Data Analytics. Our philosophy is that data analytics must enable organisations to solve specific problems and help create opportunities.

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1 Cyber Security Analytics Data Analytics Trends 2017 Performance Our philosophy is that data analytics must enable organisations to solve specific problems and help create opportunities. Tebogo Mokale Director: IT advisory

2 Senior leaders are recognising the importance of analytics The support of senior leadership is key in ensuring the adoption and sustainability of analytics efforts. By insisting on fact-based decision-making, and through the provision of resources, leaders send a signal that analytics is important to how the organisation operates. 44% 47% 8% 1% Strongly Agree Agree Disagree Strongly Disgree In our survey, 91% of respondents believed that senior leadership supports their analytics efforts, with 44% strongly agreeing that they receive this support. The leader charged with overseeing analytics varied across firms. In 53% of organisations, the CFO or CEO had overall responsibility for analytics, while the Chief Analytics Officer role was only present in 7% of the organisations. 25% of the organisations did not have a single leader charged with overseeing analytics, but interestingly, 71% of this subset included organisations where respondents believed there was senior leadership support. This may point on the one hand to the will to be analytics driven, while also indicating a lack of coordination. 35% 25% 18% 11% 7% 2% 2% Chief Financial Officer Chief Executive Officer Chief Information Officer Chief Analytics Officer Chief HR / Chief Operating Corporate Affairs Officer Officer No responsible person earmarked 2 Data analytics trends 2017

3 The focus of analysis is still on accounting & finance while the customer view is gaining ground The impact of analytics increases as more functions are involved and become insight driven. The level of involvement by function varied across firms, with accounting & finance, sales & marketing, and operations being the only functions where analytics was used at more than half of the organisations. Surprisingly, only 27% of organisation used analytics in the the supply chain & logistics function. Accounting & Finance Sales & Marketing Operations Customer Service Audit, Compliance & Risk Strategy Development & Execution Information Technology Human Resources Supply Chain & Logistics Research & Development None 2% 44% 41% 38% 33% 29% 27% 21% 53% 61% 76% The use of analytics within functions was also related to the leader that had overall responsibility for analytics. In firms where the CFO led analytics efforts, there was a clear bias towards accounting & finance, with the usage percentage increasing to 93% from the overall 76%. Where the CEO led analytics efforts there was a discernable shift to become more customer driven, with sales & marketing increasing from 61% to 73%, and customer service increasing from 44% to 60% and becoming more important than operations. Organisations where the Chief Information Officer or Chief Analytics Officer led analytics efforts were more likely to have a balanced distribution of analytics application areas, indicating the neutrality of these leaders. Data analytics trends

4 Slow progress to sophisticated analytical methods As expected, there was less usage of more sophisticated analytical methods, with organisations being more likely to perform simpler descriptive analytics. 82% 69% 51% 40% Descriptive Diagnostic Predictive Prescriptive Four out of five organisations made use of their data to understand what happened, with only 69% going further to use the data to understand the drivers of what happened. Far fewer organisations were likely to use analytics in a prescriptive manner that simplified decision-making. Furthermore, 68% of organisations stated that they had not implemented any form of big data which is congruent with the lower use of predictive and prescriptive analytics. The executive leadership had a bearing on the analytical sophistication, with organisations where the CFO led analytics efforts being less sophisticated than the average while those being led by Chief Analytics Officers being more likely to adopt predictive and prescriptive analytics methods. 4 Data analytics trends 2017

5 Focus remains on traditional data sources Surprisingly, nearly nine out of every 10 organisations felt that they possessed good quality data, and that they could rely of this data for analysis and decision-making. 87% 21% 66% 11% 2% Strongly Agree Agree Disagree Strongly Disgree As expected, those firms with perceived poor quality data tended to focus on descriptive analytics, with very little diagnostic, predictive and prescriptive analytics use. Furthermore, these firms tended to use analytics only in the accounting & finance function. Organisations primarily relied on internal and structured data for their analysis. Interestingly, those that believed the quality of their data was poor were as equally likely to use extenal structured data as they were to use internal structured data, which is indicative of efforts to source external data to complement what was perceived as poor internal data. These firms were also particularly averse to using external unstructured data. Structured Internal 78% Structured External 41% Unstructured Internal 29% Unstructured External 15% 18% Organisations were equally likely to source data from multiple un-integrated sources as they were to do so from a data warehouse. They were less likely to source data from single applications or spreadsheets. 18% 32% 33% Multiple Un-integrated Sources Data Warehouse Single Application Spreadsheets Data analytics trends

6 Spreadsheet is king, but interactive visualisations are gaining ground Organisations used multiple tools to perform data analysis with simple spreadsheets at 81% being the most popular. The use of bespoke, purpose built tools increased to 49% from 36% for those that perform predictive analytics. The use of a cloud based analytics platform was still relatively unpopular. These cloud-based platforms were more likely to be used by smaller firms, particularly those employing between 10 and 50 people. Analytics modules in ERP software were in turn more likely to be used by firms with 100 to 500 people. Spreadsheets 81% Bespoke, purpose built analytics tools 36% Widely available analytics tools offered by software vendors 27% Online / cloud based analytics platforms Analytics modules in ERP software 19% 16% Similar to the data analysis, the output of data analytics was most consumed using spreadsheets. Encouragingly, the use of dashboards is increasing and now exceeds the use of presentations and text based reports, indicating a shift to interactive modes of consuming insights. Those using text based reports were also likely to make use presentation tools such as PowerPoint. Unsurprisingly, the location of tools used to consume analytics is mostly on the desktop, which is consistent with the widespread use of spreadsheets. While the use of online and mobile platforms is still lagging behind, there was a positive relationship between the use of these platforms and the use of dashboards and visualisations. 92% Desktop based application 80% 55% 47% 34% Server based application 59% Online 34% Spreadsheets Dashboards Presentation and applications visualisations (Powerpoint) Text based reports Mobile 20% 6 Data analytics trends 2017

7 The demand for specialist analytics talent continues to outstrip supply and organisations are finding a compromise Firms had varying degrees of automation and repeatability of analytics performed. The leading approach to analytics was manual execution on a periodic basis followed by manually executing as and when needed. Automated execution was less prevalent. 49% Manual & periodic 46% Manual as and when needed 29% Automated & periodic 21% Automated & continuous Most organisations relied on the use of general employees with some analytical capability as opposed to analytics specialists. Very few organisations made use of external consultants for analytics purposes. The organisation of analytics teams was also varied across firms. The majority of firms either had no analytics team, or the analytics resources were spread throughout the organisation. Only 13% of organisations had a dedicated, centralised analytics team. Firms that had a centralised team had a higher likelihood of focusing on manual, as and when needed, analysis. On the other hand, decentralised teams were more likely to focus on manual and periodic analytics, implying a bias towards report driven analysis. Automated and continuous analytics were more likely when firms had specialists trained in analytics, whereas automated and periodic analysis was more likely to be performed by external consultants. General employees with analytical capabilities 87% 13% No analytics team Analytics Specialists 24% 19% 41% Multiple teams throughout the organisation External consultants 12% 27% Combination of centralised and decentralised teams Central analytics team Data analytics trends

8 Financial services and retail still lead. Small and medium sized firms are catching up 31% 18% 19% 6% 11% 9% 7% Less than 10 Between 10 and 50 Between 50 and 100 Between 100 and 500 Between 500 and 1000 Between 1000 and 5000 More than 5000 The firms were distrubuted across various sizes based on the number of employees. Financial Services Wholesale & Retail Trade Manufacturing Health & Social Services Real Estate Public Administration Education Hospitality Information, Technology & Communication Professional Services Agriculture Construction Entertainmnent and Recreation Transportation 8% 8% 7% 6% 5% 5% 4% 2% 2% 2% 2% 15% 16% 16% They were also spread across various industries, with financial services, wholesale & retail trade, and manufacturing being more prevalent. 8 Data analytics trends 2017

9 Our end-to-end analytics services are designed to help enhance organisational capabilities and support forecasting and forwardlooking financial growth and sustainability. Audit analytics Continuous control monitoring Forensic analytics Municipal revenue assurance Conflict of interest analytics Business network visualiser Market attractiveness solution Cash conversion analytics Forecasting Business performance insights Data profiling & cleansing Data migration reviews Data analytics trends

10 Contact us Tebogo Mokale Director: IT advisory & data analytics lead T +27 (0) E tebogo.mokale@za.gt.com Oupa Mbokodo Director & head: IT Advisory T +27 (0) E oupa.mbokodo@za.gt.com Michiel Jonker Director: IT advisory T +27 (0) E michiel.jonker@za.gt.com Sithabile Zungu Associate director: IT advisory T +27 (0) E sithabile.zungu@za.gt.com About Grant Thornton Grant Thornton is one of the world s leading organisations of independent assurance, tax and advisory firms. These firms help dynamic organisations unlock their potential for growth by providing meaningful, forward looking advice. More than 47,000 people across over 130 countries, are focused on making a difference to clients, colleagues and the communities in which we live and work. Grant Thornton South Africa App Download from the Apple App or Google Play store Grant Thornton South Africa. All rights reserved. Grant Thornton South Africa is a member firm of Grant Thornton International Ltd ( Grant Thornton International ). Grant Thornton International and the member firms are not a worldwide partnership. Services are delivered by the member firms independently.