Adopting Big Data and analytics technology in supply chains
Business Chief sits down with supply chain experts to discuss the benefits and challenges of adopting Big Data and analytics in supply chains.
“People talk a lot about data being ‘the new oil’, and cognitive supply chains are indeed making a huge impact, allowing businesses to use Big Data to drive themselves onto the next level. Using artificial intelligence and machine learning to process data makes it increasingly realistic for systems to make smart decisions without the need for human intervention,” says Fred Baumann, GVP for Industry Strategy at Blue Yonder. “When businesses are able to identify disruptions and act with immediacy and decisiveness, the effect will be transformational. Alongside the short-term problem solving, cognitive supply chains provide longer-term learned recommendations to enable businesses to stay ahead of the curve.”
Agreeing with Baumann, Grant Millard, Director and Technology Services Specialist at Vendigital, explains that traditional data analysis methods are outdated and inefficient. “More often than not, companies are operating in a data vacuum. Analysis is based on static data sets which are created, and then recreated, from the ground up. Companies are continuously manipulating the data to get the insight they are after and then repeat this process every time insights are required. This is not only inefficient, but costly and the result is reliance on systems that fail to deliver clear and credible data-based insights. This is where Big Data and analytics can help so that the user is no longer required to analyse data. Rather, the system is telling them what action they need to be taking.” Kirsty Braines, COO at Oliver Wight EAME adds that, “it is a proven benefit that advanced analytics for the supply chain industry increases yield, whether through improved production or reduction of waste. Advanced analytics can play a vital role in identifying issues that can impact yield, as well as help to reduce operating costs, manage inventory and create a more personalised customer experience.”
The challenges of adopting Big Data and analytics within Supply Chains
“The world is becoming more complex as more business and consumer interaction channels migrate into the digital space. This complexity is evident in the amount of data these interactions create across an increasing number of channels,” says Jonathan Clarke, Manager, Statistical Modelling at LexisNexis Risk Solutions. As a result, when it comes to Big Data and analytics, there are a number of challenges that companies can face including data manipulation, adherence to GDPR, credible data, talent and digital maturity. “Technologies such as AI, Industry 4.0, blockchain, Big Data and analytics are game changers for businesses, however it’s all advanced technology and the clue is very much in the name. A huge proportion of companies haven’t reached the maturity to completely handle data, with the technology not fully understood, let alone successfully implemented. If organisations don’t align technology with their business plans, they risk making a very expensive mistake in terms of time and money. This applies to data too. Unless organisations dedicate time beforehand to understand what information they want, what purpose it’s going to serve and how they’re going to manage it, analytics becomes an exercise in futility,” comments Braines.
“Additionally, there is little point in importing this technology into the business if the data that exists is not credible, as this could lead to incorrect predictions,” adds Millard. “It is also important that business leaders import the right expertise. Sometimes, they fail to do this and either get a data scientist who doesn’t understand the business context or an industry expert who knows nothing about data science. Getting Big Data and analytics to deliver value is a multi-disciplinary activity.” Ultimately, Millard stresses that “for organisations considering investment in Big Data and analytics to improve their supply chain management, they need to understand that there is no one-size-fits-all. If these factors are not fully considered at the outset, any investment could deliver negligible value.”
Contemplating the future of Big Data and analytics within supply chains, Baumann speaks of the potential of the technology. “The use of Big Data and analytics in supply chains is rapidly increasing, with it being possible to achieve a near-autonomous supply chain in the future. However, for this to happen, businesses need to get to a point where they feel confident and can trust that technology can identify disruption and subsequently take action. Once this has been achieved, the effects will be incredible: just imagine the possibilities that will be provided by a self-learning, self-healing supply chain that is able to predict challenges and transform them into opportunities for growth.” Agreeing with Baumann, Peter Ruffley, CEO of Zizo, sees emerging technologies, such as the internet of things (IoT) and AI, having the ability to generate greater efficiency within the supply chains of the future. “Edge computing is also going to provide a much easier way for businesses to quantify and understand what they are investing in when looking at collecting data, processing it and moving it. It provides the opportunity to have greater agility and real time analytics.”
Clarke does however comment that, in order to speed up the adoption of these technologies, “government and regulators have a role to play to ensure that legislation is clear, to guide companies on the correct usage of this technology. The significant benefits offered by the increased use of Big Data and analytics has to be balanced with the lawful, compliant use of data.” Raj Bawa Operations Director at JBi Digital adds that, “while the culture has improved significantly in this area,” he too believes that the need for impactful enforcement or policing of big companies is urgently needed to truly reap the benefits of the technology.
How changing your company's software code can prevent bias
Two-third of tech professionals believe organizations aren’t doing enough to address racial inequality. After all, many companies will just hire a DEI consultant, have a few training sessions and call it a day.
Wanting to take a unique yet impactful approach to DEI, Deltek, the leading global provider of software and solutions for project-based businesses, took a look at and removed all exclusive terminology in their software code. By removing terms such as ‘master’ and ‘blacklist’ from company coding, Deltek is working to ensure that diversity and inclusion are woven into every aspect of their organization.
Business Chief North America talks to Lisa Roberts, Senior Director of HR and Leader of Diversity & Inclusion at Deltek to find out more.
Why should businesses today care about removing company bias within their software code?
We know that words can have a profound impact on people and leave a lasting impression. Many of the words that have been used in a technology environment were created many years ago, and today those words can be harmful to our customers and employees. Businesses should use words that will leave a positive impact and help create a more inclusive culture in their organization
What impact can exclusive terms have on employees?
Exclusive terms can have a significant impact on employees. It starts with the words we use in our job postings to describe the responsibilities in the position and of course, we also see this in our software code and other areas of the business. Exclusive terminology can be hurtful, and even make employees feel unwelcome. That can impact a person’s desire to join the team, stay at a company, or ultimately decide to leave. All of these critical actions impact the bottom line to the organization.
Please explain how Deltek has removed bias terminology from its software code
Deltek’s engineering team has removed biased terminology from our products, as well as from our documentation. The terms we focused on first that were easy to identify include blacklist, whitelist, and master/slave relationships in data architecture. We have also made some progress in removing gendered language, such as changing he and she to they in some documentation, as well as heteronormative language. We see this most commonly in pick lists that ask to identify someone as your husband or wife. The work is not done, but we are proud of how far we’ve come with this exercise!
What steps is Deltek taking to ensure biased terminology doesn’t end up in its code in the future?
What we are doing at Deltek, and what other organizations can do, is to put accountability on employees to recognize when this is happening – if you see something, say something! We also listen to feedback our customers give us and have heard their feedback on this topic. Those are both very reactive things of course, but we are also proactive. We have created guidance that identifies words that are more inclusive and also just good practice for communicating in a way that includes and respects others.
What advice would you give to other HR leaders who are looking to enhance DEI efforts within company technology?
My simple advice is to start with what makes sense to your organization and culture. Doing nothing is worse than doing something. And one of the best places to start is by acknowledging this is not just an HR initiative. Every employee owns the success of D&I efforts, and employees want to help the organization be better. For example, removing bias terminology was an action initiated by our Engineering and Product Strategy teams at Deltek, not HR. You can solicit the voices of employees by asking for feedback in engagement surveys, focus groups, and town halls. We hear great recommendations from employees and take those opportunities to improve.