This is a guest blogpost by Stuart Wells, Chief Technology Officer, FICO.
Recent research by Industry Week found that 73% of manufacturing companies recognise the potential benefits of successful supply chain optimisation (SCO) projects. The same report highlights that while manufacturers have been investing heavily in SCO projects for a long time, and continue to do so, not all of these projects achieve the return on investment they potentially could.
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Even though SCO has been around for years, manufacturing firms still struggle to implement optimisation effectively. Each organisation faces it own challenges carrying out those projects, but there are two key issues that most manufacturers share: data swamps and siloed legacy systems.
Data and integration: the key challenges
The ‘Big Data’ hype pushed firms to invest in storage tools and solutions that quickly collected as much data as possible. However, very few businesses thought ahead, and having a lot of data without a plan for how to use it does not solve any issues, or add any business value.
Manufacturing firms are also struggling to find off-the-shelf applications that fit their existing environment. Ripping and replacing all current tools and platforms is not an option, as many contain critical business data. Many manufacturers struggle with data dispersed across disconnected systems and platforms. This limits their ability to optimise business and process decisions.
Over 85% of organisations tell Gartner that they are unable to exploit Big Data for competitive advantage, while at the same time 95% of IT decision makers expect Big Data volumes and the number of data sources they use to grow further. There is a critical industry need to evolve from classic data management to an approach that leverages information and knowledge across all platforms and systems.
Shell and Honeywell: how optimisation paved the way to success
One company that has taken this productive approach and implemented a successful optimisation project is Honeywell Process Solutions. In many oil-refineries, and other companies in the continuous process industries, the production schedule is created through a surprisingly low-tech approach; humans working with spreadsheets. Manual scheduling is restricted by the analytic limitations of the human brain, which is prone to error, so Honeywell Process Solutions developed an analytics-powered optimisation tool.
The company used mathematical algorithms to analyse hundreds of variables in a short time to determine the best solution out of many thousands of possible scheduling scenarios. This has driven significant economic impact. For example, the downstream effect of scheduling demand-driven production of 100,000 barrels equates to an annual profit increase of more than £2.3 million.
Optimisation is not only useful in production scheduling. Shell, a global group of energy and petrochemicals companies, deployed powerful optimisation tools to improve asset utilisation and maintenance requirements of the chemical plants while improving plant stability and profitability. Shell has nearly 600 advanced-process control applications around the globe, with each processing plant using its own set to run plant operations. It needed a solution that would provide plant-wide control, and help maximise the economic operating benefits for each plant.
For Shell, it was all about making the plants as safe as possible. The team at Shell deployed a platform that runs calculations in real-time by balancing numerous constraints and objectives. After the system calculates the best actions, the onsite team interacts with a visual tool that gives them the control and flexibility to explore trade-offs and make the best possible decisions for the plant. The tool provides recommended actions for every situation, as well as the optimal values for flows and temperatures, which keeps the plant and its crew safe.
Innovate to stay in the game
Manufacturers who use data and analytics in innovative ways will be ahead of their competitors, according to the Centre for Data Innovation. The application of analytics can help many business areas gain significant advantage, in particular when it is used for optimisation as analytic models help organisations to reduce inefficiencies.
Optimisation can help to enhance your workforce and line scheduling, better mix products to meet quality standards, improve production planning, enhance truck loading, optimise production across plants, and rebalance inventory. Like Honeywell and Shell, it is important that manufacturers embrace advances in technology and innovate if they are to thrive in the data-driven marketplace.