SAP unveils 'Intelligent Capabilities' for digital supply chains
SAP SE has announced new features to “digitally optimise the supply chain and infuse it with intelligence from product design and production to delivery, operations and service”.
With the integration of SAP S/4HANA to digital supply chain solutions from SAP, companies can gain new insights, make predictions and instantly adapt in an agile supply chain that extends to customers and supplier networks.
The latest solution updates enable an integrated supply chain and manufacturing environment with enhanced capabilities for production planning and scheduling, availability and fulfillment, compliance, health and safety, and production engineering and operations.
“Intelligent technologies help businesses make better sense of data, plan and predict outcomes, and optimise the entire product lifecycle including the customer experience,” said Hala Zeine, president, Digital Supply Chain and Manufacturing, SAP.
“SAP helps companies embrace smarter business based on data-driven insights to run supply chains with greater insight, speed and purpose.”
The new capabilities include:
- Support for highly engineered products — consolidated operations including bill of materials, intelligent process planning, shop floor execution and integrated system testing. Production engineering and operations can be synchronised across manufacturing execution for complex assembly and low-volume operations, such as in aerospace and defense, which traditionally required manual processing.
- 3D visualisation and production — providing visualisation from design through production to service and maintenance, and supporting the network of digital twins. Core business processing is combined with complete product lifecycle management to support decision-making, production and maintenance operations, and 3D printing of components.
- Deeper sourcing and supply integration with Ariba Network — enabling critical supply analysis, vendor selection and flexibility to adapt to changing global trade regulations and variable customer requirements.
- Process production now supported with recipe management development — including the ability to track and find optimal recipes.
- Proposal of suggested options for materials without purchase contracts — using machine learning that can reduce exceptions and errors when processing long lists of open purchase requisitions and help operational purchasers easily create requests for quotations with algorithm-based suggestions.
- Demand-driven replenishment — improved buffer-proposal suggestions for transferred products using machine learning capabilities. This more precise inventory management results in better service levels and better return on assets.
- Enhanced sales forecasts and delivery performance — by gaining reliable sales and fulfillment insights using predictive analytics and machine learning.
5 Minutes With: Jim Bureau, CEO Jaggaer
What is data analytics, and why is it important for organisations to utilise?
Data analytics is the process of collecting, cleansing, transforming and analysing an organisation’s information to identify trends and extract meaningful insights to solve problems.
The main benefit for procurement teams that adopt analytics is that they’re equipped to make faster, more proactive and effective decisions. Spend analysis and other advanced statistical analyses eliminate the guesswork and reactivity common with spreadsheets and other manual approaches and drive greater efficiency and value.
As procurement continues to play a central role in organisational success, adopting analytics is critical for improving operations, meeting and achieving key performance indicators, reducing staff burnout, gaining valuable market intelligence and protecting the bottom line.
How can organisations use procurement analytics to benefit their operations?
Teams can leverage data analytics to tangibly improve performance across all procurement activities - identifying new savings opportunities, getting a consolidated view of spend, understanding the right time for contract re-negotiations, and which suppliers to tap when prioritising and segmenting suppliers, assessing and addressing supply chain risk and more.
Procurement can ultimately create a more comprehensive sourcing process that invites more suppliers to the table and gets even more granular about cost drivers and other criteria.
"The main benefit for procurement teams that adopt analytics is that they’re equipped to make faster, more proactive and effective decisions"
Procurement analytics can provide critical insight for spend management, category management, supplier contracts and negotiations, strategic sourcing, spend forecasting and more. Unilever, for example, used actionable insight from spend analysis to optimise spending, sourcing, and contract negotiations for an especially unpredictable industry such as transport and logistics.
Whether a team needs to figure out ways to retain cash, further diversify its supply base, or deliver value on sustainability, innovation or diversity initiatives, analytics can help procurement deliver on organisational needs.
How is data analytics used in supply chain and procurement?
Data analytics encompasses descriptive, diagnostic, predictive and prescriptive data.
Descriptive shows what’s happened in the past, while diagnostic analytics surface answers to ‘why’ those previous events happened.
This clear view into procurement operations and trends lays the groundwork for predictive analytics, which forecasts future events, and prescriptive analytics, which recommends the best actions for teams to take based on those predictions.
Teams can leverage all four types of analytics to gain visibility across the supply chain and identify optimisation and value generating opportunities.
Take on-time delivery (OTD) as an example. Predictive analytics are identifying the probability of whether an order will be delivered on time even before its placed, based on previous events. Combined with recommendation engines that suggest improvement actions, the analytics enable teams to proactively mitigate risk of late deliveries, such as through spreading an order over a second or third source of supply.
Advanced analytics is a research and development focus for JAGGAER, and we expect procurement’s ability to leverage AI to become even stronger and more impactful.