Over the course of the year, I have had several conversations with my colleagues Andy Steer, Simon Williams and Frank Jacobs on the subject of why SAP HANA is a perfect storm for SAP customers. In particular, this blog focuses on my thoughts relating to how SAP HANA has driven innovation and how that enables SAP S/4 to provide more timely insight enabling more effective decision making.
Why organisations need Business Intelligence (BI)
It is hard to imagine any blog these days that doesn’t acronym drop terms like #DataLake, #PredictiveAnalytics, #IOT, #ML, #BigData etc. but ultimately all this technology, philosophies and methodologies have evolved to solve business problems. The goal of all data and analytics technological capability is to provide insight of some form enabling an organisation to make decisions in a timely fashion.
In the 1990’s a general approach developed by Stephan Haeckel was developed and is referred to as “sense & respond”, but in the world of business intelligence, is often called “closed loop decision making”. The basic premise is that an organisation continuously monitors (senses) its environment for change, evaluates possible choices and responds accordingly.
Figure 1 – Forrester “Sense & Respond” model adapted for SAP S/4
Whilst a simple principle, this has always been problematic in organisations for reasons such as:
• Delays by which insight is actually received;
• Disconnected technology stacks; and
• Continual data movement and poor data quality and/or data governance.
and is also exacerbated by project and procurement issues which typically:
• Procure line of business applications on a functional basis;
• Produce information requirements to support a functional need;
• Procure analytical technologies to meet point initiatives e.g. A Data Warehouse, Departmental/Desktop analytics for analytical needs; and
• Avoid the wider organisational information needs, which will drive performance.
In an ideal world, an organisation will have appropriate technologies enabling them to sense problems, define an action, respond to the issue and monitor it in an on-going fashion. For example, a goods-in operator may be booking in some returns of wine and whilst doing so a trend chart may show that returns are increasing based upon the brand he/she has booked in.
Figure 2 – Closed Loop BI
The Merchandising department using the same analytical capability receives an alert because a “returns” event threshold has triggered. The required organisational functions will then review the information, drill into issues relating to case mixes and discover a large amount of substitutions going on because there is not enough stock. The team then makes decisions to expedite more stock, rectify the situation and eliminate the cost wastage associated with these returns. This also heads off issues associated with customer satisfaction. Many other forms of embedded BI come to mind and these will require additional forms of technology response.
All this needs to be achieved more simply and without moving data unnecessarily to an analytical platform for it to be effective and keep total cost of ownership (TCO) with IT systems low.
How solutions have evolved over time
The simple example above is a real world customer issue and involves general operational and business intelligence which would normally be achieved by moving data from the SAP ERP to SAP BW or another analytical platform.
Technology responses to achieve operational insight have varied over the last 25 years or so covering basic reporting using SQL, Executive Information Systems (EIS), Data Warehouses, Operational Data Stores, Microsoft Excel models and more recently Data Lakes / Advanced Analytics. The majority of these responses have three fundamental problems:
1. The pervasive nature of data access has meant data has been moved to an analytical platform creating delays in insight;
2. Governance and ownership of data is never resolved properly; and
3. Decision making is not joined up with the context of operational processes
In fact, we find ourselves in an environment where the rate of change in technology is so fast now that the explosion in data & analytics solutions is going to increase IT complexity and hinder decision-making. Procurement will continue to insist on comparisons prior to purchase and more and more vendors will provide niche technologies resulting in a “death by 1000 cuts” for the IT Director who has to manage this evolving toxic landscape.
However, what if I can influence the afore-mentioned problems by:
• deploying solutions that embed BI into my operational processes?
• enable business users to configure the analytical insight they get in their operational processes?
• simplify my analytical platforms; and
• reduce the cost and complexity of continual data movement.
The modern SAP S/4 & SAP HANA landscape
SAP developed the SAP HANA platform to address such needs from the ground up and not via a variety of add-ons. SAP HANA not only underpins the SAP ERP strategy with SAP S/4HANA but also underpins the SAP approach to modern data platforms for analytics with SAP BW/4HANA (see Introduction to SAP BW/4 HANA).
The modern SAP S/4HANA application interface has enabled a rich set of capabilities for both IT and business users to enable embedded BI to become a reality. Firstly, IT users can provide a “semantic layer” of business information, calculations, metrics and views providing a trusted view of the operational data held within SAP S/4HANA. The business information and views are then accessed by users to deliver an information architecture, which provides appropriate corporate performance and KPIs as well as embedded BI, thus enabling the closed loop architectural vision to be realised.
Figure 3 shows a set of tiles a user may have available and in particular, we are focussing on “Overdue Payables” which provides information indicating there is a high value of creditors owed money. A user clicks the KPI tile to open the embedded analytic within SAP S/4HANA.
Figure 3 – KPI Tile
Figure 4 through to Figure 6 show example analytics embedded within SAP S/4HANA enabling the business user to interact with the underlying data, perform the required analysis and take actions appropriately.
Figure 4 Embedded Analytics
The user chooses to view the creditor information by company code and initially sees there is an equal amount of critical and overdue amounts owing. To aid analysis, the user can then interact with the charts to understand the detail behind the figures. Initially, the business user drills into the critical payments required and sees a bar chart showing the organisations owed the most money.
Assuming there are no reasons why the business users needs to continue blocking payments, he/she can then link to a transactional screen enabling them to manage the payment blocks for the company which is owed money.
Figure 5 – User Interaction & Filters
In this instance, the Fiori transactional screen is presented and the business user chooses which transactions can be paid via the un-blocking feature designed.
It is this last part, which enables an organisation to close the loop from insight to decision making. At no point has an organisation had to extract data and move it to a secondary analytical data store to undertake the insight that enables decisions to be made. Embedded BI features like this also support reduction in TCO associated with provision of operational insight.
Figure 6 – SAP Fiori Transaction Screen
SAP S/4HANA is pre-packaged with an “out of the box” set of KPIs and analytics based upon best practice business models enabling operational insight to be generated very quickly. These “intelligent processes” consisting of models and KPIs are not fixed and can be extended if required to support specific information needs.
Embedded BI within SAP S/4HANA is a compelling reason for many organisations to drive their transformation initiatives and move from their current SAP ERP. The potential to both reduce TCO and improve operational decision making enables an organisation to become more agile and responsive in today’s competitive environment. The capabilities within SAP S/4HANA further enable a common information architecture to be created for SAP S/4HANA and SAP BW/4 HANA enabling advanced analytics within SAP BW/4HANA to be leveraged within the same information framework. For further information on SAP BW/4 HANA see my blog Introduction to SAP BW/4 HANA.
Delivering insight without moving and transforming data also further reduces TCO for analytical projects whilst ensuring data quality and governance of transactional data remains firmly owned by the appropriate organisational function. Elimination of departmental analysis presently delivered using desk top BI products and Excel solutions also occurs as more information requirements are driven through SAP S/4HANA and SAP BW/4HANA information architecture.
Did you like this blog post? Here is a similar post by David on BW/4