Data: What does "good" look like?

Data: Measuring good?

Introduction?

A 2015 Gartner article said, “The data can only take an organisation so far. the real drivers are the people.,” whilst this article is now six years old. Nevertheless, it is still relevant, and little has improved. Organisations continue to strive to become data-driven, less dependent on gut decisions and much more reliant on fact-based decision making; however, the reality of this quest is more difficult for many to achieve.?

?In this blog, I would like to discuss the main attributes that we see within our customers that highlight what good looks like when it comes to data.?

Data Maturity?

Data on its own has no meaning, no value. It only takes on meaning when it becomes information, and then that information is interpreted to drive value in our organisations.?

?We get value from data by turning it into information. That information can then provide us with knowledge. When embedded into our processes and decision-making, that knowledge starts to add value to our business and helps organisations mature in their use of their data.?

?In other words, data in a meaningful form becomes information. That information helps a business make accurate decisions on how they have been and can operate.??

To help measure and organisation maturity when it comes to data, we can look at three key dimensions,???

Are companies’ data mindful: These organisations tend to collect and manipulate their data manually, with it coming from multiple sources. Business users have little confidence in the data with little or no consistent meaning of data elements across the organisation. IT are seen as owning data with business user reliant upon gaining access to external data sources from them, this not only creates an element of distrust but also and without doubt slows down the access of relevant information at the right time to business users.?

• Reporting is purely focused on operational and is limited to tasks that are critical for business operations. There are no formal BI & Analytics tools or standards to support the use, with departments tending to purchase their own solutions. Spreadsheets continue to be the most pervasive BI tool within the business.?
• These organisations start with a platform and process first approach to their digital transformation.?
• They rarely, if at all, put in place ROI cases for the use of data??
• Advanced analytics is done in silos with no automatic feedback of the outcomes/information back into their operational systems??

Are companies’ data accomplished: Do you have a standard set of KPIs with consistent meaning, that is used across the business. Business users have confidence in the information they are provided to drive operational reporting and planning needs. Data is transformed into information that is then used to make critical business decisions.??

• Descriptive analytics is used, typically driven by IT and preliminary stages of implementation. It is used to report on activity on what activity has already happened.?
• The use of Planning tools is in place. Data is usually collected from a single source with little or no flexibility for complex planning scenarios. Little or no automation for the use of external datasets into our planning functions?
• Processes are in place to ensure data is clean, consistent with issues resolved quickly?
• Specialised training is provided?across the whole organisation?both to help create?trust in the data provided and to help empower business users??

Are companies’ data enabled: Embedded intelligence within core business processes, data flows simply across the organisation with no internal or external barriers. Every business user makes decisions without question upon facts. Companies move on from data is information towards information being knowledge, and that knowledge embedded into the way the company operates?

• Predictive analytics is used to predict what will happen many years from now with the use of both internal and external data sources?
• Advanced use of Prescriptive analytics, in many cases embedded within business processes. The users no longer input variables into the system. Instead, the system both predicts what the user needs to see to enable an intelligent decision. The use of machine learning and artificial intelligence helps detect issues before they happen.?
• Data scientists are not pigeonholed and are seen as part of every business process streams?
• Internal and external data is seen as an asset with a clear view on its value, dare I say it, data has a value on our balance sheet.?
• Data is used as an asset to trade with the whole supply chain.?

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?Embedding a data culture into our business processes?

From data, we can enable an organisation to run intelligently. To do this we need our employees to trust the information they receive, ensure that this is provided on time and most importantly empower them to make decisions based on the information, to do their job.??

According to Statistica, “The total amount of data created, captured, copied, and consumed globally is forecasted to increase rapidly, reaching 64.2 zettabytes in 2020. Over the next five years up to 2025, global data creation is projected to grow to more than 180 zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected caused by the increased demand due to the COVID-19 pandemic, as more people worked, learned and used home entertainment options more often from home.”?

?Whilst this data can create immense value for organisations, business users continue to drive their business upon gut decisions rather than rely on the information they have being provided. Therefore, trust in the data and information they are being given is vital, without trust we will never change employee’s behaviour. ?

Therefore, the internal culture regarding how it views and acts upon data is critical, this needs to be at the heart of any mature data-driven organisation. Those organisations that embrace a data culture strive and become market leaders. A report by Mckinsey in 2018 said that “The experience of these leaders, and our own, suggests that you can’t import data culture and you can’t impose it. Most of all, you cannot segregate it. You develop a data culture by moving beyond specialists and skunkworks, to achieve deep business engagement, creating employee pull, and cultivating a sense of purpose, so that data can support your operations instead of the other way around.”?

Mature organisations drive a top-down approach to data, empowering their users to find the information they need to drive the business. This information is provided intelligently and at the right point in time, user have confidence that the information they receive is correct and they feel empowered to make decisions based on it.?

Most importantly as system integrators we must ensure that our customers see value from their data projects. Measuring the ROI after each implementation will help build both the trust and value from our customers' investments. Unfortunately, this is something that I see lacking by many system integrators and vendors.?

?Data-enabled business processes??

Business transformation is about disrupting, innovating, and staying ahead of the competition. In an interconnected, digital world where customer expect a personalised service, organisations struggle to keep up and meet demands. The focus has been on technology, updating legacy applications, providing best of breed solutions, that will create the foundation to provide innovation. So why have so many digital transformations failed and equally why do so many customers still struggle with the business case and value for S/4 HANA???

Let me get straight to the point, technology alone does not drive long term business value, the old phrase ‘it is not what you have it is how you use it that matters’ is key. When we deliver an S/4HANA platform we provide that organisation a technology that can help to transform and evolve from where they are today.?

So, if the platform is only one part of the jigsaw where do companies find value and how will this build the business case for S/4HANA. I believe the answer to these failing business cases and transformations is the lack of conversations at the start of the engagement on data and how it can drive alternative ways of working from processes to business models.?

At the heart of every organisation is their ERP platform, S/4HANA in this article, this is what keeps every business running. ?

If we start our business case for S/4HANA looking through a customer-first lens then we start to appreciate the difficulty and complexity of the changing and volatile demands of our customers, and therefore the impact on every single business process within S/4HANA. We quickly start to move away from a process-by-process approach to delivering S/4 HANA and we start to think about how this platform could and should run in a global, volatile and multi data domain world.??

We need a platform that allows our business users to make quick decisions or even predict what our customers’ new requirements are. These decisions impact every part of our business from product design to service. Bad decisions could mean loss of a sales, customers and even reputation. At the same time, we start to appreciate that the data required to create the information that is needed to run our business cannot be just found within our S/4HANA platform.?

To find true value from our S/4HANA digital transformation we need to remove batch-based decision making and start to embed intelligence directly into our business processes. Building trust in data, understanding the data domains required to make business decisions and adding intelligence into our business processes starts the journey from batch-based decision making into a truly autonomous enterprise, one that can react real-time to the global, every changing demands of our customers.?

?In our next blog we will discuss how you can go about setting yourselves up for with data alongside a successfully intelligent S/4HANA solution.?

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