SAP Smart Predict – Recent Deliveries, Outlook Webcast Summary

This was an ASUG webcast last week with Jan Fetzer , Product Management, SAC (SAP Analytics Cloud), focusing on SAC Predictive.  Thanks to SAP’s Ingo Hilgefort for arranging this.

Review of where SAP stands with Smart Predict, with an outlook, new developments

Figure 1 Source SAP

Figure 2 Source SAP

Augmented Analytics – Overview & Positioning

Figure 3 Source SAP
20 years ago, started with semantic layer platform, led by IT, model led by IT
Data warehouses, summaries of data
Questions asked are predefined
50% adoption

Visual – business led, diagnostic analytics, interactive, focuses on best visualization of data
Tools serve self-service needs
Structured data
Adoption rose
35% adoption

Advent of big data, unstructured data, structured data, deluge of data, focus of analytics changed to be machine-led
Pervasive, diagnostic analytics
Significant insights for users
Patterns, mining data automatically
New interaction schema for interacting with system
Systems can suggest, user context, embedded in apps
See higher adoption

Figure 4 Source SAP
Augmented analytics in SAC became design goal
Allow people to interact with data in a fun way
Find relevant insights in data, use machine intelligence, to find relevant information/changes in data
Elevating users to find best visualization, best relationship that stands out, to more complex problem solving

Figure 5 Source SAP
Business led patterns, on the left

Added additional learning, intelligence, system can suggest, explain data points, relevant insights
On the verge of alerting people about changes in data
Complete predictive engine at the heart of SACFigure 6 Source SAP

See ways people use the system, seeking the guidance from the smart capabilities within SAC to find relevant insights on data

Figure 7 Source SAP

3 buckets of functionality shown above
Converse with system, search to insight – on desktop or mobile, type question and system understands what you mean and generate best representation
Activate smart insight on chart showing textual representation on screen
Investing in this to make it smoother, custom vocabulary

Automated insight – uses machine learning, AI, to find explanations to see what drives data point

Predictive – build a predictive engine in the heart of SAC – look forward instead of traditional BI solutions
Can do this at scale
Predict what will happen in the future

Smart Predict Today

Figure 8 Source SAP
Smart Predict, forecast time series

Classification – classify customers, products, which customers will buy – yes/no

Regression – continuous signal – how will a number be at a certain point in time

Predictions in a dataset can be copied to planning models – tool to do that are called data actions; will be simpler in Q3 release

Figure 9 Source SAP

Problem focus of business outcome – e.g. anticipating customer behavior

Figure 10 Source SAP
Classification – yes no decisions, on off decisions

Regression – numeric values, influencers of those numbers

Time series – generated as a multiple time series – by business area, product group, etc.

Data this can be built upon is shown above; can connect directly to Live HANA system without moving the data to the cloud

Figure 11 Source SAP
Live connectivity to HANA tables, SQL views (not yet calc views, being worked on, hopefully later this year)

Train the model

Smart Predict Roadmap

Figure 12 Source SAP
Where is SAP investing

Will soon release integrate with planning workflows, already with beta customers; planned for August release

Figure 13 Source SAP
Predictive forecasting complements planning

Planning – what should happen based on company targets, while monitoring that, forecasting shows do current developments compare

Figure 14 Source SAP
Do not want to replace the planner; make their life easier, and consider more data points when creating plans
ML helps find patterns in data, make suggestions how data will evolve over time
Business acumen – edit forecasts, make more confident plans

Figure 15 Source SAP

Scenarios seeing with customers

Figure 16 Source SAP
Can use Smart Predict with planning models
Business focus
Beta closes in 2 weeks
GA planned for Q3

Figure 17 Source SAP

See predict scenarios in file system

Refreshing of data sets, live datasets (BW/4HANA + calc view support)

What do you think?