Pang is responsible for organisational transformation, architect and solution refinement, and new business creation with a focus on cloud and big data. With his broad international experience acquired over the last 24 years across all technology solutions spanning infrastructure, security, business intelligence and strategic planning, Pang has served a diverse range of clients with many of them being Fortune 500 companies.
Pang is responsible for organisational transformation, architect and solution refinement, and new business creation with a focus on cloud and big data. With his broad international experience acquired over the last 24 years across all technology solutions spanning infrastructure, security, business intelligence and strategic planning, Pang has served a diverse range of clients with many of them being Fortune 500 companies.Read less
In the 1976 movie The Pink Panther Strikes Again, the hapless police inspector Jacques Clouseau, played by Peter Sellers, checks into a hotel. He walks across the lobby where there is a small dog lying down. Clouseau turns to the nearby hotel clerk and asks: "does your dog bite?" The clerk answers "no", whereupon Clouseau bends down to stroke the dog, which promptly bites him.
"I thought you said your dog did not bite!" exclaims the angry and somewhat shaken police inspector.
"That is not my dog," responds the clerk.
It seems that even when you think you've asked the most important question, and have been given a truthful answer, you can still end up getting an unwelcome surprise.
Instances of small dogs attacking businesses are thankfully quite rare. Not so the problem of unreliable information.
"We live in an age of data." says Patrick Pang, Head of Solution Consulting at JOS. "Businesses and individuals are surrounded by it and are creating it in ever increasing amounts - day-in, day-out, contributing to a data deluge."
The era of Big Data has thrown the information floodgates wide open; data that was once impossible to capture or interrogate is now increasingly commonplace. From the usual suspects - sales figures, financial data, and so on - through to unstructured data such as contact centre notes and customer feedback, but also social media comment.
"Businesses are surrounded by data." says Pang. "It can easily become little more than unreliable background noise unless it is effectively marshalled."
Business intelligence (BI) is not a new concept. The earliest known use of the term was in a publication called Cyclopædia of Commercial and Business Anecdotes, which dates from 1865 and was written by Richard Millar Devens. It was first used in the technology industry by IBM in the 1950s.
We can think of BI as the interface through which a business can make sense of all the information and data within every part of its organisation - it is a way of asking questions. Structuring those questions - or queries - however, is not as simple a task as it might superficially seem; one does not get to use natural language, or better still, to speak one's queries to a BI system.
While it may once have only been an option for large organisations, that's no longer the case; increases in performance and lower price points have opened up BI's advantages to a wider audience. Yet there remain some very real challenges facing many organisations using BI.
Since the earliest days of computing, getting data into a system has always been much easier than getting information out. Reports have to be built to support the business’s needs, and the corresponding queries behind those reports have to be structured via lines of code.
From sales performance data to cost analysis, there is a consistent and constant need for specific types of information. Reports can therefore be written once and then left to run whenever required, providing actionable business intelligence on demand.
It could even be the case that some of those reports and queries pre-date the systems they run on, having been created within an organisation’s original BI system. One of the unintended consequences of this can be that the integrity of those query results and reports, which were built using legacy systems, may become unreliable where updated enterprise IT systems have been subsequently deployed.
Personnel changes can really exacerbate this situation; if you're relying on legacy systems, and perhaps there's just one person left in your team who remembers how that system works, what will you do when they leave?
Modern BI systems have been built with agility in mind and overcome many of the difficulties with legacy systems; they can be rolled out and made operationally ready within shorter timescales. That emphasis on speed and agility extends into the ease with which new reports and queries can be created, and new business needs or initiatives can be brought into the BI fold.
This is particularly important if your business is affected by specific seasons or events in the calendar - whether that's major retail events like Singles' Day or Black Friday, or the need to bring a new business unit on stream quickly.
As Pang explains: "There has been a revolution in BI which means that business function leaders in mid-market companies and SME-sized organisations can begin to take control of their data and transform information into insight. As technology continues to trickle down, greater power to interrogate data in a fast and effective manner is becoming available. The time taken to create and run reports can be reduced by as much as 70% in some cases, and with BI automation there is scope to reduce complexity too."
"Dashboards and reports are commonplace within BI tools, but can still place heavy demands on business users to take the information delivered by reporting tools and dissect it to find actionable insight. With so much data accumulating non-stop, it is a real challenge to know what you must pay attention to and what you can afford to discard."
Enterprise-scale BI has a reputation for complex, time-consuming installation, requiring many man-hours of consultants' time to ensure a thorough understanding of the business, its market, and its needs. This is no longer the case and the mid-market stands to win thanks to increased ease-of-use, faster deployment, and more rapid report generation.
Automation will allow businesses to ensure the right data is pulled into view at the right time to make sure the answers are relevant and useful. It could be an analysis of competitor performance against a fixed set of criteria, or it could be an evaluation of weather trends or social media mentions of certain keywords, compared with previous years' sales data.
If one of the monitored data points shifts significantly this can trigger a report containing a valuable, real-time, snapshot of events. Automation can also help avoid assumptions, simplifications, and biases that even the most conscientious of people can be guilty of when interpreting data.
"Maybe you want to track marketing campaign success by monitoring sales in a particular store, or redemption of certain codes, and overlay those results with other data - will changing weather play a part, or how about introducing complementary product suggestions?" Pang explains. "Being able to assess such factors was unthinkable not long ago, and until even more recently, unaffordable for all but a few."
The key thing businesses want to achieve from the combination of all their available datasets is valuable, actionable insight – understanding what it is they need to find out, knowing the right questions to ask, and being able to put the answers they get into their proper context. And by doing so, of course, organisations would then be able to avoid getting bitten by any unpleasant surprise.
"Enterprise-scale BI has a reputation for complex, time-consuming installation, requiring many man-hours of consultants' time to ensure a thorough understanding of the business, its market, and its needs. This is no longer the case and the mid-market stands to win thanks to increased ease-of-use, faster deployment, and more rapid report generation."
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