Mirror, mirror on the wall…

Business intelligence and big data are considered meaningful
technologies that have the power to show your business as it truly is, and give it a trusted pathway towards its potential.
By Tamsin Oxford
Johannesburg, 22 Mar 2023
Michael Grant, Synthesis Software.
Michael Grant, Synthesis Software.

McKinsey believes that big data and business intelligence (BI) are technologies essential to business growth and innovation, describing them as ‘meaningful tech trends’ that deliver a convincing case when it comes to tangible business value and longterm benefits. The firm says these technologies are shaping the edge of innovation and accelerating the core qualities of the digital era – granularity, speed and scale.

However, the waterfall of new technologies, solutions and approaches can be deafening. Companies are numbed by the constant barrage of, ‘Oh, use this tool!’, ‘Hey, big data is everything!’, and ‘Look at this shiny toy’. It’s hard to find a pathway through the hype, one that will actually deliver the insights that will allow for the business to make smart decisions.

This is echoed by Forrester in its 2002 report ‘The Future of Business Intelligence’, which pointed out that most of the business benefits promised by BI platforms remain aspirational. In 2021, only 20% of decision-makers said they had seen increased revenue thanks to data and analytics. Most blame the limitations of people, data, and strategy, and many struggle to see the value of their BI investments. Forrester believes that legacy BI is dead. It believes the biggest challenges affecting the company’s ability to get value from its BI and big data applications are silos, lack of context, standalone applications that don’t go the last mile to the decisionmaker, and limited access to any but the well-trained few. This means that it’s time to shift the narrative from the dead legacy platform that lives in dashboards and thrives on complexity, to solutions that deliver the key words of impact, personalised, pervasive and unified.

Translated, this means that companies should be focusing on BI and big data approaches that integrate metadata, create connections between insights and actions, and leverage automation and machine learning capabilities. Gartner shares this view. The firm underscored the value of AI, data sharing and data fabrics in creating systems that allow for decision-makers to not just embed resilience, but surf the choppy waters of uncertainty with greater confidence. Gartner also highlighted metadata, augmented digital worker platforms, adaptive AI systems, and composable data and analytics as key trends shaping how companies can fully realise the potential of data within the business.

First-party data drives personalisation and allows marketers to draw from the guest experience across all touchpoints on the buyer journey.

Stewart Smith, Middle East and Africa, Sojern

So how do you choose? How do you shove aside the noise in favour of a relevant solution? The answer lies in one context. This is what should define how the organisation approaches its investments and planning, and how it squeezes the value from the data to ensure valid and relevant insights that influence decision-making and growth. According to Forrester, ‘seamlessly embed relevant insights into all digital workspaces and systems of work’. Gartner believes that ‘by 2025, context-driven analytics and AI models will replace 60% of existing models built on traditional data’.

The pace of technology won’t change; what has to change is how technology leaders create ecosystems that can embrace and leverage this change to remain competitive and ahead of the game.


You are the fairest in the land

Brainstorm: What BI solution have you been using and has it delivered value?

Bob Lafite, managing executive: ICT Strategy within ConCom, BCX: BCX uses the BMC suite for BCX AIOps, where it looks at the information on the client’s networks to monitor the large number of devices connected. For example, we use it to detect when clients are down. This data is then stored in a secure database to be analysed for trend prediction and possible failures in the network.

Chris Wiggett, head of Data and Analytics, Dimension Data Southern Africa: Power BI, Salesforce and SAP Analytics Cloud.

Tim Wood, executive head: IS and IT, Vox: Within our business, we are definitely on the path to shifting towards Power BI like many other entities in our larger Vivica Group. At Vox, we have built bespoke and customised ways of exposing data from various databases and then presenting the data to different teams. As one would expect, there are still users who prefer to receive their data in Excel format. Rather than this being a problem, it allows them to run their own queries and filters. At the same time, we use the more advanced SSAS (SQL Server Analysis Services) analytical services to build models that optimise data for querying.

Stewart Smith, MD, Middle East and Africa, Sojern: We make use of our hotelier clients’ first-party data to drive revenue and build stronger relationships with guests. First-party data drives personalisation and allows marketers to draw from the guest experience across all touchpoints on the buyer journey.

Brainstorm: How have big data and BI changed the way you do business?

Michael Grant, CTO, Synthesis Software: We used information from direct sales and supplier networks to model customer behaviour with more precision. The better sales forecasts were used to optimise the entire supply chain, resulting in less capital deployed into the logistics network. This had a monumental impact on the business, with a significant improvement in its efficiency.

Chris Wiggett, Dimension Data Southern Africa: While we fully appreciate the importance of experience and business intuition, we also recognise the ever-growing requirement to base decisions on sound, data-driven information. Our continuous investment in data and data platforms has enabled an environment where all relevant sources can be processed and analysed efficiently, enabling accurate, relevant and low-latency business decisions.

Tim Wood, Vox: Intelligence generated from data has enabled us to understand ourselves better, both operationally and on the customer-facing side. Similarly, it has enabled us to build insights around our customers, which supports proactive customer engagements. Ultimately, it means a smoother-running business, making intelligent decisions and delivering a better customer experience.

Demetrius Ganesh, head of big data, MIP: We started looking at how we could embed better BI into our solutions, choosing Yellowfin as our tool of choice because of the ease with which it can be embedded and customised, and the value it offers users. Yellowfin provides better contextual analytics.

The data game-changer

Logistics firm Unitrans unifies its data with a smart solution that taps into BI and innovation.

Unitrans Supply Chain Solutions (USCS), a diversified supply chain solution company, shifted its logistics gaze to its data in a bid to connect the digital dots across multiple silos and systems. As Christo Röder, Finance Innovation manager at USCS points out, he realised that rolling out the business intelligence (BI) system would be like taming a wild animal.

A brief history of big data

8 000 BC The earliest evidence of using data to manage business in Mesopotamia
1662 John Graunt develops records of mortality in London
1889 Herman Hollerith invents a machine that can organise census data
1926 Nikola Tesla predicts people will carry data on an instrument in their pocket
1928 Fritz Pfleumer invents a way to store information on tape
1937 Franklin D. Roosevelt’s administration orders the first major data project and IBM gets the gig
1943 First data processing machine, Colossus, is developed to decipher Nazi codes in WW2
1946 ENIAC arrives on the scene
1965 The US National Security Agency builds the first datacentre to store 742 million tax returns
1976 Seymour Cray reveals the world’s first supercomputer
1989 Tim Berners-Lee invents what would become the World Wide Web
2001 Doug Laney from Gartner coins the three Vs – volume, variety and velocity
2005 The term big data is coined by Roger Mougalas
2006 Hadoop from Yahoo! arrives
2008 CPUs the world over process more than 9.58 zettabytes of data
2010 Eric Schmidt drops the data mic with: “There were 5 exabytes of information created by the entire world between the dawn of civilization and 2003. Now that same amount is created every two days.”
2011 The Obama administration announces the Big Data Research and Development Initiative
2016 90% of the world’s data was created in the last two years
2023 2.5 quintillion bytes of data is generated daily

“Each entity, each division, each customer had a different system and some of those beyond the South African borders didn’t have internet connectivity, using a 3G line at best,” he says. “The company was also sitting on heaps of data that was largely underutilised and slow processes meant that the data being used wasn’t very effective. It could take us two weeks to just prepare basic data and, in this industry, that’s essentially useless for decision-making.”

Enter Qlik. With its relatively urgent need to gain visibility into, and control of, the data, Röder extended the company’s existing Qlik implementation to resolve the data and intelligence challenge. The company had started using QlikView a few years previously, allowing for Röder to clean up the data, find errors and structure it more effectively. Collaborating with partner B2IT, Röder developed a platform that was a combination of QlikView and NPrinting and then supplemented this with Qlik Sense to manage data flow.

“Qlik is flexible, it can talk to different sources, and it can work with basic CSV files to extract the data and the insights, which means teams can upload information from anywhere, even a PC in a container,” Röder says. “It was simple and cost-effective, and it changed how we lived with our data.”

The solution provided USCS with daily reports that included rankings, exception reports and so much more. It became instantly popular with employees because it was easy to use; within a year, everyone was using it. The deployment is classified into two main categories – internal and customer facing – and has delivered measurable improvements to reporting, accuracy and operations. It has also transformed cross-referencing, data sanitisation, and data quality and integrity.

“Managers can make more effective decisions, we get the information faster, which mitigates risk, and we even found a R2 million truck we didn’t know existed, all thanks to the data,” says Röder. “We now have an environment where people are able to think innovatively on a continuous basis and in every area – from customer to internal efficiencies; it’s a game-changer for us.”


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