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Salesforce buys Tableau. What does this mean for customers?

Salesforce Acquisition of Tableau

This article was originally published on LinkedIn.

 

This is certainly the news of the day, if not the quarter! The Salesforce acquisition of Tableau is an exciting and critical development for all Salesforce customers. Einstein is already evidence of Salesforce’s belief in analytics. This acquisition further shows that Salesforce recognizes analytics to be truly transformative to every business. And, fundamental to how the Salesforce suite of products will add value for the foreseeable future. While this journey started with Einstein, it is now set to accelerate.

As a Salesforce customer, what does this mean for you? How can you take this promise of big data and analytics, and actually realize the value to grow your enterprise?

In our opinion working with dozens of customers, it’s safe to say most of you might not be ready. And you know this. But you have to get there fast.

Below are the most important ways this merger of Salesforce and Tableau (once approved) will impact you as a customer, as we see it right now. We’re coming from the view of a strategic advanced analytics consultant and Salesforce partner focused on data and advanced analytics. So we’ll focus on steps that you as a customer can take to capitalize on this development starting now.

 

1. There will be a crucial spotlight on the quality of your data

Soon, you’ll see fantastic use cases and the tantalizing visualization that Tableau is known for in Salesforce marketing materials. You will be amazed at how visualization can bring terrific insights to life. And, how easily your users can act on such insights in a timely manner. You will also see there are new opportunities for you.

While all of the above can be true, there is one critical requirement:

Your data must be squeaky clean!

In recent surveys, a majority of companies say they don’t have confidence in the quality of their data. But in order to achieve the value of analytics – across sales, marketing and strategic decisioning – nearly every aspect of data you touch must have the highest integrity.

For example:

  • The data model must be robust to store and process data
  • Sales and data entry process must be disciplined
  • Ongoing commitment to procure/fill in missing data through a variety of means
  • Continuous cleansing, deduplication and transformation practice

Often the reality is, companies are not prepared for this. Instead, they rely on the tech stack to take care of this. That is not robust enough.

Also this critical cleansing step takes awhile – much longer than most enterprises would like – because poor data quality is often the result of years of legacy bad practices that have been untouched.

Customers need to set aside a budget – anywhere from 30% to 100% of the purchase of CRM and analytics tools like Salesforce and Tableau – in order to maximize the value and expectations of the investment in technology and analytics. Account for this when you’re figuring how much you can invest in analytics.

2. The analytic maturity of your organization has to grow (up) very quickly

 Most reports, dashboards, and even advanced analytics can be implemented in an isolated, ad-hoc manner for marketing campaigns and business development. This often happens because companies develop predictive models to optimize limited, prioritized goals.

Tableau will blur the lines between visualization and advanced analytics (predictive analytics, modeling, AI). Further, visualization will become an enterprise-wide endeavor. Nearly every user of Salesforce will want to slice their data, propose what-ifs, and make decisions. Users will push the limit of what visualization can do – and what inferences it can provide. They will also want to collaborate with and present across multiple teams.

The analogy “you’re as strong as your weakest link” would be appropriate here.

Here’s what you have to do to make sure this does not adversely affect your organization:

  • Ensure an understanding of the underlying data. Train every user so they have a basic understanding of data sources, transformation, sparsity, and correlations.
  • Develop a roadmap for advanced analytics. Establish a baseline of how and when the insights are developed, and how to progress from one stage to the next … think crawl, walk and run.
  • Tie to your business outcomes and goals. Begin with the end in mind. Determine who in the company is responsible for what aspect of insights, including techniques for analytics and visualization that impact specific outcomes.
  • Build domain expertise into analytics. Each use case or application of analytics must have a business owner with strongest knowledge of that aspect of the business. Only then can they make sense to visualize, interpret, set measurements and take actions that drive results that they are accountable for.

Build a core team that links technology, analytics, and business leadership together as you implement each phase of visualization and advanced analytics.

3. You must look at investments in your “data ecosystem” in a holistic way

From the above points, I hope you recognize that your total investment might be much more than just the cost of Tableau licenses!

Besides this, you may also have tools across various divisions that need to be consolidated. Here is what you might want to consider along this front:

Other BI tools: You might have non-Salesforce tools that already perform much functionality that Tableau would bring. At an Enterprise level, you might want to consider if consolidation makes sense.

Data Infrastructure: Now might be the time to re-think your data architecture strategy towards scalability and supporting data both internal and external to Salesforce. Here, you should consider if data platforms like Heroku, and data integration software such as Mulesoft, would provide an easier path to managing data readiness.

Data Quality: You can’t skimp on this anymore! And unfortunately there are no short cuts, at least in the near-term. This is a whole world unto itself. So data quality preparation should start early, be comprehensive, and have continuous maintenance.

Einstein: This has been the flagship SKU of Salesforce for advanced analytics. It’s too early to speculate which way this will trend and how the feature overlap will be addressed. Look out for future announcements and be prepared to make adjustments.

These are my early thoughts in the wake of the news about Salesforce and Tableau. In the coming weeks we’ll dig deeper into more specifics on how you can truly leverage this new development and best achieve value from advanced analytics in Salesforce.

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Valgen provides data cleansing services for Salesforce data, and analytics consulting and implementation for Salesforce Einstein.

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