Think of the “computer” in your pocket – your mobile phone. It knows so much about you and what you’re doing, what you may need next, and how to get things done more efficiently.
You open your Uber app and it knows where to send a car for pickup. If you sign onto social media, Facebook or Instagram shows you relevant content based on your personal interests or those of your friends. When you send an e-mail that mentions an attachment, it reminds you to attach the file.
These personal applications are context-aware. They use the data you create to deliver a perfectly tailored user experience. And we love that, right?
Here’s the interesting thing: Enterprise software does not naturally deliver that sort of experience – today. But that is about to change.
Context-Aware Versus Intelligent
Humans experience things with an awareness of their context. We understand the place that we’re in and whom we’re engaging with. We know what came before – whether it was the last part of a conversation or some other interaction – and we can anticipate what is coming next. There’s a sense of continuity in our experience that helps us understand how we should adapt and react to new stimuli.
At work, we do best when people understand us. We are more likely to achieve our goals with teammates who understand and respect how we work, receive input, and prefer to engage. All of that requires context.
Enterprise software can often be customized and configured, but it typically is not context-aware. Here’s what I mean: While an app might show me information that relates to me, such as a list of my preferred supply chain providers, the information isn’t likely to be in the context of what I am doing or what I need next.
For example, when I’m ordering products, an enterprise application might understand that I need to order a certain product from a vendor in my region. But in selecting recommended vendors, the software doesn’t take into account that my budget is under pressure this quarter and I need to limit my search to a specific price range. That’s especially true when the deciding factors are based on my latest e-mail correspondence and a disconnected financial system.
Context-aware software can take today’s so-called personalization beyond a superficial level toward one that actually amplifies and augments human output.
If my app recognized my situation and constraints, it might suggest the vendors with the characteristics and capacity to meet my requirements – even if I have no existing relationship with them.
Context awareness is also different from intelligence, which many companies are trying to build into their software. Intelligence is created when algorithms or decision criteria are used to take action on a particular set of data.
Let’s say you know that sales rise when it rains. If the weather forecast predicts three consecutive days of rain, you could expect to sell more merchandise. The intelligence built into your software could help you determine which merchandise you should stock to meet the anticipated higher sales demand.
But it rarely considers the context around your operations. Imagine you are located in Las Vegas, which gets minuscule amounts of rain each year. A predictive model might be right in suggesting that you will sell more umbrellas on the days that it actually does rain. But because the humans around your stores understand their context more broadly, they may not buy too many umbrellas based on the local expectations that they won’t need them in the future. No matter what the data suggests, selling exclusively umbrellas in Las Vegas is a bad idea.
Personalization and intelligence don’t equal context awareness – but they are both prerequisites for it.
A Higher Standard for Enterprise Software
Consumer apps understand context because they have access to the user’s position, browsing habits, and past behaviors. Most consumers allow applications access to their inbox, messages, or push notifications. Information gleaned from these resources provides companies with even more context and data.
In the world of enterprise software, this type of data ingestion has more meaningful barriers. For one, data is regularly siloed. It’s also unclear who has the rights to share it – the user or the company? Couple all that with regulatory issues around data sovereignty and you have a perennial challenge. Simply put, in an enterprise environment, collecting context-relevant data is more complicated than clicking a terms and conditions bubble.
Enterprise vendors also face the challenge of enriching legacy IT systems with context awareness. It’s not enough to provide context awareness only to new technologies or greenfield deployments. Vendors must also deliver innovation that adapts, enriches, and future-proofs the investment customers have already made.
Also, new data encryption models and innovative types of data security are coming to market. We’ll also have to deal with data sovereignty issues across geopolitical boundaries to ensure that data stays in the right places and is accessible by only the right parties. One of the biggest differences between the companies that will succeed in the next decade and those that won’t will be how effectively they are able to think about technology, ethics, and data privacy in a holistic way.
To illustrate this, let’s examine one of our most important investments: Anonymized user behavior tracking. With it, we can monitor and analyze user activities independent from the user interface while still acting as strong stewards of user data. This technology anonymizes data, clusters it, understands specific data flows, and ultimately makes recommendations on how to simplify or even automate processes using that data.
Because we’ve determined how to monitor context, we can watch how customers use their SAP software and predict what a user is trying to accomplish with a given task flow. We can identify when a user is trying to enter a supplier invoice and see that it requires too many steps to complete the task. When this happens, we know that something in the user’s system configuration was set up inappropriately, so we can automatically identify the problem and improve the process.
Current enterprise solutions tend to capture only transactional details. As the technology matures, expect to see more instrumentation around context that answers such questions as: When did the transaction occur? What was the weather like? What happened immediately before or after the transaction?
By blending these different sources of data together, we can consider all of the relevant information and increase context in the decision-making process. That’s a big improvement from a technical perspective.
Considering our increasingly fragmented value chain, it is not enough to limit our focus to technology, privacy, and security challenges. We must also consider ethical and moral implications of context-aware systems. Imagine a company uses SAP software to make decisions about payments. SAP in turn uses an external partner payment platform to provide payment processing recommendations. How do we ensure that there is end-to-end responsibility for the quality of the recommendation being provided by our partner?
As a software vendor, we have a lot of experience dealing with this. But if you’re a large industrial business that’s thinking about completely reshaping the way you go to market and service your customers, you’re potentially using multiple software providers to help you execute. You must ensure that the right moral and ethical controls are in place, even in a newly digitized value chain. It’s important to work with partners that invest the appropriate time into understanding your business. Otherwise, you may be unintentionally outsourcing your decision processes.
As context-aware systems mature, more data integration will be used to inform how applications behave. Identity models and enterprise data tracking will begin to resemble the consumer world, where data blends together across systems in a way that helps create better recommendations and supports better decision-making. That blending of information will likely extend to analytics, where users can create their own dashboards that pull information from multiple self-service systems.
The shift to context-aware systems is already beginning, driven by both workers and their employers. Workers want the same usefulness in their work tools that they experience in their consumer software. Companies will invest in context-aware systems because they will deliver value to their organization. Software that is more human – understanding the context in which things happen in the enterprise – will be the next step toward amplifying and augmenting what workers can accomplish.
About Horizons by SAP
Horizons by SAP is a future-focused journal where forward thinkers in the global tech ecosystem share perspectives on how technologies and business trends will impact SAP customers in the future. The 2020 issue of Horizons by SAP focuses on Context-Aware IT, with contributors from SAP, Microsoft, Verizon, Mozilla, and more. To learn and read more, visit www.sap.com/horizons.
Max Wessel is chief innovation officer of SAP.