Decision Optimization : Helping Organizations in Uncertain Times

“Keep it simple. When you get too complex you forget the obvious” – Al McGuire

There’s beauty in simplicity. That beauty of simplicity shows us that complex problems do not need complex solutions. When it comes to technology and technology solutions, it is the simpler ones that have made the mark, seen mass adoption, and reached iconic status. You have to look at some of the apps on your smartphone to understand the power of simplicity – it’s only the ones that are simple and easy to use that you use more, isn’t it?

But what do you do when the times that you live in become complex because of uncertain times? How do you make sure that you can depend on the quality of your decisions when each decision can have far-reaching consequences?

Organizations are aware that making good and fast decisions are challenging in the best of times. Making high-stakes decisions, those popularly known as ‘big bets’, are tough even in the best circumstances. It is potentially paralyzing for organizations to make these big bets and smaller but still important decisions in the face of uncertainty like the COVID-19 pandemic that we are experiencing presently.

Organizations need to increase their agility in decision making to keep up in these turbulent times. This environment is defined by a sense of urgency. You cannot wait for too long to make crucial decisions. And the people tasked with execution have to be confident about the quality of the decisions. For this, organizations need a strategy that provides coherence to the actions needed to be taken. The strategy must be able to best commit the available resources to solve a problem. This is where decision optimization comes into play.

What is decision optimization?

That good organizational decisions are rooted in data is not news anymore. Given the rise of the data economy, we are all aware of how data-driven decision making helps the organization improve the bottom line. With this, we have seen the meteoric rise of the importance of data science teams. We are also witnessing the growing use of technologies such as AI and Machine Learning to improve decision-making and implementation tracking.

Decision Optimization is a subset of data science techniques and is used often to feed into the practice of prescriptive analytics. Decision optimization helps organizations further improve the quality of their decisions for complex problems using tools to build and deploy optimization models that are mathematical representations of business problems. These optimization solvers are further assisted by intelligent algorithms to deliver recommendations to the decision-makers.

Using these recommendations, organizations can get insights into the concrete steps they can take to meet their objectives such as to reduce costs, improve customer satisfaction, increase profitability, accelerate operational efficiency, etc.

Why decision optimization makes sense now more than ever?

“What could happen”? This is most often the question that we need to answer before we answer “what can we do”. Predictive analytics solves this problem by putting historical data, advanced analytics, and machine learning algorithms to work. This uncovers hidden patterns and relationships in the data. With this information, it models likelihoods and scenarios to aid the decision-making process.

But predictive analytics does not provide the information on what actions to take based on these insights to deliver the best outcome. For this, you need to improve your prescriptive analytics capabilities. Decision optimization comes into play here. Decision optimization employs optimization software to deliver prescriptive analytics capabilities to make better decisions and improve their business outcomes.

Today uncertainty reigns supreme in the business landscape. Changing global markets, the increasing speed of technological change, changing consumer demands, and sudden, unseen emergencies (such as the COVID-19), all contribute to the chaos. The complexities of the business environment do not seem likely to ease off any time soon. As such, it only makes sense for organizations to focus on technology-driven solutions that can improve the quality of their decisions. The aim is to ensure that they use the best combinations of decisions to solve a larger business problem efficiently.

Advantages of decision optimization

By using decision optimization technology organizations can:

• Develop and monitor enterprise planning and execution decisions and view key performance indicators across different business aspects
• Evaluate the strength of forward-looking business decisions and understand the potential financial outcomes by leveraging scenario analysis
• Improve the time-to-value of packaged applications and capably tailor solutions to meet the needs of specific business processes and models
• Generate competitive advantage by transforming analytics insights into planning and scheduling processes, and logistics and asset utilization decisions

Decision optimization, simplistically, is all about making the smartest decisions. This is achieved by using mathematical evaluations that sift through all possible solutions to recommend those that are most likely to help you achieve a specific business goal. It does this while taking into consideration all the variables, trade-offs, and constraints.

Decision Optimization can help the organization improve the quality of decisions that impact critical enterprise challenges such as identifying production bottlenecks, improving sourcing strategies, production scheduling, demand forecasting, staff scheduling, portfolio optimization, price optimization, sales and marketing, application development, operations performance, supply chain optimization, etc. with more certainty. And in uncertain times like now, certainty has a tremendous value all its own!

For more details, Please watch our recent webinar on “How Data Analytics can work for a Supply Chain Company for the Van Scheduling using IBM Decision Optimization.