In a move that feels “back to the future”, Salesforce has agreed to acquire Tableau Software Inc for US$15.3 billion in a deal that is expected to close in the third quarter of 2019. It seems all independent BI and analytics companies (except SAS!) eventually get snapped up – Business Objects by SAP, Hyperion by Oracle, Cognos by IBM. The move comes less than a week after Google acquired BI and analytics provider Looker.
Today, many businesses use Tableau (over 86,000), including a lot of Salesforce customers. They have chosen Tableau because it is easy to deploy and use, and like Salesforce own applications, it targets the ultimate decision maker – the business user – and sometimes even the consumer. Recent research into the BI systems integrators in Asia Pacific shows that Tableau is one of the leading analytics platforms for the partner community in the region – the big SIs have many people focused on Tableau. But that dominance is being challenged by a re-energised Microsoft, whose Power BI is also witnessing strong growth – and who is typically the price leader in the market.
For Salesforce customers, there is some overlap between products – their own Einstein Analytics tools do much of what Tableau can do – although Tableau helps customers see insights from data stored both on the cloud and inside their own data centres. It also moves Salesforce closer to the Customer 360 vision – the ability to get a view of customers across the Commerce, Marketing and Service Clouds. Salesforce customers not using Tableau today will get a better user experience by using Tableau as the visualisation platform.
History has shown that it is hard to make such acquisitions successful. Tableau was a huge success because it was independent. The same was for Business Objects and Cognos before their acquisitions. History has shown that when the large BI and analytics vendors are acquired, others move into that space. While Salesforce has announced they will run Tableau as a separate business, it will no longer be independent. Partners will need to be maintained and provided a growth path – and partners are the cornerstone of Tableau’s success. Some of these partners might have strong ties to other software or cloud platforms too such as SAP, Oracle, AWS or Google. Customers of Tableau might feel sales pressure to move to a Salesforce environment – and will likely see Salesforce integration happen at a deeper level than on other platforms.
Tableau’s independence will disappear. However keeping Tableau as a separate business may not be the long term goal for Salesforce – it might be to offer the best application and analytics solution in the market – to make the entire suite more attractive to more potential buyers and users. It may be to take Salesforce beyond the current users in their customers to many other users who may not need the full application but need the analytics and visualisations that the data can provide. If this is the case, then the company is onto a winner with the Tableau acquisition.
BUT…
The long term goal is not analytics reports delivered to employees. It is not visualisation. It is automation. It is applications doing smart, AI-driven analysis, and deciding for employees. It is about taking the human out of the process. In a factory you don’t need a report to tell you a machine is down – you need to book a repair person automatically – or a service technician to visit before the machine has even broken down. And you don’t need a visualised report to show that a machine is beyond its life expectancy. You need the machine replaced before it fails catastrophically.
Too often, we are putting humans in processes where they are not required. We are making visualisations more attractive and easier to consume when, in reality, we just needed the task automated. While we employ humans, there will be a need to make decisions more effectively, and we will still require tools like Tableau. But don’t let the pretty pictures distract you from the main prize – intelligent automation.
If you would like to speak to Tim Sheedy or another analyst at Ecosystm about what the acquisition Tableau by Salesforce might mean to your business or industry, please feel free to schedule an inquiry call on the profile page.
I ran several roundtables over the past few weeks speaking to business and technology leaders about their AI investments – and one factor came up many times – that it is hard to build a business case for AI because 70% accuracy was not good enough…
What this means is that companies have thousands of things to automate. Most of those automations in the short-medium term will deliver 100% accuracy using RPA and other simple automation tools. Every time you run that process you know the outcome.
Along Comes AI and Machine Learning
These dumb processes can now learn – they can be smart. But originally they won’t deliver 100% accuracy. They might only deliver 60-70% to start with – climbing perhaps to 90%. The benefits of these smart, learning processes can amaze – costs can fall, processes can improve, outcomes can accelerate. But traditionally we have built technology business cases delivering 100% accuracy and outcomes.
So we need a new way to think about AI and a different language to use about the way it works. The people who sign off on the business cases might not understand AI – they will come to the business case with the same lens they use for all technology investments (and evidently – all business investments). We also need to be better at selling the benefits to our leaders. CEOs and Managing Directors in the roundtables are surprised to hear that AI won’t deliver 100% accuracy – they said unless they know more about the capability, savings and outcomes that the solution might drive, they are unlikely to fund it.
Make Your Dumb Processes Smart
I take this as good news. It means we have moved beyond the hype of AI – the need to “do AI in our business” that drove many of the poorer chatbots and machine learning projects. It means that businesses review AI investments in the same way as any business investment. But it also means we can’t over-promise or under-deliver on AI. Woodside did this with their initial foray into AI, and they are still playing catch up today.
While there are many opportunities to use “dumb automation” and save money, reduce or redeploy headcount – or have employees focus on higher value activities or make real differences to customer experiences – there are as many opportunities to make dumb processes smart. Being able to automatically read PDF or paper-based invoices – processes usually done by humans – could be a huge saving for your business. OK – maybe you can’t redeploy 100% of the staff, but 70% is still a big saving. Being able to take human error out of processes will often help to save money at two steps on the process – automating the human input function up front and also getting rid of the need to fix the mistake.
Start Your AI Journey With The Low Hanging Fruit
Ecosystm’s Global Ongoing AI study has shown that most businesses are focusing their AI investments on internal initiatives – on reducing process time, cost savings and driving productivity – which makes the most sense today. They are the easier business cases to build and the easiest benefits to explain.
Perhaps AI is also a chance for businesses to acknowledge that “efficient” does not always mean “good”. Many of the processes we automated or coded to ensure 100% compliance don’t give customers or employees what they are looking for. And maybe making the customer happy 70% of the time is better than not making them happy at all…
If you’d like to dig deeper into Ecosystm’s reports exploring the data from our ongoing AI study – check them out here (you’ll need to register if you have not already – it is free to register, but some content is premium):
4 Vendors Emerge as Leaders: Understanding the AI Vendor landscape
Use Cases Drive AI Software Adoption: Understanding The Industry Landscape