Optimising your SAP data strategy

Data remains one of a business’s most valuable assets, with organisations increasingly using insights derived from analytics to drive decisions and strategy. According to our latest survey of 116 SAP user organisations across the UK and Ireland, three quarters of respondents said their use of data for business intelligence has increased over the last 12 months. However, our survey also revealed that many organisations still face challenges in extracting maximum value from their data.

Major upgrades often reveal data blind spots

A key data source for most organisations is their ERP system. From sales revenue to supply chain planning, software such as SAP can be a treasure trove of customer behaviour and operational data. However, when the time comes to make large-scale changes, such as moving from on-premise to the cloud, organisations often discover blind spots in their data strategy and risk losing value during an upgrade or migration.

One strategic project many organisations are currently tackling or preparing for is upgrading to SAP S/4HANA. Our research showed that two thirds of participants think data management is a challenge when moving from ECC 6.0 to S/4HANA.

S/4HANA’s data structure differs from ECC 6.0, and problems can arise if an organisation has too much data residing in older formats. If a company has not archived its data where necessary, its tables will likely be overloaded with data. The more data a company has in its current system, the longer and more complicated the upgrade will be. Reviewing, archiving and preparing your data for the new formats in advance of the upgrade will make the migration easier and minimise downtime.

Lack of necessary skills, technology and high-quality data

More widely, over half of our survey respondents said they believed their organisation lacked the necessary analytics and intelligence technologies to make effective use of all their data, and 41% said lack of skills was a roadblock to optimising value. Without further investment in recruitment or upskilling or appropriate analytics solutions, organisations will fail to derive maximum value from their data and their ERP investments.

Two thirds of our survey respondents said they also faced challenges around data quality when realising additional value from their customer data. High-quality data is consistent, accurate and complete. The more siloed your data and the more complex your IT environment, the higher the chance of duplication or overlap or other inconsistencies such as discrepancies in units or spellings. Business analysts might also overlook a data silo, causing the overall dataset to be incomplete, resulting in misleading analytics.

Additionally, if your data is inaccurate, you’re unlikely to see the complete picture and any analytics will likely produce skewed results. For instance, if your customer data contains inaccuracies, it is extremely difficult to deliver highly personalised services. Data accuracy problems usually arise from simple human error through spelling mistakes or misunderstandings over ambiguous field names and column headings. Cleansing your data in preparation for any major upgrade will help to ensure a smooth transition.

Optimising data through strategic investment

The research findings are clear: to protect data value during any major change, an organisation needs to invest in the necessary skills and technology and prioritise data quality. Investing in tools such as SAP Analytics Cloud will also help ensure an organisation use all data effectively and uncover valuable insights.

Ultimately, when it comes to data, the challenge is less about how much you have, but rather what you can do with it.

To read more on this topic our Data Analytics Report 2022 is available for all UKISUG members to download here