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Do most modern tech purchases end in regret?

Business analytics has evolved into an all-embracing business intelligence function that predicts the outcome of decision-making in future scenarios.
Paul Stuttard
By Paul Stuttard, Director, Duxbury Networking.
Johannesburg, 02 Aug 2022

A colleague recently drew my attention to an unattributed online-delivered statement. It contained the bold claim that “most tech purchases end in regret”. 

The substantiation was that as technology continues to become more critical to the business, technology customers have access to more options and information than ever before, which leads to more instances of buyer remorse.

There is little doubt that technology is increasingly critical to business success. The fact that the work-from-anywhere distributed operational model so successfully achieved its objectives during the pandemic − and continues to do so in the post-COVID era − is clear evidence of this.

Now, as organisations re-energise their efforts to build business success, often on a global stage, they are faced with a wide range of technological options that produce, manipulate, process, store, communicate or disseminate information.

In order to design, manufacture and market a product or provide a service, vast technological resources and many high-tech devices are often needed before goals can be fully realised.

Currently, companies are in the process of amassing large amounts of data concerning potential markets, existing customers, competitors, prospective collaborators and more.

Today, organisations have the ability to be increasingly discerning. In other words, they are able to gain the knowledge needed to maximise investment returns more rapidly than ever before by expertly mining and optimising the information they gather.

I agree with Meghan Brockmeyer, head of global strategic accounts marketing at LinkedIn, who believes that today’s technology buyers are more enlightened than their immediate forebears.

“From how they seek information, to how they evaluate vendors and ultimately make purchasing decisions, today’s enlightened tech buyers are defined by a drive to make the best possible decisions for their business,” she notes.

Today, organisations have the ability to be increasingly discerning.

But is there a down side? Could an emerging company, intent on establishing a foothold in its sphere of activities through the use of technology, take a wrong turning and head in a counter-productive direction or encounter an unexpected dead-end?

According to Brockmeyer, “influencers, implementers and end-users have greater ability to wield influence and authority than in years past”. What does this mean? Could a small group of vociferous advocates within an organisation sway a critical decision or two in its favour? And could this result in disaster?

She says research shows that more than 85% of corporate technology purchasing decisions are made by executives in tech-focused roles, including IT, operations, engineering and research.

Perhaps one of the best ways to obviate a feeling of regret or anxiety after making a purchase among this band of often-talented professionals is to turn data into a competitive advantage by advancing the analytics skills of this group of experts.

Many organisations are already familiar with the application of analytics in the security arena. Security analytics is the process of using data collection, aggregation and analysis tools for security monitoring and threat detection. Security analytics solutions can incorporate large and diverse data sets into their detection algorithms.

Similarly, business analytics is able to guide businesses to success by exploiting the value of individual solutions.

Business analytics has evolved from an application that focuses on simply highlighting features, facts and figures into an all-embracing business intelligence function that predicts the outcome of decision-making in future scenarios. It can even assist in the decision-making process itself.

This results in a growing affiliation between technology and business functions within an organisation which are now able to integrate more directly with business processes to fuel innovation for the future.

In this light, the role of technologies such as software-defined wide area networking (SD-WAN) is key. SD-WANs are paving the way for organisations to adopt the next-generation of cloud-based applications, while building strong foundations on which real-time artificial intelligence (AI) will be able to operate across a variety of customer channels and touchpoints.

SD-WANs are also showing the way towards the universal adoption of predictive analytics (PA). This advanced form of AI uses current and historical data to predict future behaviour patterns, such as demand cycles.

In preparation for the adoption of AI and PA, a cohesive data and analytics-centric strategy must be developed by businesses in order to – for example − spotlight aspects of production procedures or customer service that might be improved.

In a previous article, I suggested it won’t be long before organisations begin employing “analytics officers” tasked with laying the groundwork for a data-and-analytics-centric culture designed to give their organisations a competitive edge in the marketplace.

Their presence will also present a welcome buffer against possible confusion in the ranks of senior executives and decision-makers who may be losing touch with the features of new solutions and the benefits associated with the latest innovations.

Analytics officers will be able to draw attention to more “over-the-horizon” opportunities and identify more hidden risk factors, thus leading to far fewer instances of buyer remorse.

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