Think back to Blockbuster, MySpace and Kodak. What do these businesses have in common? At first glance, nothing: they all operate in different industries. What connects them, though, is their tumble in the abyss of irrelevance.
Why do good companies dissolve? One plausible explanation is that management, upon facing new, disruptive situations in their environment, falls back on methods that were successful in the past. Call it short-sightedness, incompetence or complacency; either way, clinging to old formulas can be a glaring mistake.
Rather than providing frontline managers with complex models and Byzantine algorithms, simple and intuitive interfaces should make information available quickly and easily
Companies like Amazon have created a generation of utterly spoilt customers: all they have to do is click on a button. Two days later, their product at their doorstep, shipped for free. No wonder Amazon’s logo doubles as a smile. How do they do it? By digging into their goldmine – data – and using it to drive their strategy and build relationships with customers.
The volume of data available in the world is exploding and changing the nature of competition: companies with more access to data have a bird’s eye view of activities in their market and are less likely to be blindsided by a start-up in a garage. The secret lies in mapping three distinct landscapes: industry, competition and consumers.
Watching out for shifting business conditions, new opportunities and competitive threats lays the foundation for a predictive analysis, but scanning internal sources of unstructured data – e-mail enquiries, customer complaints, social media – is equally important. In today’s world, a combination of social media and a disgruntled customer means that your reputation is only a tweet away from taking a hit. How you manage your relationship with clients is the underlying hallmark of success, no matter your industry, focus, product or service.
Amassing vast quantities of consumer intelligence is the surest way of earning loyalty in the face of competition. Streamlining every interaction you have with a customer can generate useful information like their likelihood of using your product or service again.
That being said, building a competitive advantage does not originate with data; it begins with identifying a business opportunity. “Why” needs to come before “how.” Aimless data mining means that you corral huge amounts of data in an endless search of what it really means and how it can boost your performance. Rather, the right approach is a targeted strategy that begins with analysing all the factors that affect your performance, before asking the question “What bottom-line-enhancing decisions can I make if I have all the information I need?”
The volume of data available in the world is exploding and changing the nature of competition
The modus operandi lies not in embellishing old-world thinking with the latest available technology; instead, new processes and systems need to be built around the technology that is available. Businesses are tasked with carefully selecting the ecosystems that are most compatible with their goals. Business Intelligence (BI) tools were developed with this in mind: they interpret large volumes of data about market trends and competitor performance. Customer Relationship Management (CRM) tools, being consumer-centric, also provide opportunities to analyse buying behaviours and patterns. With their help, executives uncover trends, deliver insights and are able to forecast growth.
The modus operandi lies not in embellishing old-world thinking with the latest available technology; instead, new processes and systems need to be built around the technology that is available. Businesses are tasked with carefully selecting the ecosystems that are most compatible with their goals. Business Intelligence (BI) tools were developed with this in mind: they interpret large volumes of data about market trends and competitor performance. Customer Relationship Management (CRM) tools, being consumer-centric, also provide opportunities to analyse buying behaviours and patterns. With their help, executives uncover trends, deliver insights and are able to forecast growth.
Data-driven insights need to be designed for those who are on the actual frontlines, not for analysts or IT programmers. Rather than providing frontline managers with complex models and Byzantine algorithms, simple and intuitive interfaces should make information available quickly and easily. Analytics, when embedded into simple tools like a collaborative work application, workflow management software or even the cloud, allow for information to be more accessible, pervasive and transparent. This is when your data goes from being powerful to truly transformational.
Any new measure, strategy or tool invariably demands a new mindset. Executives have the responsibility of upgrading all employees’ skills and capabilities – failing to do so would be a disservice to their company. Continuous training and coaching will bridge the literacy gap within the organization. Ultimately, the objective is that change be woven into the fabric of the company.