Data is the oil standard for businesses today and has proved the fastest-growing trend in the global economy. There are many articles, reports and books which showcase the benefits enjoyed by data-driven organisations. Common threads amongst these discussions focus on customer acquisition, retention and long-term profitability.
So, how can the Manufacturing industry use visual analytics to evolve? Read on.
What is Visual Analytics?
Visual analytics is a broad term that refers to using interactive graphical interfaces to support analytical insight. This data strategy improves data analysis by employing sophisticated technologies and procedures (such as data source integration software, data visualisation tools, dashboards, and collaboration tools) to generate visual representations of information. By visualising the data using graphs, charts, and maps, users can discover patterns and draw actionable insights to effectively facilitate high-level, complex activities, such as reasoning and data-driven decision making.
The need for visualisation in manufacturing
There has been a significant uptake of visual analytics in manufacturing because companies in this sector generate vast amounts of data. The volume of data makes it challenging for executives to understand how equipment, processes, and materials operate. It requires them to sort through large amounts of raw data to identify potential issues which affect their company’s bottom line. Visual analytics allows users to sift through data more quickly, speeding up the identification of problems and opportunities in their manufacturing processes. Some key benefits of this include:
- Improved data exploration and data analysis, and reduced cost
- Consumption of more data in less time
- Earlier detection of trends, outliers, and correlations, which may provide a competitive edge
- Instant feedback and real time updates, keeping data relevant and accurate
Unlocking the value of manufacturing and consumer goods data with visual analytics
Visual analytics in manufacturing allows users to assess risk areas, spot errors in processes, track the status of supplies and materials, and determine where organisations can improve efficiency.
Billions of rows of data are available to businesses daily, coming into a business at different speeds, sizes, types and methods (see four v’s of big data) making it a struggle for many to manage the complexity of the available data. All employees must be able to access this data to do their jobs effectively and bolster organisational efficiency. However, to make the insights within a company’s data accessible to every level of the organisation, companies need to unlock it so that everyone can understand what’s going on.
To unlock a company’s data and allow visual analytics to make data more human-centric, companies need to take these key steps:
Step 1: Be data-driven first—with executive buy-in
Emphasise the implementation of data analysis initiatives. This entails creating a data culture where employees across and throughout departments are empowered to make decisions that serve the organisation’s goals. It will allow users throughout an organisation to access relevant information within their respective fields of business while providing executives with the information they need to make business-critical decisions.
Step 2: Decide on an implementation plan
Organisations need to be systematic and stick with the process through the entire development lifecycle to be successful. This requires examining the challenges and opportunities of data management, identifying data management capabilities and implementing the appropriate approach.
Once an organisation has decided on a data visualisation tool, it’s crucial to deploy the analytics solution in-line with best practices and ensure that users are expertly trained to maximise potential value. Implementation, training and optimisation require significant investments in time and resources. However, user training is a crucial part of the process since it can help generate better insights from visualised data.
Step 3: Find opportunities to streamline
Focus on the top metrics that everyone in the company needs to monitor and improve and how visual analytics can support these metrics. Success stems from the collaboration between all departments in an organisation, so business leaders need to define the right metrics that can make a real impact on company performance.
Step 4: Think big
Organisations need to identify business problems, then design and implement a visual analysis of the data as the first step so all employees can quickly help to find a solution. By merging data silos with this strategy, companies can integrate real-time production data with historical data, apply complex analytics, and measure the entire production process end-to-end to uncover necessary improvements.
What are the benefits of using visual analytics in manufacturing?
The benefits of visual analytics in manufacturing include unlocking the value in data by revealing patterns, trends, and other significant information that may be difficult for users to identify otherwise. Data visualisation makes big data more accessible for manufacturers because it simplifies the information for users to understand what is happening in their operations more quickly.
Powering Better Product Design
Manufacturers can now test designs for efficiency and ergonomics without ever making a physical prototype, thanks to the power of data analytics. Visual analytics completes this process by making innovation simpler, especially when design, testing and feedback can include tens of thousands of lines of quantitative and qualitative information.
Powering Automated Manufacturing
Today, in many sectors, human interaction is limited. Manufacturers can reduce unplanned downtime by detecting anomalies in the manufa cturing process or equipment and implementing preventative maintenance. Visual Analytics enables teams to keep an eye on performance by identifying trends and anomalies months in advance without needing to wade through a mountain of data.
Powering Efficient Product Management
Over-estimating demand might lead to overproduction, resulting in millions of losses for the manufacturer. Conversely, when an organisation underestimates market need, it may cause delays in product or service delivery and damage its reputation. Because of this, manufacturers must accurately estimate their demand to maximise their earnings to the greatest extent possible.
Demand forecasting with visual representations can quickly help predict customer demand. Visual analytics techniques can take historical purchase records and compute future market conditions and produce accurate demand forecasts for the future, allowing manufacturers to fulfil market needs without squandering resources. Visual analytics can provide easy-to-manage and adaptable reporting that is simple to understand through reports that enable the manufacturing processes to be optimised to the market in real- time.
Identifying The Big Picture
Data and analytics frequently reveal trends and patterns that suggest a company’s progress and levels of success. Furthermore, oddities and underlying connections provide additional context. Traditional approaches can be challenging to analyse data, find anomalies, pinpoint abnormalities, and recognise underlying relationships, especially if the right tools aren’t utilised.
One of the essential tools to use is Visual Analytics. What’s the advantage? It allows you to explore critical drivers visually, experiment with them, and hopefully make better decisions as a result. The software enables users to figure out why an incident occurred, assess all alternatives, and unearth hidden potential in data. The software also leads to interaction and the strengthening of important relationships.
What to look for when implementing visual analytics
Visual analytics in manufacturing monitors production lines, tracks equipment status, reduces process errors and improves product quality. Manufacturers are using a variety of different data visualisation formats and tools to analyse information.
When looking into a visual analytics tool, look for the following essential features:
- Visualisation components: Histograms, bar charts, scatter plots, pie charts, treemaps, trellis charts, etc.
- Ad-hoc data discovery: Analysis can be made interactive via drag-and-drop interactions, as opposed to mere visualisation of data sets.
- Connect to external data sources: Hadoop, Cloud services, NoSQL and Oracle, etc.
- Provide alternative approaches to data loading and analysis: Whether in-memory (spreadsheets), on-demand (event data streams), or in-database (Hadoop).
- Geo analytics: Incorporating geo-location features and location-based analysis, such as location-based clustering, spatial search, and distance/route calculation.
- Team collaboration: Without the need for additional third-party tools.
These visualisations help managers analyse the data they collect, identify problems, and make informed decisions that can positively impact operations.
The importance of having the right platform and tools
Having both the right approach and tools in data visualisation is key to making it a successful endeavour. When considering potential options, the one recommendation is to go with the experts first.
Tableau is a powerful visual analytics tool that companies can easily integrate to reveal hidden insights in their data. It provides users with rich visualisations that quickly unveil new trends they previously could not identify without assistance.
It also offers advanced analytics capabilities that allow users to combine data sets, carry out in-depth analyses, and quickly spot changes in their business operations. Tableau’s robust features help organisations improve processes, analyse risk, avoid financial loss, better understand how their equipment performs, and identify where to improve.
Visual analytics is not a new concept, but companies will need to use it as part of its data strategy as big data grows. Today, companies can use visual analytics by leveraging existing tools that provide a graphical interface to create and consume data. It’s vital that companies clearly understand its business objectives, key performance indicators, and the information it wants to visualise, ensuring it employs the right tools to use this approach effectively.
If you would like to find out more about how visual analytics can benefit your business, email us at Salesforce@coforge.com.
Other useful links:
Data visualisation 101
Tableau Visual Analytics
Data & Analytics capabilities
