How to create real value through data analysis – Interview with Director, Sean Taylor

It is widely accepted that the Covid-19 pandemic has accelerated businesses’ digital transformation strategies.

These investments are not made for their own sake, but to have a positive, measurable impact on a business. If one sits down with any C-suite, their reason for embarking on the journey is almost always to unlock value to become more competitive.

Using technology such as business intelligence (BI) software to create value is, at its core, fairly simple. One would look at either supporting top line growth by finding new opportunities inherent in a company’s data, such as cross-selling, upselling, and reducing customer churn, or by driving cost reduction, which supports the bottom line; or both.

However, while the concept may be simple, diving head first into patchy solution implementation without adequate analysis of the tools and technologies available to support the overall business processes won’t result in the elusive creation of value, and – as one would imagine – this leads to much frustration.

Let’s start at the beginning. One of the most common challenges in enterprises is a siloed approach to data. This is a legacy hangover where one would find business functions such as manufacturing, procurement, sales, operating almost as stand-alone entities.

Different people in different departments extract similar information to generate reports. In essence, you may find an input in one silo is an output in another. These people extract this data and then enrich it offline, most often in the form of an excel spreadsheet, which they then prepare for reporting purposes.

It becomes apparent then that each of these data owners can become fixated on their own silo but not appreciate how it impacts everyone up and down the line in the organisation. The information value chain is only as strong as its weakest link.

At all these links in an organisation, the data owners are extracting core elements from the system and enriching it outside of the system, which defeats the entire objective of a considered BI strategy: a single version of the truth.

With this approach of end users who individually try to enrich the data and package it in a presentable format, an organisation loses the ability to disseminate important insights widely. In effect, the creator of the spreadsheet inherits ownership of that intelligence, and it tends to live with that person for the duration of their stay at the company. When they leave, this intelligence tends to get lost which creates a gap in continuity.

This is compounded by a trend gaining momentum, and which has been exacerbated by the pandemic. As people leave organisations, those that remain tend to take on more responsibility. One of the effects of this cost-saving strategy of not rehiring is that the staff who remain become stretched and begin juggling tasks. When a workforce has less time, the gathering of insights, enriching it and presenting it, becomes compromised.

How to use data to create value in this environment

It is therefore no surprise that businesses around the world have become receptive to the concept of a single source of data that has been vetted for integrity and accuracy, from which all reporting and analytics are drawn. Beyond this, by providing a workforce with a flexible tool that can take out ad hoc insights and answer specific questions, the business enables itself to become lean and agile. Further efficiencies are gained through automating targeted report distribution.

  • Expose hidden insights broadly – Organisations can maximise value by making hidden insights apparent. But to whom? BI, and the insights it delivers, unlocks the highest value when it is adopted broadly, and especially when it is integrated with standard operating procedures.
  • Data becomes systemised – To achieve this, there needs to be a thorough review of the information value chain that identifies the existing data enrichment opportunities in the organisation, and specifically where end users enrich it offline. Ideally, an organisation wants to work with a partner that can customise a tool so that the solution extends its reach throughout the business, and the data becomes systemised into a formal governance structure. Pulling out a single version of the truth and disseminating more widely relies on data preparation processes that ensure all data sets are relevant, accurate and usable.
  • Understand relationships between data sets – Naturally, there are various solutions, some of which are limited to a query-based approach. This is not ideal. It is crucial for a BI tool to understand all the relationships between different data sets in a business and then expose hidden insights that would ordinarily be missed. When a BI solution is built it must be designed so that anomalies are highlighted easily and so that hidden insights prompt users to ask the right questions.
  • Actionable insights – The point of this is to develop self-reliance in the organisation. This means the insights extracted must be actionable. For instance, if a retailer – for example – can use its BI software to predict out-of-stock scenarios across various sites, it is empowered to manage its stock and cash flows proactively without the burden of key human resources needing to drive this. That’s value.

With an array of products, tools and service providers in the market today, organisations should spend time carefully evaluating the options available to them in terms of their overall data and information value chain. Whilst budget is an important consideration, the cheapest solution will not necessarily yield the quickest or highest return on investment.

It is important to consider the overall data landscape, and approach the BI implementation with a clearly defined strategy, choosing a toolset that will provide a single version of the truth, quick time to value and actionable insights throughout the organisation.

Read the original publication on IT-ONLINE.

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