Business data analytics – making it work for the business
One of the critical axioms driving businesses in the digital age is the awareness that being a data-driven company will be vital in understanding what powers the business. To accelerate digital transformation initiatives that sound nice to have, business data analytics can show how to leverage it to make the most out of opportunities to optimize the organization.
By now, many firms are aware of how powerful insights into their processes, supply chains, even maintenance schedules can vastly improve the entire operation. But while some 47% of business leaders say advanced data and analytics have fundamentally altered their industries over the past four years, as per McKinsey, many are still struggling to put their data to work to improve performance efficiencies and to capitalize on the opportunities that could be presented.
That’s because there can be more than a few obstacles to leveraging advanced business data and analytics to their fullest extent. For one thing, proper data resources can often require a substantial investment of time, money, and resources and it can be hard to convince key decision-makers that the ROI is worthwhile.
And in many cases, an organization’s data is rarely neatly ordered, without inconsistencies and discrepancies. This can often require arduous data clean-up before the data can be put into action, bringing up the third common issue: too often the data is visually well-presented, at presentations and such, but how it can be integrated into actionable workflows is sometimes overlooked in the strategizing.
Understand the why
In order to overcome these barriers and to maximize the usage of both the business data and analytics capabilities, companies should start by first asking themselves what are their business objectives. Understanding what they want to achieve, can help companies figure out what they want to gain from their historical data.
For example, sales forces often don’t think they need data because they interact directly with the customer and know what they want. But advanced data insights can be very effective at identifying cross-sell opportunities by surfacing the buying patterns of customers with similar profiles, enabling sales representatives to understand their customer behavior better and suggest aligned products.
Set realistic targets
Secondly, enterprises often overestimate what their business data analytics is capable of, while frequently underestimating the amount of time and effort that might be needed to make effective use of it, instead of just skimming the surface of the most broad insights, learning just the most generalized findings that applies to the whole firm.
Analyzing industry data can be a heavy task, just look at the insurance trade. There is ample data but most of it was compiled in paper format, so extracting it and making it useful is incredibly hard without an automated solution purpose-built for this task. Hence, organizations need to be realistic in how long it will take just to digitize the data and ensure accuracy alone, let alone studying and learning from it.
Build relationships between IT and biz units
A successful data analytics strategy, where the business truly realizes the value of data expenditure, involves the entire business, not just the business intelligence or IT departments.
IT and data leaders should spend time with the business role to understand the inherent pain points and opportunities, and once identified can connect those points to what the available data and tools are capable of doing, ensuring the widest impact and most pervasive value is gleaned the data strategy.
Uncovering the maximum out of the business data using an effective and actionable analytics strategy, is one of the surest ways to guarantee ongoing enterprise growth, helping to identify and then supply insights to help the business maintain the course, or evolve dramatically with changing market forces, as the case may be.
Having a sound strategy in place from the get-go will be a key facet of business survivability in the digital era.
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