Solving the Last Mile Challenge in Big Data

As we ease into the Big Data economy, business intelligence needs to undergo big changes to make it effective till the last mile - where results matter the most: the end user. While end user is the last mile where the most important business decisions are made, the current business intelligence poses two huge obstacles: cost and complexity. Let us understand why businesses aren’t getting the most out of BI and what can be done to overcome the last mile challenges.

What Businesses are Not Getting Right with Current BI

In any regular enterprise, the BI projects are mammoth undertakings that require huge price tags, armies of implementation consultants, and specialized, full-time staff for ongoing support. According to Gartner, over 60% of enterprises state they have a BI strategy, but despite the many years of experience that most enterprises have with BI, they aren’t doing better in addressing the fundamental challenges of BI from an end-user's perspective.

BI technology needs to refocus on the following points:

• Adopt Search-based Simple Interfaces: If you had to take a training course or rely on outside support to use Google, Whatsapp, or Facebook, would they have claimed billions of users? Of course not! The simplicity of User Experience is critical and paramount. A simple, intuitive end-user experience will be an integral element because it is an already common and effective user experience model to search and access consumer information (just the way you use Facebook, Amazon, or LinkedIn). Following this model, more and more BI providers can add features that allow users to simply search across billions of rows of data to gain instant insights. 

• Enable Ad-hoc Reporting: The next natural step in the Big Data & Analytics evolution is enabling ad-hoc reporting for the broader organizational audience. Yet, this turns out to be more difficult than anticipated. Less technical personnel are faced with a blizzard of arcane data names and a mountain of hard-to-understand tables. They are forced to be dependent on the technical report writers for any new reporting. Gartner reports that IT takes an average of six months before a single report is generated on any new data source. The nimble nature of the Big Data & Analytics opportunity is lost for them.

Drawing a BI strategy doesn’t mean just choosing which mega vendor your enterprise will work with. Gartner estimates that no more than 20% of business users actually use BI proactively. It indicates that BI is not being widely used to manage performance. IT must look for means to align BI initiatives with business objectives, keeping in mind the increasing speed of technology change.

How Search Insights Solves the Last Mile through Search Layer

While a quickly-evolving Big Data revolution ripples across multiple industries, enterprises are still using archaic business intelligence. They are forced to rely solely on scarce technical resources to accomplish anything with Big Data & Analytics. Big Data adoption will remain limited, if the last-mile challenges continue to obstruct users in accessing data. A focused shift back to the BI end user via search will be a promising step forward.

What enterprises really need is an easy-to-use, simple interface that gives non-technical users self-service reporting ability and actionable insights. A layer that has a Facebook or Google like consumer grade experience can bridge the last mile. Non-technical users should no longer have a difficult time deriving meaning through data structures or programming languages. To derive useful search insights, a search layer should have the following characteristics: 

• A search layer should understand the complexities of the data structure.
• It should translate technical jargon into recognizable business names, and organize them in a format that seems logical to the front-line business person.
• It should enable non-technical users to create queries and build reports based on terminology that is familiar and meaningful.
• It should enable natural language search.
• It should have a more real-time, interactive, and iterative user interface for data exploration and analysis.

Let’s look at some use cases of the search layer.

• The sales team can easily access everyday sales data by asking ad hoc questions.
• The Accounting and Finance group can use the search layer to review the general ledger.
• The Operations team can benefit from a version that focuses on branches.
• The Marketing team may need search insights that focus on both campaign management and geo-demographic analysis.

Once in place, the beauty of the search layer is readily apparent. In most cases, typical reporting and analytics tools can easily access the underlying data. But, the people costs associated with everyday report generation, professional services, and configurations required for running data reports will easily outweigh the licensing costs of any past generation business intelligence solutions.

Creating a search layer is a virtual necessity for any enterprise to push the power of Big Data & Analytics out to the wider organization. It is better described as a technique for bringing data closer to the user in a meaningful way. With a user-focused BI technology, enterprises can overcome the last mile challenges and discover search insights for important decision making.

Building user oriented enterprise solutions, not just products

While discussing the topic of why retailers cannot keep up with their customers in terms of information and expectations – several enterprise businesses told me that the single most reason is the lack of easy & timely access to business insights! While this is the exact problem that we are trying to solve at Drastin, we observed several (not-so) interesting aspects in the journey – on how software vendors have been approaching the customer needs.

The Piecemeal Approach for Enterprise Products

Traditionally, IT-facing software vendors believed that selling to enterprises is very different from selling to consumers, due to the following differences:

• Consumer products are mostly end-to-end solutions, because the buyers are the users. For example, while selling a car, the car’s frame, engine, seats, electronics, road permit, etc. are not sold separately. They are sold together as a car to the consumer.
• In case of enterprises - only layered products are built and not solutions, because the buyers and users of the product are different. This leads to an unfortunate thinking that the buyers are more important than the users at enterprises.

This belief led them to design their software as a piece-meal approach to the enterprises, something that can be sold easily, rather than something that can be consumed as an end-to-end solution and that solves an entire use-case for the enterprise user.

The net result of this thinking, lack of design orientation and the lack of focus on user experience forced the enterprise buyers to always buy their day-to-day tools separately. Take the BI space for instance. The enterprises have to buy half-a-dozen layered products from ETL products, BI layers, reporting tools, and visualization tools – separately to fulfill their BI requirements. BI is not alone, I observed the same piecemeal approach in the infrastructure and cloud space as well, as part of my venture. Each of our pilot customers is going through the same issues in the world of decision making. In trying to design products for enterprise buyers rather than consumers, the software vendors have to face evaluation teams and lengthy approval times because of the top-down thinking of enterprises. This ultimately results in lack of attention towards developing a great solution against a great technology.

Is this an issue with the thinking, or the design, or the focus that is only on technology and not on the user?

Our Approach at Drastin

We are looking at a very different approach of providing an integrated “solution” to all customers, rather than a “technology product”. An approach that solves a use-case scenario end-to-end for an enterprise user. An approach that solves both time and cost to the enterprise user. An approach that involves giving a consumer experience to an enterprise user. 

I would like to share some of our key learnings that any enterprise product can take away to create a better experience.

• Build a solution, not a product. A solution that gives an advantage in everyday work, reduces dependencies, and enables self-empowerment. 
• Build something that the users would love to use, and not because it has been authorized by their boss.
• Build something that both the user and the buyer understand. Both have different dimensions to the same problem – while one may focus on the functionality and usability, the other may focus on governance, compliance, service, and TCO.
• Build something with which the user can attach emotionally and can use as an efficiency booster. The enterprise product should allow the user to see the efficiency in one’s own productivity. 
• Build something that solves not only a technical problem, but also a business problem. 

An enterprise product, when built as a solution and with the end-user in mind, could be a lot more complex technically but needs to focus constantly on the point of consumption, so that the user can get value out of it easily. We need to build solutions with the consumer in mind – what they want, how they want to use it, and how it fits in with their lives. It shouldn’t be the technology layers that are important. It should always be about the people who use them to derive value.