Demand Optimisation

Balance

The first demand optimisation lever is balance, the multifaceted approach of ensuring alignment between all the aspects of the organisation to ensure demand is optimised and enable the most effective use of supply. It accepts organisations as similar to all other human relationships, flows of information that regulate action. Some of the most common balance initiatives are as follows:

Addressing strategic misalignment

One of the most common business challenges is the lack of alignment between these key areas. Misalignment can be addressed in one pf the following key areas:

• Decay, where elements of the strategic framework are no longer compatible with the world in which they operate.
• Fragmentation, where elements of the strategic framework exist in different guises across an organisation.
• Overtension, where the strategic framework is well defined but is undeliverable on account of the tensions that exist within the organisation.

Adjusting quality

The Pareto principle dictates that eighty percent of the value comes from twenty percent of the effort, and the remaining twenty percent of value would
constitute eighty percent of the effort. Adjusting quality levels on lower value activities can result in quick demand savings.

Avoiding the cost of poor quality

Whilst there may be opportunities to achieve demand saving through quality reductions in low value activities, there’s an equal case for increasing quality in high value activities. There are direct and indirect costs of poor quality (COPQ) :

• Indirect COPQ are things such as the cost of customer dissatisfaction and impact to organisational reputation through producing poor quality goods. Often given less credence is consideration of the costs incurred by the customer, such as the time spent returning a defective product or, to take the example from chapter twelve, the effort for the customer to scan their own purchases at a self-service checkout.
• Direct COPQ includes not only the costs of control, like management processes and quality checking, but also the costs of repair and replacement that result from poor quality. Total quality management theory suggests that up to forty percent of capacity is wasted due to direct COPQ .

Managing demand

The management and control of demand is a key aspect to ensuring business success, at all three levels of the organisation. Demand is rarely static and typically fluctuates. 

Taking steps to both smoothen demand, and managing the downstream implications of upstream demand signals, is key to reducing overall demand requirements.

Changing the organisational design

Organisational design changes incorporate some of the following key areas:

1. Structures. These are the formal and informal structures within businesses, from the operating model to the business hierarchies; ratios of function to spans and layers; systems to geographies.
2. Culture. This comprises the purpose, values and brand of a business. Different approaches are needed depending on whether we are building a culture in a new organisation or changing the culture in a mature organisation.
3. Performance. Business performance can be improved from an organisational design perspective in three ways. Process improvement, which is to make processes more efficient. Work design, which is to make roles better designed. Operational transformation, which is to overhaul enterprise processes to make them more effective

Bot

The last demand optimisation lever is bot, the use of automated technologies to augment or replace existing capacity or capability. There are five levels at which bot can be achieved:

Industrial Automation

Industrial automation is the automation of material handling processes within the primary and secondary sectors of the economy. Its roots lie in the early use of the assembly line to move items between workstations, rather than operate on a static basis. The next leap took place in the early 1960s with the rise of robotics, then in the 1980s as computer power combined with greater production of robotics.

 

Data Centre Automation

What industrial automation does for manufacturing; data centre automation does for data processes. Data centres grew from the large computer rooms on the mid-twentieth century into remote facilities, clouds, with the growth of the internet. Automation of within the data centre not only enables the maintenance of the centre itself, but from a workforce planning perspective it enables the automation of workflows and processes. Achieved typically using scripting or an application programming interface (API), it automates data flows between different software and systems; in basic terms, it allows computers and applications to talk to each other.

Machine Learning

Machine learning (ML) focuses on teaching robots how to learn using algorithms, and sequences of instructions that show a computer how to perform something. Whilst algorithms in traditional computer programming might be used to solve a problem directly, the algorithms in ML enable the machine to learn and thereby solve the problem independently.

 

Cognitive Automation

The next step in evolution is cognitive computing, where technologies learn, improve, reason and decide. Whilst machine learning may be book-smart, cognitive computing is street-smart and able to weigh the surfeit of VUCA information signals to offer a practical solution. Implementation of cognitive computing at a process level achieves cognitive automation and embedded technologies capable of independent thought.

 

Demand optimisation is often a challenging concept to land with stakeholders as business practice has, in many places, turned HR into a function that simply receives and processes orders for more workers. Pivoting to demand optimisation challenges operational leaders to be introspective and look at their systems first. It is, however, one of the better ways to achieve business success.