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Despite some of the challenges regarding data rights, data protection, and privacy, Big Data has already had a significant impact on society, on how we work, and live. But there is more to come. Data scientists and domain experts with the aid of modern analytic and in-memory technologies have made great advancements, however we are just scratching the surface when it comes to unearthing the value from all of the diversity of data we are creating.

Looking into a not-so-distant future, intelligence-enabled applications will be the next generational change of software technology. I am talking about machine learning, deep learning, natural language, and speech-to-text types of technologies that will bring intelligence to applications –both in terms of the insights that can be drawn from large and diverse data sets and in terms of how end-users experience those insights. These intelligence-enabled applications will observe the vast diverse set of data, will understand it in a way that is relevant to the people in various roles driving business, making decisions, and just doing their jobs; it will learn from that interaction, and will take action based on past experiences.

Looking into a not-so-distant future, intelligence enabled applications will be the next generational change of software technology.

In the enterprise business applications space we talk about workloads like human capital management, travel, procurement, supply management, or customer engagement. Our enterprise customers all have the same challenges; they are thinking about retooling these workloads, and retooling how businesses operate to embrace data signals that they didn’t have access to before.

Say you are a global contract manufacturer and the livelihood of your growing business depends on winning bids via RFPs (Request for Proposal). There is a lot of work that goes into responding to an RFP, so that it fulfills all the asks, expresses the value-add of your company, and maximizes your profitability. There are tools today that help in the RFP process, like screen scraping, pulling data out of websites, pulling data out of contracts, and basically writing the RFP. However, this does not make up for the experience that a seasoned employee brings to the table interpreting what is being asked for in the RFP, knowing the history with that customer, and knowing about risks and alternatives with local suppliers and transportation providers that help formulate a locally competitive and sustainable winning bid price.

If your business is growing, chances are you have a few seasoned veterans and a whole bunch of rookies who are writing bids. Basically, you don’t have much of a bench to pull from, which lowers your odds of winning overall.  This is a scenario where Big Data and intelligent systems are going to provide that knowledge and experience to everyone. In some ways, leveling the playing field – everyone will benefit from diverse, historical data, and analytics informed contextually relevant insights. In time, there will be an RFP app with an intelligent agent working alongside the employee to write the winning bids.

At SAP we are already thinking and researching about how intelligence is going to be interwoven into our applications in the future. The goal is to figure out how everybody can benefit from world-class experience in a domain space even when they are brand-new to the job. I fully grok that nothing replaces domain expertise; intelligence-enabled applications will just help scale that expertise.

SAP’s work in this space follows a design thinking methodology, which starts with what we want to achieve. The very first step is about going back to the root of the value created, and talking to the people who are domain experts and central to the workflow – we need to understand what they really do and how they do it. We are closely observing how they get their job done, what information is used, what are the things to look out for, why they do it in such a way, etc. At the end of the process, you learn about data sources and information that people are using to do their jobs that are beyond what is traditionally assumed.

Having transformed a few times thru generational software changes, SAP knows that it is not just about building a generic application with machine learning technology. The key is starting with a particular domain problem and returning value to a set of users, for a particular workload. That’s the beachhead.

As we journey deeper into this Big Data and intelligence driven future in the enterprise, everything will turn on its head and it is not often that you get the opportunity to be at the forefront of something this significant.

I am often asked why SAP is relevant in this space. My answer is simple, there are two things that are important to know about SAP.

First, it is the data underneath SAP systems that is running the world today.  SAP’s ERP and our Cloud LOBs like Concur and SuccessFactors are the most deployed systems of record on the planet. We earned this position with both deeply functional software, but also through deep industry knowledge. SAP recognizes the value of all the diverse data sets working in concert to help the world run better and improve people’s lives.  The data insights that we have around finances, logistics, manufacturing, travel, procurement, human capital management, and customer engagement is an important component; and the relationships between these data sets is where we are having conversations to find the sweet spot for innovation and value creation.

Second, we are moving very quickly towards the future. Early on we recognized that the diversity and scale of data is going to have a profound impact across many industries. Our investments support this belief, as seen in SAP HANA which is an in-memory Big Data processing system, SAP Vora which plugs into the Hadoop ecosystem, all our acquisitions in the human resources, travel, procurement and commerce space that were carefully picked to build out our digital framework, and we are now bringing ERP to the cloud with S/4 HANA as our digital core.

This is one of the most exciting times in the industry. As we journey deeper into this Big Data and intelligence driven future in the enterprise, everything will turn on its head and it is not often that you get the opportunity to be at the forefront of something this significant.

If you haven’t read it yet, here is the link to Part I of this blog.

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