Dreamforce 2018 - there's more to Salesforce Analytics than Einstein

Profile picture for user pwainewright By Phil Wainewright September 26, 2018
A conversation with FinancialForce highlights dashboard and visualization capabilities in Salesforce Analytics - it's not just Einstein AI that adds value

FinancialForce financials dashboard analytics screenshot
FinancialForce analytics - click for larger version

To most people familiar with the Salesforce product family, the name Einstein is synonymous with artificial intelligence. But the Einstein brand also encompasses the analytics products, even when these tools don't use AI per se. The rationale for this is that they can use AI, and this will increasingly become normal practice as time goes on. But there's a lot more going on under the covers that perhaps gets overlooked because of the Einstein branding.

This point was brought home to me at Dreamforce during a meeting with Raphael Bres, VP Product Management at FinancialForce, who was showing me the analytics built into the new release of its financials application, which rolls out next month. The product is built on the Salesforce platform, and therefore uses Einstein Analytics to power its dashboards. He was clearly enthusiastic about the performance this delivers, as he told me:

I've never seen this in twenty years of business intelligence — the speed and the way it transforms.

He says this will help FinancialForce compete against other players in its market, whose products rely on less powerful analytics, as well as open up opportunities with high-end prospects because the platform will scale to larger data volumes.

This piqued my interest, because the last time I had looked in any detail at Salesforce's analytics capabilities, it was in the first flush of its initial launch as Salesforce Wave. Back then, Salesforce fell into the trap of overhyping its capabilities before it was ready for production use, and perhaps has since overcompensated by talking about it too little.

An all-inclusive analytics platform

To get back up to speed about what it's now capable of, I sat down with Ketan Karkhanis, SVP & GM of Analytics Cloud at Salesforce. He uses the analogy of the smartphone, which has replaced various separate devices that we used to carry around with us. Traditional analytics products are designed to perform specific functions — one to organize the data, another to create historic reports, something else to create visualizations, and so on. Salesforce gives you all of that as a single product, he explains:

We are writing a new definition of analytics which is now inclusive of all the above. It is of course, to your point, breathtaking visualizations done at speed and scale.

All of this flows from the initial goal of delivering analytics that could be embedded directly in the Salesforce CRM environment and would allow the user to drill down into the underlying data. This is where analytics delivers real value, he explains:

It's not just because of the visualizations, not just because of the speed, the ease, the scale, but the most critical factor — it is in context of the business process. We give you a mechanism to, in-context, infuse insights in the business process.

This was only possible by doing everything in a single analytics platform, running at scale in the cloud:

You can have a billion rows in a single dataset. You don't need to buy any additional hardware. We do the columnar, the reverse index, the search algorithms. We do all that.

We optimize the data layer for you so that when your dashboard is running on it, it's returning in sub-second speeds.

Embedding insights into the business context

It's all built from the ground up with that goal of embedding insights into the business context, including the visualization layer, Karkhanis adds:

Very few people know that we wrote our entire charting library, ground up. We don't OEM anything. Most products out there, they open source [their] charting libraries. Our entire charting library, the visualizations layer, is ground-up built for this infused insights mechanism.

This then changes the use case. It means you can deliver analytics to people that will not only help analyze the data, but also through predictive and prescriptive analytics guides them towards better outcomes. This, he concludes, is why AI-powered analytics has to be considered part and parcel of the solution:

The reason we are so differentiated in the market compared to the dozens of classical visualization products out there is we help you not just measure outcomes, but achieve better outcomes. It is about behavior shaping. It is about productivity ...

My goal is not to give you a better looking charts, my goal is to give you insights which will help you serve your customer better.

Infusing intelligence into applications

Karkhanis argues that this is part of an enduring trend that is bringing intelligence into business applications — and therefore it's inevitable that partners like FinancialForce will choose to embrace it:

The architecture of a business application is changing. It is no longer just forms and workflows and buttons. It is about guidance, infused intelligence.

This is can also be seen at customers such as Australian telecoms giant Telstra, he adds:

They have transformed their entire B2B sales organization by delivering Einstein Analytics to each and every sales rep in that embedded experience to drive more predictability, more forecasting accuracy, higher sales. They're not just doing a digital transformation, they're doing an intelligence transformation, because it's not about digital experience only. It is about digital experience plus embedded intelligence and that gives you the intelligent experience.

My take

While you can see the value of prescriptive analytics in a sales automation or marketing environment, I think there's a different perspective in a financials context. Yes, there are use cases in finance for running predictive modeling and perhaps some prescriptive analytics in areas such as collections. But finance people already do a lot of reporting and analytics as a routine part of the value they bring to a business.

The market that FinancialForce addresses will therefore see the benefit of doing these activities within a near real-time dashboard that's embedded in the financial application. Especially when, as Bres showed me, they have point-and-click configuration options to select the KPIs included in the dashboard, and a huge library of visualization options that transform on demand. Salesforce may have underestimated the appeal of its analytics platform outside of the sales and marketing arena — and should perhaps be less shy about trumpeting what it's capable of.