Author: Z. Caner Taşkın
Over the past decade, supply chain and information technology organizations have invested extensively in data collection and storage systems and schemes and have made great strides in terms of their data maturity.
Companies now have access to an immense amount of data and many are often able to process this data and visualize – in real time – the current state of their operations. But how many of these companies can actually utilize the data they gather to create accurate projections and plans, make decisions, and take actions that help them achieve their business goals? Not many.
Indeed, all this investment in data collection and maintenance is generating little business value for supply chain companies. This is because data maturity, in and of itself, is not a driver of greater productivity and profitability. In order to unlock the value of your data, you must have the capability to use it to make optimized decisions – and this is what we call “decision process maturity”.
So how can you assess and improve your company’s decision process maturity?
The three layers of the decision process
Supply chain operations have literally hundreds of decision processes – from due date promising to capacity, supply, and inventory management – and each decision process consists of three layers. The overall maturity of the decision process depends on the maturity of these three separate, underlying layers:
-Data: For each decision process, you must assess your level of data maturity. If your company has the capability to collect real-time data from various sources including back-office systems and IoT devices, intelligently collate relevant data, and extract business intelligence from it, then you have reached a high level of data maturity.
-Algorithms: You must also evaluate your algorithmic maturity for each business process. By algorithmic maturity, we mean the ability to process data using advanced algorithms to make optimal plans and projections. Many supply chain companies have tons of real-time data, but lack the technology to effectively process this data and glean actionable insights from it. Without this algorithmic capability, these companies have to rely on the human brain, which simply cannot cope with the sheer volume and complexity of the data and analyze it to make calculations and predictions.
-Organization: The last layer of decision process maturity that you must take into consideration is organizational maturity – which refers to your company’s ability to look at the plans and predictions generated by your data and algorithmic systems and use that intelligence to make decisions and take actions. Without a well-designed business process in place – where the right people (decision makers such as planners and other key stakeholders) get access to the right information at the right times – even the richest data and most powerful algorithms will not be able to deliver the business value you are looking for.
Assessing your company’s decision process maturity
Each decision process in your company comprises these three components – data, algorithms, and organization – all of which may have different maturity levels for that particular decision process.
For example, if we look at a specific decision process in your company, your data maturity may be high, but your algorithmic and organizational maturity may be low – and thus you won’t be able to generate maximum business value from all the data you are capturing and compiling. In this instance, pouring more money into data collection and analysis systems will not provide a fix for this issue – as the other dimensions (algorithmic and organizational) will still be the bottlenecks preventing your company from reaching maturity for that specific decision process.
In order to evaluate the overall maturity of a decision process in your company and determine how to improve it, you must:
- Look at the decision process holistically and assess your data, algorithmic, and organizational maturity for that particular decision process.
- Identify which of these three layers are bottlenecks and areas of weakness that require further improvement and investment.
- Devise a concrete plan to improve one or more of these underlying layers to achieve decision process maturity.
It’s important to note that there’s no one-size-fits-all solution that can deliver decision process maturity of every decision process within a company – as each decision process has its own unique circumstances and challenges.
Furthermore, the goal is not necessarily for a company to improve all its decision processes to the highest level, as not every decision process in a company needs to be at the same level of maturity. It may be perfectly acceptable for a company to use manual decision making based on spreadsheet data for some decision processes, while other decision processes in the same company may be better off utilizing sophisticated data analytics algorithms and optimization models fueled by real-time data.
Companies should focus on improving the maturity of the decision processes that matter most to them – those that, if optimized, will bring the biggest operational, bottom-line and competitive benefits.
Is your company ready to begin assessing and improving your decision process maturity?
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