Dec 1, 2020

The Greater Data Ecosystem: Driving Decision-Making

Peak.AI
Data
AI
Sponsored Content
Peak.ai
5 min
The greater data ecosystem
As teams face increasing pressure to make the right decisions at the right time, Peak.ai discusses the importance of data driven decision making...

The phrase “data is the new oil” has found its way into just about every business presentation since it was first coined by Clive Humby back in 2006. The statement, although contestable (since not all data has the same ‘octane’ content), does beg the question that should always follow: what data?

As the COVID-19 pandemic continues to disrupt the majority of industries, its impact on supply chains has been nothing short of seismic. As teams face increasing pressure to make the right decisions at the right time, squeezing every last drop of insight and information out of your vast amounts of data has never been more important. 

These tricky times call for a new approach to data-driven decision making, and there’s now a real need for supply chains to focus on, what we call, the greater data ecosystem. 

Yes, you can make effective decisions based on data from your current systems, or by joining up a few previously-siloed sources across your organisation – but there’s potential to go even further than this. The more data you have to play with, the more informed your supply chain decisions will be. Let’s take a closer look at a few different data sources that Peak is exploring with our customers to drive intelligent supply chain decisions.

Customer Systems and D2C data

This is all about linking data from your own supply chain systems with your customers, as well as consumer behaviour data points (for those with direct-to-consumer channels.) For instance, this could be their ERP system or even the logistics systems between your business and your customer. 

For example, suppose you’re a consumer packaged goods business or a manufacturer, with a better handle on Electronic Point of Sale (EPOS) and any other sell-out data from your customers’ systems. In that case, you can better predict what demand is going to be like, and better understand their stock levels in order to help you anticipate yours. You could even factor into account things like receipts data; what baskets are shoppers generally buying together, and how can this help you better anticipate how groups of products are going to sell together. 

This closer relationship with your customers’ systems allows you to better serve them and increase efficiency and anticipate demand fluctuations. In short, it’s all about creating more competitive supply chains which are more cost-effective, with better service levels and a more accurate view of demand. 

Supplier Systems

By leveraging data points from your suppliers’ systems, you can plan ahead in the most efficient way and execute an effective just-in-time (JIT) inventory management strategy, holding minimal assets to save cash and space whilst still fulfilling customer demand. Our customers who are employing this methodology are able to understand when a supplier is going to deliver, to what location, and anticipate the arrival of goods and raw materials whilst also better understanding working capital implications. 

Environmental and Global Data

Don’t underestimate the power hidden away in external, third-party data sources and the impact it can have on your supply chain decision making. Think about the ways your business can utilise, let’s say, macroeconomic data to understand what could be driving issues connected to supply and demand. Yes, we immediately think of things like GDP, or maybe even exchange rates, but there is now a plethora of data out there, that may be more industry and company-specific, that helps predict demand or implications for business performance. For instance, a sad but apposite data feed could be the level of COVID-19 near a supplier, which may hamper their ability to supply. Potentially, AI and machine learning could help understand the impact of these incidents with supply performance.

Network Data Sharing

“If companies begin to institute data sharing in their supply chains at the same time, they will be in a much better position to deal with a future shock.” ––World Economic Forum

This one may seem a little more blue sky for many businesses at first, but the benefits can be enormous if you can imagine not just working closely with your retailers, but also with competitors and those providing similar products – allowing you to gain a unique view of exactly what is happening across the rest of the market. This leads to a better understanding of wider trends and the ability to make better smarter decisions. With a mutually beneficial relationship with the wider network, you can understand supply issues, and work with competitors or neutral parties to deliver better products and services to your customers creating a form of ‘coopetition.’

Introducing a New Type of Business System

Tapping into the greater data ecosystem and utilising it in your decision making offers an untold number of benefits for supply chain teams. However, to truly unlock this potential, a new approach – and a modern architecture – is needed. 

In the same way that business functions have their own systems of record, the ability to power decision making based on a wide range of data sources hinges on the introduction of a new, centralised enterprise business system. For Peak, this is our AI System, which gives teams the ability to leverage unlimited data points at scale and speed.  

With artificial intelligence (AI), we’re able to connect the dots between data points and prescribe recommendations and actions to help you optimise your decision making across the entire supply chain. 

For instance, by feeding external data into both demand and supply planning systems and leveraging it with AI, you can optimise that connection between these two core areas of your business. Not only does it allow you to better sense demand with a higher degree of accuracy, but also enables a better understanding of how supplier and operations constraints are affecting supply – automatically making micro-adjustments to optimise the way demand is being fulfilled.

Get in touch to find out more about the impact AI-powered decision making and the potential access to the greater data ecosystem carries for your supply chain.

 Sign up to our upcoming webinar alongside AWS to learn how to accelerate your D2C strategy. 

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Jun 16, 2021

Fluent.ai x BSH: Voice Automating the Assembly Line

Fluentai
BSH
AI
Technology
2 min
Fluent.ai and BSH announce plans to bring speech-to-intent AI to the assembly line that will increase factory efficiency and improve worker ergonomics

Fluent.ai has deployed its voice recognition solutions in one of BSH’s German factories. BSH leads the market in producing connected appliances—its brands include Bosch, Siemens, Gaggenau, NEFF, and Thermador, and with this new partnership, the company intends to cut transition time in its assembly lines. 

 

According to BSH, voice automation will yield 75-100% efficiency gains—but it’s the collaboration between the two companies that stands out. ‘After considering 11 companies for this partnership, we chose Fluent.ai because of their key competitive differentiators’, explained Ion Hauer, Venture Partner at BSH Startup Kitchen.

 

What Sets Fluent.ai Apart? 

After seven years of research, the company developed a wide range of artificial intelligence (AI) software products to help original equipment manufacturers (OEM) expand their services. Three key aspects stood out to BSH, which operates across the world and in unique factory environments.  

 

  • Robust noise controls. The system can operate even in loud conditions. 
  • Low latency. The AI understands commands quickly and accurately. 
  • Multilingual support. BSH can expand the automation to any of its 50+ country operations. 

 

How Voice Automation Works

Instead of pressing buttons, BSH factory workers will now be able to speak into a headset fitted with Fluent.ai’s voice recognition technology. After uttering a WakeWord, workers can use a command to start assembly line movement. As the technology is hands-free, workers benefit from less physical strain, which will both reduce employee fatigue and boost line production. 

 

‘Implementing Fluent’s technology has already improved efficiencies within our factory, with initial implementation of the solution cutting down the transition time from four seconds to one and a half”, said Markus Maier, Project Lead at the BSH factory. ‘In the long run, the production time savings will be invaluable’. 

 

Future Global Adoption 

In the coming years, BSH and Fluent.ai will continue to push for artificial intelligence on factory lines, pursuing efficiency, ergonomics, and a healthy work environment. ‘We started with Fluent.ai on one factory assembly line, moved to three, and [are now] considering rolling the technology out worldwide’, said Maier. 

 

Said Probal Lala, Fluent.ai’s CEO: ‘We are thrilled to be working with BSH, a company at the forefront of innovation. Seeing your solution out in the real world is incredibly rewarding, and we look forward to continuing and growing our collaboration’. 

 

 

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