Navigation through the Digital Transformation

Process Mining, RPA, Smart Process Control and Augmented Analytics

digitization digitale Transformation - warren buffet

Big Data, Artificial Intelligence, Process Mining, RPA, Machine Learning and more – it is becoming more and more obvious that digital change is no longer a pipe dream. In fact, the point at which the Digital Transformation has long since moved from a groundbreaking trend to an absolute necessity for companies has long since passed. However, large parts of the industry seem unprepared for this important step. In 2018, only 38% of all companies worldwide had a digital business strategy. Even among start-ups, the figure of 55% is still only just over half of all respondents.

However, besides its challenges, the Digital Transformation also holds enormous potential. New methods such as Process Mining provide the perfect basis for the strategic development of digital business models. This opens up new technologies that revolutionize work, such as Robotic Process Automation (RPA), Smart Process Control and Digital Twin Frameworks.

To achieve these goals, however, a well-thought-out digitization strategy is needed. Digital Business Transformation must be carefully navigated from the very first step.

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What is the Digital Transformation?

Digital Transformation, Digitalization, Digital Change – all these terms have the same core idea. Society and companies are in a continuous process of change, driven by the constant development of new digital technologies. From online services to global communications to self-learning algorithms, data, and intelligent machines, they are driving ever larger parts of business and private life. This development is also recursive: new technologies simplify the development of further new technologies. The consequence: ever steeper, exponential growth.

This is already omnipresent in personal everyday life. Smartphones, personal computers and the World Wide Web dominate society. More and more innovations such as smart devices and virtual reality are becoming conventional commodities. The Internet of Things has become the basis for fundamental social change.

Facts worth knowing: What is the Internet of Events & Big Data?

But digitization also has far-reaching consequences in the business context. Companies worldwide are faced with the challenge of carrying out a Digital Business Transformation. In the age of information, manufacturing and service-oriented companies are expected to keep pace with the speed of technological innovation. The Digital Transformation thus represents the most important challenge of our time for industry and economy. It is important not only to understand data, but also to use it and convert it into actionable value.

What are the implications of Digital Transformation for companies?

Digital Business Transformation deals with the planning, control, optimization and implementation of a company’s value chain. This includes the employees, the tools used and the implemented processes within the organization. This all-encompassing approach opens up the possibility for completely new business models and new methods within the value chain. For example, invoices would no longer be checked and processed manually, but by the computer. New production parts no longer have to be ordered, but are produced using a 3D printer. Technologies such as Process Mining even make it possible to check and optimize the performance and compliance of a company’s business processes based on data.

However, in order to achieve these objectives, organizations must meet a number of requirements.

a) Digital infrastructure.
In order to exploit the potential of areas such as Big Data Analytics and Artificial Intelligence, a digital infrastructure is essential. Whether in industrial manufacturing or in accounting, processes must be at least partially digitized. This is the only way for internal IT systems to collect the data that forms the basis for many of today’s innovative technologies.

b) Flexible organizational hierarchies.
The introduction of new technologies always involves a change process within the organization. This affects all stakeholder groups equally. The management plans and controls the implementation of such technologies, but the realization is in the hands of the employees. This requires understanding, education and acceptance. Flexibility is therefore a basic prerequisite for effective digital transformation.

c) Competitive innovation speed.
Innovation alone is often not enough. In order to remain competitive, companies are forced to keep up with the vast state of innovation in their market. The exponential growth of digital change means that organizations that do not adapt quickly enough to new circumstances are left behind.

What are the challenges of a digital change process?

Finding the right digital strategy is essential for business transformation. Even if all prerequisites for the start of a digitization process are fulfilled, without a well thought-out strategic innovation plan only very few new developments can really be implemented.

Moreover, it is not enough to simply integrate and use digital technologies in the company. In addition to logistical issues, organizations must also consider that Digital Transformation is an ongoing process. The market determines the speed at which new technologies are introduced. This presents managers and process owners with the challenge of rapidly implementing innovations to keep pace not only with the competition, but also with society’s state of the art.

Furthermore, digital change requires effective knowledge management between business units. Humans are still the decisive factor in the implementation of new technologies. It is therefore not sufficient to just adapt the IT landscape of a company. Innovation requires experts and sensitivity for adapting to new developments.

What are customer expectations in the digital age?

Technological developments affect industry and society alike. As companies develop new tools to deliver their products and services to customers faster and more effectively, consumers’ needs and expectations change.

More performance

The technical innovations that are revolutionizing Industry 4.0 are not hidden from the public eye. Whether through direct observation or indirect subjective experience, customers notice the performance improvements digitized companies are experiencing. As a consequence, more powerful products and faster delivery times are becoming the norm. Digital change not only determines supply, but also has a direct impact on customer demand.

Better communication

The Internet has become by far the most important channel between companies and their customers. On the one hand, this opens up new ways for organizations to carry out more direct communication and more targeted marketing. Customers are presented with multi-layered customer journeys and multi-channel marketing. On the other hand, it also raises the expectation that companies must always be available, communicative and transparent. The balance of power between supplier and buyer has shifted significantly in favor of buyers. In this new structure, open and fast communication is a necessity.

Process Mining as the navigator through Digital Transformation

Digital change presents many challenges for companies, but also promises enormous development potential. Digital business models benefit from more effective controlling, more security and stronger customer contact. But to tap this potential, a future-oriented, fact-based strategy is needed.

Process Mining solutions such as LANA provide the basis for digitization strategies.

Understanding data, using data.

Process Mining is a method for targeted data processing. Tools such as LANA Process Mining automatically read the process data stored in IT systems. On the basis of these so-called event logs, the tool visualizes the business processes as they are actually experienced in operation. Process Mining thus ensures unparalleled transparency. It allows deep insights into the performance and conformance of processes and automatically identifies bottlenecks, deviations and optimization potential.

The preparation of real process data forms the basis for companies to transform their business models in a target-oriented and data-supported way.

Optimizing the business from the ground up.

The Process Mining approach does not only function as a roadmap for digital transformation. The versatile features enable Process Mining to actively support business development. LANA uses Machine Learning algorithms to get to the bottom of problem causes. The automated target/actual comparison also allows direct comparison between real and ideal process flows – Conformance Checking through the power of the data.

With Process Mining, companies build the framework for sustainable optimization measures.

Minimize risks proactively.

Data-supported transparency in business processes is also an effective tool for thorough controlling. With reports that are accurate to the second and flexibly adaptable dashboards, compliance risks can be prevented at an early stage.

Process Mining represents the starting point, the framework and the continuous control of the Digital Transformation of companies. LANA accompanies you on every step of your digital journey.

How does Process Mining work in practice?

Poster Process Mining Preview EN | Lana Labs

Reach new horizons with Process Mining

Read three examples of innovative technologies that companies can develop through the use of Process Mining.

Robotic Process Automation (RPA)

What is it about?

The potential of automation plays a particularly important role in the implementation of processes. Robotic Process Automation refers to the execution of individual process activities by trained artificial intelligence. For example, invoice checks or document creation can be carried out automatically. The virtual robot learns the necessary process steps independently using an RPA tool.

robotic process automation RPA

Why should you use it?

Automation through RPA represents an immense potential for improved resource efficiency and faster process execution. The self-learning system is less error-prone and more transparent than a costly manual implementation. At the same time, the technology offers comprehensive monitoring through automatic logging of all activities performed in the system.

How does Process Mining help?

Both the introduction and the implementation and control of a Robotic Process Automation solution can be facilitated by Process Mining. First of all, tools such as LANA provide a holistic insight into process data to provide a good overview of which business processes are ideal candidates for automation. This data interface is then used in the implementation of RPA as well as in continuous monitoring.

Smart Process Control

What is it about?

Smart Process Control describes the monitoring and control of processes using a learning system. A model is fed with historical process data using Machine Learning methods. This training allows it to automatically link process and data correlations with system configurations and key figures. Taking current live data into account, the system can independently make changes to the system settings and adjust the process control autonomously.

Why should you use it?

The automated process adaptation through Smart Process Control allows optimization measures to be carried out in real time. Decisions to change certain parameters are not made retrospectively after undesirable process deviations have already led to resource loss. Instead, the process is automatically adjusted as soon as undesirable behavior occurs.

How does Process Mining help?

Process Mining is the essential foundation on which Smart Process Control is built. A controlling system inevitably requires the data insights that Process Mining offers. Firstly, it trains the Machine Learning algorithm. Secondly, real-time monitoring cannot take place without an interface to the process data. Process Mining is therefore a basic building block for the effective use of Smart Process Control.

 

Selbstlernender Prozess - Process Mining Glossary | Lana Labs

Augmented Analytics & Digital Twins

What is it about?

Augmented Analytics covers the entire range of new intelligent analysis technologies. Machine Learning automates and revolutionizes the performance analysis of various business areas. The Digital Twin Framework is one of the areas in which this technology has attracted particular attention. Smart data analysis in real time creates a complete digital image of a process, a business unit or even an entire supply chain. This serves as a basis for in-depth analysis, controlling and monitoring.

Why should you use it?

The relevance of augmented analytics is gaining more and more attention. The technology was named one of the most important Tech Trends for 2019 by the market researchers Gartner. Of course, artificial intelligence does not only play a role in the implementation of your business models. Data control is one of the key areas of this technology’s potential. The first Digital Twin projects in various industries are already showing promising results. Hardly any other analysis method offers such an all-embracing, in-depth insight into your company’s processes.

Digital Twin mit Process Mining

How does Process Mining help?

Process Mining essentially belongs to the field of Augmented Analytics itself. Machine-learning-supported process analysis, however, forms a comprehensive framework for the establishment of a Digital Twin Network. The data visualization capabilities offered by tools such as LANA Process Mining represent the core of what a Digital Twin is supposed to achieve.

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Digital Transformation with
LANA Process Mining

Are you ready to tackle the Digital Transformation of your business? Then follow our navigation. The optimization of your business is our goal – for this we tread new paths of excellence. To find out how you can best use LANA in your business, don’t hesitate to contact us!