Historical ERP data: simplify, automate and save money

The digital transformation calls for intelligent answers in a wide range of markets and industries that lead to sustainable solutions despite the uncertainty under which business leaders have to make decisions today. This is all the more true as far-reaching restructuring is expected in many companies in the wake of the coronavirus crisis. Acquisitions and sales, mergers, split-ups, mergers and break-ups of business units, etc. will be on the agenda of managers in order to successfully overcome the consequences of the crisis.

What's more, companies need to save money in the short term. However, IT projects that make this possible must be in line with long-term strategies and measures. The true company value plays a decisive role in both the short and long term. The higher it is, the stronger the negotiating position and the greater the scope for action. To a large extent, this value lies in the company's data and documents. It is therefore no wonder that renowned analyst firms are increasingly emphasizing the importance of information in order to make companies more agile and thus increase their value.

By information, they mean in particular so-called X and O data, i.e. transaction data from operations (O data) and all data relating to the user experience (X data, where X stands for experience). If you look at the successful data-based business models of online providers, the focus on X and O data is only logical. However, compared to companies in traditional industries such as mechanical and plant engineering, automotive or textiles, internet providers are still young newcomers. This certainly explains to a large extent why X and O data currently occupy such a prominent position. However, the knowledge of how to build vehicles efficiently and with consistently high quality is older than the design of an electric car and the corresponding control software.

The human body, its size and dimensions are not subject to the same changeability as viewer tastes in series and films. This is why patterns from the 1950s, for example, are still part of a textile company's valuable intellectual property. Machines and systems have a life cycle of several decades, which means that not only construction plans but also maintenance reports over this period provide valuable insights. These can be of great service in the development of future products, even if the proportion of software will be much greater in the future. Finally, industries such as banking and insurance or the healthcare sector, which are currently facing particular challenges from digitalization, also have an immense treasure trove of historical data that they must store for many decades for legal reasons alone.

Unlocking this treasure should provide valuable answers to today's digital challenges. It is therefore the total stock of information, both current and historical, that constitutes the true value of a company and adds to it.

Digital meets real

Here the lessons learned from the still young online business models, there the experience gained from decades of business activity. Here the focus on short-term changes, there the long-term value of intellectual property acquired over many decades. What looks like a contradiction, and probably was until a few years ago, is becoming a cooperation in the course of the digital transformation. In addition to tried-and-tested construction plans, more and more data from machines and systems will contribute to value creation in the future.

Analyses that indicate changes in consumer tastes allow textile companies to adapt to new trends more quickly and with greater precision in terms of target groups, and even to steer them. Automotive manufacturers can once again become innovation drivers with their proven process and production knowledge if they take full advantage of the opportunities offered by digitization.

The knowledge gained from customer histories, some of which span several generations, can give banks and insurance companies the edge they need when designing personalized digital offerings. The digital transformation is causing digital to meet real and history to meet zeitgeist everywhere.

The intelligent company of the future will therefore focus not only on X and O data, but also on historical H data. This merging of X, O and H data and making it usable together is a challenge for companies' IT departments. They are all, but especially the H data, distributed across many different and sometimes very old systems. And their sheer volume is an obstacle to greater agility for companies. Typically, the proportion of company information that can no longer be changed for legal reasons alone accounts for 80 to 95 percent of the total volume in live systems.

Separate, automate, save

To turn the history from an IT legacy into a source of higher added value, it is important to separate the X and O data from the H data and to manage the life cycle of the historical information separately on a separate platform. This approach has numerous advantages: Significant cost savings can be achieved in the short term, as the legacy systems can be completely decommissioned once the information has been separated and outsourced. As a result, operating costs can generally be reduced by 80 percent compared to continuing to operate the legacy systems. Ideally, no upfront investment is required if the platform and its functionalities can be subscribed to as a service, as is common in the cloud age.

In addition, this transfer of legacy information - including the business context in which it was once created - allows the proportion of data and documents that need to be transferred to the operational systems to be drastically reduced. In the context of a transformation to SAP S/4 Hana, for example, the effort involved in data migration can generally be halved. However, this short-term effect also translates into long-term benefits: Firstly, historical information can be regularly transferred to a separate platform for information management. Not only from systems that are to be decommissioned, but also from the operational solutions. These remain lean and agile in the long term - and do not require a continuous expansion of resources.

Against this background, reducing the total cost of ownership (TCO) of a new S/4 environment by 25 percent is not a pious wish, but a realistic estimate. On the other hand, this approach also has a positive long-term effect in other scenarios. Companies can harmonize and consolidate their heterogeneous system and application landscapes, and even entire IT sites.

If they have sold subsidiaries or business units, they can select their data quickly and completely and transfer it to the buyer in a modern format. This approach also allows companies to increase the protection of their intellectual property and reduce or eliminate legal risks. The requirements of current and new legal provisions such as the EU GDPR or other regulations, which demand seamless management of the lifecycle of historical information, can be met thanks to integrated retention management.

In addition, the historical information and its business context remain 100% accessible despite being stored on a separate platform. This gives specialist users a complete view of customers and suppliers, for example. Companies can meet their obligation to provide evidence and information at any time for internal audits or external audits. Finally, such a platform is the prerequisite for big data scenarios of all kinds. It can be used to cleanse and optimize legacy data before it is stored in an audit-proof manner.

Duplicates can be deleted and incomplete data records can be supplemented and enriched with information from other sources. This is crucial if the promise of data-driven business processes and models is to be realized. Decisions made on the basis of data analyses are only as good as the quality of the data itself. This is all the more true in scenarios where mass data is generated. And these will be standard in the future.

Simplicity instead of complexity

Automation is the key to reducing complexity: complexity that arises from the heterogeneity of the application and system landscape. Complexity that is the result of too much information in the operational solutions.

Complexity that requires costly rework due to poor data quality. Complexity that can only be managed in migration and transformation projects by additional human and financial resources.

Specialization in the management of the lifecycle of historical information and the right connections of a platform suitable for this purpose to the operational systems create the prerequisites for this automation.

At the same time, it is the key that opens the door to a company's treasure trove - to both current and historical information - and massively reduces the associated costs, regardless of the sector to which they belong. This is because the current and future value of a company lies in the information - a realization that is not caused by the current crisis, but can make a decisive contribution to overcoming it.