Demystifying digital: 5 tools to accelerate business outcomes

Editorial Team

Jun 4, 2021

From natural language processing to machine learning, the digital transformation landscape is full of terms that may read like mysterious jargon. In a complex economy, business leaders may be tempted to wait and see how others fare with new technology rather than assuming risk. However, in the case of many digital tools, the business benefits of implementation can offer a rapid return on investment that far outweigh the risk. In fact, prolonged waiting may even hinder organizations as customer expectations exceed capabilities or competitors race to adopt them first.

Driving enterprise digital transformation means changing the way a business operates. The modernization goal is to replace dated logic, obsolete models, manual analyses and tedious tasks with more efficient digital tools to reach better business outcomes faster. Among the best-known possibilities that digitalization has introduced are larger data volumes, more automated steps and more advanced analytical models. However, it is not a single tool or automated process that will change the fabric of how an organization operates. Rather, it is when these tools are combined strategically at scale alongside effective change management tactics that digitalization is elevated to a transformative level.

Many business solutions now feature some kind of digital accelerator, whether through rule-based actions or more complex artificial intelligence (AI). The following outlines five key digital accelerators and their application, and how choosing the right strategic partner for applying these accelerators can generate faster, more successful business outcomes.

5 Digital Accelerators and Why You Should Use Them

Reveal Patterns with Machine Learning
Machine learning (ML) is a computer’s ability to progressively find patterns and apply this ever-increasing knowledge to categorizing data or predicting specific values. It’s a method for leveraging large data volumes with complex interrelationships that requires limited human interaction and can be applied in a variety of tasks, from categorizing customer feedback to predicting and alerting users to unusual events in manufacturing plants.
Automate Tasks with Robotic Process Automation
Robotic Process Automation (RPA) is a programmed set of instructions and rules that allows a machine to mimic a user’s actions to perform a task. Instead of a human taking the time to manually input data into a dashboard, an RPA can do it automatically as the new data arises, ensuring standardization and freeing up employees to do less tedious, higher value work.
Translate Data through Natural Language Processing
Natural language processing (NLP) processes the language expressed by humans so a computer can understand it and engage in a two-way communication accordingly. Using NLP can be helpful for sorting and analyzing datasets with free form text where there are slight variations in language to say the same thing by creating structured data that can lead to scalable interpretations from previously unstructured information.
Understand Priorities through Data, Text and Process Mining
This encompasses a variety of techniques and tools to structure numerical values, categorical attributes, free text or event logs in order to generate the incremental statistical and relational information commonly used for reporting and decision-making. The differentiated value lies in efficiently and accurately interrogating available inputs to derive valuable information, gleaning insight into factors such as diagnosing suppliers’ underperformance, predicting category management flow or controlling purchase order payment accuracy.
Orchestrate through Business Process Management Software
Business Process Management Software (BPMS) digitally models, executes, monitors and optimizes a series of steps that have a clear goal, driving visibility and removing waste. This can be applied to workflows triggered by events such as a customer opening a support ticket, alerting employees to action and keeping them on track throughout the next steps until ticket closure.

While these are perhaps some of the most common digital accelerators, and their sophistication may vary by the degree to which AI replaces the use of explicit rules, the bottom line is that successful implementation varies. Some businesses start with the technology and search for ways to apply it. Although this provides interesting research and development work, it is not the most effective method for a business that wishes to improve ROI or increase process efficiency where it most matters.

Case Study: Using Digital Accelerators for Better Business Outcomes

Transformation is often most successful when you start with a few small but impactful projects and follow a specific business outcome. For example, in most complex organizations, legacy operations structures have risks associated with multiple point solutions, excessive dependence on human communication and bottlenecked processes. As a result, traditional models often have gaps such as a fragmented value chain, delayed communications, suboptimal risk prioritization and issues with external entities including suppliers and customers. These gaps impact the bottom line, leading to service level issues, lower revenues and lower margins.

One Aligned Automation solution applies the five mentioned accelerators through a single connected “Nerve Center” that connects the previously disparate platforms, enabling a set of interactive dashboards with the most relevant KPIs for our clients, including supplier information, project tracking, customer history, and additional data necessary for actionable insights. This scalable solution often captures millions of dollars of value in the first year of activity filling the gaps in process and data and capturing the otherwise lost value by integrating the end-to-end value chain, unifying internal processes, mitigating supplier risk and offering better foresight and control on the market. Like most of our solutions, this platform uses a combination of AI-enabled capabilities, including RPA, ML, NLP and BPMS, to clean, sort, enrich, analyze and present data. By starting with a problem rather than the technology, we work together with our clients to take a more balanced and effective approach that is driven by the outcome.

Partnering to Enable Transformation Success

While there is great opportunity in digital transformation, many companies run into challenges surrounding digitalization in the workplace, such as:

A lack of clarity of where and how to start.
The misguided belief that everything should be automated.
An inability to connect the “loose ends” of existing software platforms.
Fear that AI will replace employees.

At Aligned Automation, we believe that digital tools are meant to support employees, freeing them up from tedious tasks to do higher value work. This is supported through our modular Fast 90 approach, which starts small and builds for scale, providing quick wins and tying up loose ends in the process.