Serving a client at its best
As entrepreneurs we are constantly looking for better ways to serve our clients. When software plays a significant role in the equation, we need to take a closer look at the advantages computer applications have in reaching this goal. We’re all familiar with the traditional way software used to play this role. In the data processing and analysis space, this boils down to the half-century-old role of automating the mundane manual labour – replacing the original job of Computer – the men and women whose task was to labour on the computation of data.
Applicable functionalities used today
Think of the following examples – chances are that your software is executing only these sorts of tasks, whether it is used by your end users, or internally by your organisation.
We’ve included 3 examples here, yet the scope of applicable functionalities touches nearly every aspect of software. More on that in later blogs:
- Planning – The human planner is still playing the key role in planning. The software persists the data, enables the quick and efficient data entry and supplies all the relevant details required by the planner to do his job. Collaboration mechanisms support the concurrent activities of multiple planners, and rules-based modules in conjunction with flow-engines simplify the task and guard against simple human errors. Think of planning unavailable personnel or failing to follow predetermined procedures.
- Transaction monitoring – Humans have a keen eye for detecting suspicious activities. Simple rules may do some of the job, and are easy to automate, yet the experienced professional will detect irregularities – single transactions or a line of activities which do not fit the expectations of regular usage. The emphasis here is once more on the cognitive load these inquiries put on the user apart from the sheer number of transactions one would need to process for a high quality fraud detection.
- Web Sites – The efforts of the traditional usability experts focus on the analysis of personas using the application. They come up with the best solution catering for what amounts to different flows and ways of using the online application. This challenging effort does very little in terms of catering for the individual user’s needs. While we have all gotten used to it as users, we are constantly challenged with adjustment of our own expectations and natural flow to fit the designed interface.
One common theme of the above examples is the way in which user tasks are simplified. Database functionalities – the efficient entry, persistence and recovery of data – signified the highlights of early software applications. They have evolved into software rule-followers, alleviating the user not only from repeatable manual tasks, but in addition incorporating business logic. Rules that keep the user on the right path while entering and editing data, and that have enough instructions to process such data automatically e.g. for the purposes of the automatic generation of rapports, orders and flows. For the user it meant a relief from the need of repeating the ‘brainless’ tasks – those tasks which do not require too much of thinking, or cognitive activity.
Becoming a smart assistant
But even if we do not go as far as building software that thinks for the user in the true sense of the word, we have now in our arsenal the capability of easing the cognitive load the user faces when interacting with the software. Let us go through the few examples mentioned above and look at the possibilities of making the software smarter – smart enough to play the role of an assistant possessing more than simple rules.
- Planning – Although the human planner can still plan the personnel for complex and rule-ridden time shifts (which can really get hairy with thousands of employees), now the application can recommend perfectly good assignments. It can learn from the planner’s past plans, as well as the past data of employee time preferences. The application assists the planner rather than take over his job. The planner can overrule, alter, or just approve the automatically generated plan. His or her changes will affect the future recommendations of the system.
- Transaction monitoring – The application of Machine Learning techniques on transaction monitoring may take several forms. We could shortly mention the ability of these types of algorithms to detect anomalies alleviating the need to specifically code threshold-based rules and also the capability of Machine Learning techniques to learn from the experts and generalize their strategies. When integrated in a transaction monitoring module, the system can alert the expert to pay her attention to outliers or serve as an early warning system, allowing her to watch their development.
- Web Sites – If taken to the next step, online applications can learn the flows and needs from each user. How does he use the application? What parts of it need to become highly accessible for this specific user? Making sense of large number of users makes it possible for the application to recognize different kinds of usages users make of the application and assist them by predicting their needs.
As these examples show, the added value to your organisation and clients means the application can suggest actions based on domain knowledge learned from experience and even getting to know the way specific users interact with it, and help them achieve more by doing less. As entrepreneurs we can achieve gains in terms of efficiency, efficacy, and, by providing our clients with smarter solutions, gain a valuable commercial edge in a modern competitive market.