelligence offers a way for companies to examine trends from collected data, obtain actionable insights, and make informed decisions.
In the industry of logistics, these steps are crucial in the data visibility practice to the point of not stating data visibility as a conditional attribute of the business but as a necessity to maintain relevancy in the market. Starting upstream for staffing purposes, if visibility does not exist on inbound and outbound shipments, management teams may not know how to staff a warehouse properly during the week due to unknown volumes. This may then affect the manufacturing line if the parts are not present. Continuing downstream, if the business does not have visibility to shipments in transit, this impacts customers by losing the capability to set customer expectations, or better yet, communicate the narrative before the narrative is known. The “Amazon Effect” of delivery notifications and tracking is an example of data visibility that all consumers expect as the status quo.
Furthermore, just like any other industry, data visibility plays an important part in the security practices of a company. Without knowledge of where the data sits or how the data is managed, leaves companies are susceptible to attacks. Proper data visibility allows companies to ensure a well-fortified environment, not just from cyber security attacks, but also from unethical business practices taking place.
If this is your first blog reading about data visibility, my bet is that it may not be your last. Data visibility is part of the current step in the technological revolution and will continue to become a more prevalent and long-standing piece as we continue on this exciting journey of technological advancement.
For more information please reach out to our team, today.
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