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Reports and dashboards can be a powerful lens into your data. If used effectively, they can provide summary information about the health of your business and can do so at a glance. They save you time, money and can give you insight into the things that are in most need of your attention.

Unfortunately, even when Business Intelligence (BI) teams build great solutions, the way most organisations deploy these solutions can make it difficult for people to find and use them effectively. From my experience, this can adversely affect user adoption and reduce your chances of getting a strong ROI. Empired have created a solution that provides a single user interface to any dashboard and report you have, wherever it lives within or external to your organisation.

Proliferation of BI Tools

Over the last 10 years in particular, the number of BI tools available has risen dramatically. Each of the mega vendors, for example, like Microsoft, Oracle and IBM have at least 2 or 3 BI toolsets alone. There are now also a plethora of specialist BI vendors like Tableau, Qlik and Domo that have their own BI products [i]. These vendors commonly have a tool for standard reporting and a separate one for what many now term “data discovery” [ii].

It’s confusing for the “typical” user to know when to use one BI tool instead of another and what the relative benefits and downsides are of each. But, this is not an article about BI tool selection, it’s about improving user experience and adoption.

An Overly Complex Landscape for the “typical” User

Consider what we will now refer to as a “typical” user in a “typical” company and the number of systems they interact with in an “typical” day. Consider a financial analyst for example. In our experience, a finance analyst would deal with something like 5 different systems over the course of their working month. They’ll likely deal with 1 (or 2 or 3…) systems that are general ledgers, budgeting, planning and forecasting, at least one ERP, financial consolidation, one related to resourcing and so the list goes on.

A marketing analyst is in a similar boat and will need to use CRM, customer data hubs, marketing automation tools, campaign analytics and perhaps even systems that execute on the promise of digital marketing. They may not be experts with all these systems, but they’ll need to work with them in some way if they want to know information about their customers, segments and how best to target them.

Now, each system will likely have its own reporting tool and often users will need to access these for ‘operational reporting’ and other corporate approved tools for strategic or ‘other’ reporting. In the life of a user, it’s not outside the realms of possibility that they could use upwards of 7 different reporting tools - each with its own strengths and nuances.

The Promise of the Data Warehouse Has Failed

The standard IT answer to this problem for some time has been – “well, let’s consolidate data from across the organisation and create a single source of truth” and “well, let’s consolidate all the BI tools and have one standard corporate BI tool that everyone will use”. Whatever…. If there is one thing we all should have learnt by now it’s that there are a range of BI tools available and not all of them will meet everyone’s needs universally.

The promise of the data warehouse has failed

Back when data warehouses were still black boxes, we saw IT teams preach the value of them being the single source of truth for everything. But times have changed and most have realised the error of these types of philosophical arguments. For example, does that mean that our Finance Analyst will go to the data warehouse for GL reporting or for financial consolidation that was only updated last night? You’ve got to be kidding. The days of the large, expensive, heavy data warehouse programs that might deliver value at some point in the future after that data is perfectly transformed and modelled are over.

The Answer?

Instead of creating a single source of truth for everything, organisations are realising the fact that ‘single source of truth’ needs to be contextual. The source of truth for general ledger reporting is actually the general ledger. The source of truth for customer relationship management is CRM. You get the idea. Data warehouses are great at pulling information together from various sources, but they aren’t the one-stop-shop that they sometimes promise.

So, instead of necessarily consolidating all of your data, you probably need to look at a solution that helps you find the information you need, wherever it resides. Imagine a place where you could go that gives you the ability to see any dashboard or report you need.

Introducing SNAP BI

SNAP BI is a window into your dashboards and reports, whether they be internal to your organisation or external. Think of it as a single lens into all the reports and dashboards you need to understand your company’s performance. The great thing about SNAP BI is that it can reside on a server somewhere in your data centre or in your public or private cloud.

Introducing SNAP BI

Take the Financial Analyst example. Rather than looking at BI tool “A” to interrogate the general ledger, BI tool “B” for budgeting, BI tool “C” for ERP, BI tool “D” for financial consolidation and BI tool “E” for the data warehouse, the Financial Analyst simply needs to go to SNAP BI. SNAP BI will provide later between the user and all the different BI tools that exist in the organisation.

SNAP BI takes the pain away and improves the experience of our users by simplifying and enhancing their user interface. The key to success is to put ourselves in the shoes of users and make accessing information simple and easy. There are certainly a lot of techniques to do this like the use of personas, user experience, design thinking and so on. We can go into detail about these at a later time but for now, the important thing is to think about how best they access the information.

Maybe data warehouses still have a role to play in our future, but one thing is for sure – our journey in driving BI adoption needs to start with the user and improving their experience, not by creating the complexity of another heavy IT system.


[i] See Gartner BI Magic Quadrant, February 2016

[ii] Data Discovery is generally referred to as the ability to interact with and merge together disparate data sources to uncover insights. It is generally thought of as becoming mainstream in 2012. Kern, J., (2013), Data Discovery, SaaS Lead BI Market Review, Information Management

Also see Forecast Snapshot: Traditional BI Platform, Worldwide 2016, Gartner, Swinehart, H. Hare, J., Sood, B, Woodward, A. 23rd February 2016

Posted by: Ben Johnson, National Business Manager, Data Insights  | 06 July 2016

Tags: Data Analytics, Data Insights, Data Science, SNAP BI

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