Editor’s Note: This blog was originally posted on WEDNESDAY, 16 JAN 2019 and has been updated to reflect new information.
When your business is powered by data, it becomes stronger in more ways than one. Read on to learn 6 ways you can build your business with data.
Through every online or in-store interaction, retailers gather data about their customers and their purchases and preferences, all which can be used to further personalise their experience in the future.
The same holds true for back-office functions like Finance and Procurement; these roles gather tons of data regarding what’s being purchased and by which location or department. The data collected can help them in strategic initiatives like forecasting future purchasing trends and identifying opportunities for cost savings. Think of your data as your gym and your organisation as an athlete. Using the right data in the right ways leads to a stronger organisation, just like using the right equipment in the right way makes an athlete stronger and more agile.
Combining data from multiple sources and collecting all your information into a data repository is an important part of ensuring you’re getting the most from your data. New sources of data, ranging from log files, both digital and physical transaction information, and sensor data and social media metrics, present new opportunities for retail organisations to achieve a competitive advantage in the industry. If you’re merging data from multiple source systems, this is an integral part of successfully managing your data and getting the most out of it.
Increase collaboration: Employees from every department of your organisation are generating data that the rest of the company will eventually use. Integrating all the data from different places and formats streamlines your connections and simplifies the complexities of bouncing between multiple platforms to view and collect data.
Get more value from your data: Integrated data is smart data—and with the holistic insights available from viewing it all in one location you can better inform strategic business decisions and make future moves with confidence.
You’ve seen it in blog titles, you’ve seen it trending as a hashtag, but what does Big Data really boil down to? Simply put, Big Data is used to describe large amounts of data of all kinds that has the potential to be mined for information and used in machine learning, AI, and other analytics projects. This type of data is so vast that it pushes beyond the capabilities of traditional databases. Gartner’s tried and true definition of Big Data is, “Data that contains greater variety arriving in increasing volumes and with ever-higher velocity. This is known as the three Vs.”
A built-in data module gives users the ability to easily gather, review that data, and develop meaningful and actionable insights based on what sort of picture the data paints. All from one built-in platform. Most organisations want to implement successful analytics integration into their processes. However, they end up complicating the process by working with third-party developers to get them started. This can cause prolonged ROI timeframes, complex integrations, and excess cash spent hiring out.
Faster product life cycles and increasingly complex operations call for retailers to use big data analytics in different ways. For instance, big data can help you reduce costs through a better understanding of supply chains and product distributions. Many retailers are familiar with the ongoing pressure to optimise asset utilisation, budgets, performance and service quality. It’s essential to gaining a competitive edge and driving better business performance but big data can provide you the information you need to achieve all this and more.
Using Analytics in Accounts Payable (AP)
An analytics dashboard for AP helps you not only capture savings through methods such as early payment discount opportunities but also gives you the tools to locate and remove process bottlenecks. An AP analytics dashboard also gives you insights into:
Invoice processing cycle times
Exceptions in invoice processing
Predictive analytics to flag any invoices that are likely to be paid late
Benchmarking invoice durations & cycle times across the organisation or suppliers
Analytics in Procurement
When you have all your organisation’s purchasing data at your fingertips, you’ll be empowered to locate opportunities to get more spend under management, improve approval times, and monitor supplier performance. You’ll be able to
Identify which vendors would be open to negotiating volume discounts
Consolidate suppliers to reduce costs, capture volume discounts, and increase negotiation power
Enable guided buying, a system that guides individual users towards the goods and services they’ve purchased in the past and what’s being purchased across the organisation to empower on-contract and compliant spend.
Gain the ability to view spend organised by category, vendor, location, organisation, and various accounting dimensions. A Procurement dashboard gives users the ability to track on-contract and maverick spend across the whole organisation while an e-procurement solution assures as much data as possible is gathered.
Analytics for Upper Management
Top level managers and company executives can view the key analytics and insights they need gathered across the purchase-to-pay processes at any time with a built-in data module. They can use this data to:
Track their company’s performance against competitors
Set KPIs based on data
Better understand spend and locate strategies for an improved supply chain
With a built-in data module, once a customer has implemented an AP Automation solution, they can see 100% of spend including direct, indirect, On or Off PO, On or Off Contract, recurring payments, utilities, expenses and more. And with so much information actively running through the system from Day 1, analytics are collected immediately and are ready to be put to work.
Data mining has gotten a bad rapport lately. But at its core, it is the process of robotically digging through mass amounts of information to find correlations and to, therefore, predict logical outcomes. Using an algorithm, data mining collects available data and uses it to evaluate the probability of a future event.
Using this information, organisations can find ways to save costs, improve customer relationships, and better manage risks. With data mining, your company can:
Quickly and automatically sort through the chaos of your huge data sets to detect patterns.
Locate data relevant to business objectives and use the information to forecast probable results.
Fuel your strategic business decisions quicker.
Data visualisation turns your data into a visualised narrative. It can be easy to get bogged down in the pure amount of data that we’ve covered, but this is where things start to transform from mere numbers and correlations to actual visual representations and connected trends.
Good data visualisation is on par with a piece of visual art. Through using a graphical representation of your data, you’ll grab and maintain interest and provide an accessible way to understand trends, outliers, and patterns in your data. To make sense of Big Data, data visualisation helps your organisation locate the narrative of your data, decipher a trend, and understand correlations more clearly.
Information in a snapshot: graphs give viewers a clear, cohesive way to absorb data and make it easier to draw informed conclusions quicker.
Discover patterns and trends: When your data is scattered and housed in multiple locations, you can’t truly understand the full scope of it all. It becomes easier to locate outliers and spot highly correlated pieces when your data is visualised.
Tell your story: Data visualisation helps you better explain the complicated and dense data, trends, and patterns that might otherwise be lost if left as numbers. Engage others with a visually appealing representation of your information to clearly get your message across.
Think of this way to view data as the “meteorologist approach.” Predictive analytics takes data collected through your systems and processes and turns it into potential outcomes. Just like how meteorology takes information regarding weather systems, air pressure, and temperature to predict your weekend report, predictive modeling uses data collected to predict subtle correlations between variables in your data and can use these correlations to make inferences about unlabeled data files.
If you can’t track and analyse your financial decisions as well as your customers’ purchases and behaviors, your retail business risks falling behind. This is why analysing your data and utilising predictive analytics is so important for your retail organisation.
Predictive modeling algorithms can help:
Procurement & sourcing departments to identify risks in delays with supplier deliveries
AP departments to identify potential risks in processing invoices that may result in late payments and consequently penalties from suppliers.
Finance & Treasury forecast for cash reserve & currency exposure needs
Additionally, predictive algorithms can inform advanced forms of artificial intelligence (AI) such as:
Image recognition,
Smart assistants, and
Natural language processing.
In order for your organisation to take advantage of all the offerings of analytics, everyone must be on board. And for that to happen, your company should have the steps in place to ensure successful change management that puts fact-based insights at the forefront.
When change management starts at the top, it effectively trickles down through each level of the organisation so that each individual understands how they’re affected and how analytics impact their role. It’s important to offer your relevant stakeholders proper training and to create a single source of truth from which to base your targets. And with each of the previous steps accomplished, your organisation will lead with fact-based data insights at their side.
Automating you purchase-to-pay solution delivers valuable and actionable data points. Download our whitepaper to learn more about the valuable data you can gather from each part of your P2P—from sourcing all the way through payments. And if you have any questions, we’re here to help!