“This change is here to stay, though, and the increasing drive to the cloud and the pay-as-you-go model and Opex over Capex is also here to stay. The GDPR (General Data Protection Regulation) sets a maximum fine of €20 million (about £17.8 million) or 4% of annual global turnover – whichever is greater – for infringements. “It is not optional to manage data and GDPR regulations mean all businesses have to have good data management practices to avoid fines. “Businesses are highly aware of how difficult it is to join up data, get common definitions, analyze cause and effect, and predict the future. How aware are businesses of this issue? Do they accept there is a problem? Data needs to be extracted through APIs and can be costly and slow. The recent trend for cloud-based SaaS services such as Oracle Fusion, Salesforce, MS Dynamic ERP, and CRM means that the system is run and managed by the vendor for you but it also means you do not have access under the hood to all the data. So-called legacy systems were typically running on servers owned by the organization and their IT teams could get access to all the data in the ERP and CRM systems and could build data warehouses to allow them to join the data and to perform analytics. The recent drive to Software-as-a-Service solutions has actually made this problem even harder. For example, without a linked set of data, how can you find out what the net lifetime value of a customer is if you include marketing spend and cost of acquisition? Which customers are profitable and which are loss making? When do you break even? Therefore, organizations end up being limited to asking the questions of the data that they have access to instead of being able to ask the questions that could drive meaningful change. The unique identifier of a customer in the CRM system rarely matches the unique identifier of the customer in the billing system or credit control system. The difficulty of joining up the data between systems and of having common definitions and meaning of data is holding back progress. Most large organizations have multiple ERP and CRM systems which have come about through merger and acquisition activity or organically. They usually come with their own reporting system, which comes with best practice dashboards but only show what is in the single system.
These systems, which typically cost millions to implement and support for FTSE 250 businesses or public sector bodies, are essential but in many cases so complex and difficult to get data in and out to join up that it makes it very challenging for businesses to be able to denote cause and effect between an action and reaction. which help organizations manage and profile their customers to enable them to analyze and drive up loyalty and purchasing and retention. Legacy systems can also be CRM (customer relationship management) such as Siebel, Salesforce, etc. This is really hard to do and some of the main challenges include dealing with multiple legacy systems covering ERP (enterprise resource planning) such as Oracle, SAP Peoplesoft, which help people manage their assets, procurement processes, projects, HR, etc. It must be repeatable and extendable – and therefore scalable. A modern data platform must be business value driven and provide trusted data, by design, from event to effective action. The most common practices we see that hold organizations back are when businesses have not embarked on building a modern data platform. What is the situation with legacy systems and practices? Can this hold back businesses when it comes to making the most of their data?
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