The first quarter is nearly gone. As a finance expert, you will soon start preparing the quarter-end close. You may remember an awful situation you faced at year-end: While your family and friends were enjoying the winter holidays, you needed to run the year-end close. You hoped that everything would run smoothly so you could get out of the office on time.
But when you checked the posting run just before leaving, you saw a red flag. Unfortunately, the error message was utterly unhelpful. It told you nothing about what went wrong, and still less about how to fix it. So instead of leaving, you had to start a time-consuming analysis that you knew would culminate in an argument with your IT department. If the error message were better, however, you might have been able to solve the issue yourself, and faster.
Another scenario: As a collection specialist, you’re responsible for gathering overdue payments from customers. If your customers don’t cover all their invoices, you want to be notified as quickly as possible about their future payments. This allows you to deal with these instances proactively, rather than waiting to react to them. Prompt notification allows you to contact the customer immediately to resolve the situation and claim the remaining cash or even avoid disputes. Being able to chase missed or even skipped payments as soon as the payment advice is processed means more effective cash collection and a better-looking days sales outstanding KPI.
Highlighting issues for immediate attention
Each of these scenarios exemplifies the need to be able to spotlight issues requiring immediate attention. Instead of tediously searching through reports, application logs, or calling various transactions, finance experts expect to receive all relevant information automatically at their fingertips, all in one place, and in a way that’s easy for them to consume and act on.
Thus, finance software needs to capture current business situations based on individually defined conditions, like thresholds, rules, or queries. It must proactively trigger notifications to ensure swift awareness of issues; explain the context from which they arose; include all relevant information, like affected postings; and, maybe most importantly, be intelligible to the finance expert receiving the notification. Finance experts demand not only to be notified of an issue but to get proactive suggestions on how to resolve it. Existing technologies like responsibility management can be leveraged to identify the appropriate users. Potential areas of application are:
- Notification about upcoming deadlines
- Information about pending tasks, such as approvals and confirmations
- Highlighting of surpassed thresholds, such as consumption rates and business-relevant KPIs
The future potential of situation handling is enormous, as intelligent finance software could capture business situations, their circumstances, any actions taken, and the results of those actions. In the future, this data could be utilized for advanced analysis, rule-based processing, and input for machine learning. Machine learning could, in turn, be used to calculate predictions and to recommend better solutions.
The potential of machine learning
The software also needs to recognize recurring patterns – for example, to analyze in what context the user accepts or declines the recommendation. This pattern recognition could be used to improve machine-learning algorithms. High-confidence responses could be considered in regular business processes and thereby be fully automated.
Situation handling offers a continuous improvement process for both high-quality, supported human handling and automation via machine learning. With the increasing availability of data over time, machine learning will expand its capacity to automate routine tasks. And with more and better data, situation handling will support users with analytics-based recommendations and process improvements. Manual processing and automation go hand-in-hand.
Now, how would you like to improve your day-to-day business using situation handling?
This article originally appeared on LinkedIn and is republished by permission.
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