Stepping into a future governed by technology that evolves at lightning speed, data management would be considered high priority in order to manoeuvre the ever-changing technological tools. The outbreak of COVID-19 has continued to expose weaknesses of systems across the globe and it is evident that digital transformation is the key for survival during crisis times. The pandemic has disrupted many global supply chains, bringing a halt to networks between companies, suppliers and customers.
|KPMG Sri Lanka Senior Manager (Management Consulting) Thisara Watawana
|KPMG Sri Lanka Head of Management Consulting and Partner Kamaya Perera
As the pandemic brought light to many technologies that need to be fast-tracked, one key area that needed focus was the tech aspect of supply chains that enables operationality during a crisis. Supply chain analytics is an area that has had its fair share of attention by industry professionals, but came into the limelight as it is necessary to overcome the disruption caused by COVID-19.
Supply chain analytics not only assists organisations in making quicker and more efficient decisions but more specifically helps organisations identify risks, predict future demand and achieve higher levels of ROI to name a few. Supply chain analytics has greatly evolved from what was mostly statistical analysis and quantifiable performance indicators to demand planning and forecasting utilising data collected from different participants in the supply chain and stored on spreadsheets. Businesses have graduated beyond simply using electronic data interchange and enterprise resource planning systems to incorporate business intelligence and predictive analytic software solutions.
The challenge companies face today is making the best use of the large volumes of data generated across their supply chain networks. The increasing complexity of supply chains requires companies to deep dive into the internal and external data captured across the supply chain to make effective decisions. This has brought about a change in the function of supply chain analytics from being descriptive (what happened?) to perspective (what should we do about it?). Bringing this topic to the centre of thought, The KPMG Academy hosted a webinar on Supply Chain Analytics with KPMG in Sri Lanka Senior Manager (Management Consulting) Thisara Watawana to elaborate on these changes and guide businesses on what this means
According to Watawana, “the journey of Supply Chain Analytics (SCA) begins with the extraction of high-quality data. Once quality data is extracted, the correct questions need to be asked and if not, even the latest analytic models will not be able to serve their purpose.” His presentation covered a vast area on how supply chain analytics should be deployed for greater efficiency and a mode of competitive advantage. Some of the key take-aways from Watawana’s presentation:
- Supply chain analytics is far from a one-person job, it is a collaborative approach led by a supply chain expert and requires the support of a data engineer and data scientist to maximise the derived benefits.
- Supply chain data plays a significant role in facing challenges in the supply chain such as visibility and fluctuating consumer demand which are two of the biggest challenges. However, data management and data governance which are key in upholding the quality and consistency of data are ranked very low on this list of challenges.
- End-to-end visibility is the biggest priority for retailers and manufacturers while, real time visibility ranked second.
- He highlighted the internal and external data sources including those that tend to be overlooked but are key in ensuring that all the data necessary is being considered in making effective decisions. Watawana also drew special attention to the role big data and its 3 Vs- Variety, Volume and Velocity, which are pivotal in present-day supply chain analytics.
- Only a mere 2% of retailers and manufacturers practice limited usage of AI on specific business processes and a further 2% use it extensively across the supply chain. The reason behind this reluctance in the use of AI is the fact that it requires high volumes of data and content in order to succeed.
- Supply chain analytics has shifted to being “perspective” allowing companies to take advantages of data analytics for decision support and decision automation as data analytics can be converted into valuable insights and recommendations. This perspective approach has optimised and simplified processes such as distribution network optimisation, automated replenishment, identify the optimum DC locations and route optimisation to name a few.
- Watawana explained an Analytics Capabilities Framework which highlighted the journey of data analytics from being Descriptive – What happened, to Perspective – What should I do and the decrease in human input towards decision making while increasing decision support and decision automation along the way.
- COVID-19 has brought about drastic changes which will have lasting effects in many spheres of our lives. As a result, the performance of perspective analytical models has been compromised as Artificial Intelligence has been affected by change in consumer behaviour which in turn has caused problems for the algorithms that run behind the scenes such as inventory management, fraud detection and marketing, to name a few.
KPMG Sri Lanka’s management consulting team led by Head of Management Consulting and Partner Kamaya Perera, with its comprehensive knowledge on the latest trends and tools to derive the most use of supply chain data that enables effective decisions, is committed to provide comprehensive solutions amidst periods of lockdown to support clients to bounce back.