Data & Analytics

• Making data the igniter of decision making: End to end processes with data (Product, Marketing, Sales, etc.).
• Generating actionable insights from data to improve performance across business.
• Installing a data-driven culture throughout the organisation.

On-Demand Presentation

• Examining which company dynamics impact the way in which you structure your team and why they matter? 
• Team structure discussed – centralised, de-centralised or federated? Is there a one size fits all approach? 
• Establishing remit and avoiding territorial conflict – Examining the overlap with internal functions and other C-Level positions, where is the ideal location for analytics within an organisation?  
• Case study examples – leveraging assets across different business units, eliminating redundancies, and targeting highly specific, individual needs across the enterprise. 

• What is the typical road to becoming a Chief Data Analytics Officer, is there one? 
• Where is the optimal place for a Chief Data Analytics Officer to sit within the business, what should their remit be and what core skills do they need to be successful? 
• What key strategies do you need to employ to drive engagement with the wider business, whilst also fostering an inclusive, supportive and curious culture within your team?   
• Working with internal stakeholders to drive support and innovation – Examining the importance of relationships with CEO/CIO/CTO/CFO/COO as well as outreach and education programs with the wider business. 

• Discussing the ecosystem of data warehouses/lakes/the cloud, what is needed to build an effective analytics environment. Examining the benefits and pitfalls of each approach. 
• Exploring what is needed in this new world of analytics, with ever growing data sets, fringe data, upgraded tools and processes and security threats, how do you build the right architecture to handle this whilst remaining agile and adaptive?  
• Do you have access to the data you need, and if not how do you go about gaining access and organising that data?  

• What are the real challenges to driving large scale commercial value, and how are traditional companies solving them?  
• What are the obstacles to rolling out at scale and what are the sets of complimentary capabilities that data science teams need to develop to be effective on a large scale commercial basis? 
• The importance of inter-departmental partnerships – Which key departments do you need onside?  
• Creating an agile approach and culture to drive innovation.  

• Examining organisational and technical infrastructure and what this means for integrating analytics within your business and analytical delivery. 
• Exploring strategies for connecting data management with business disciplines and building a data strategy that works at all levels of business. 
• Breaking down silos: Integrating projects and solutions across internal business disciplines. 
• Balancing complexity with operationalisation – Simple and elegant can be your friend. 
• Examining the importance of creating tools, systems and models that have a holistic view of the business. 
• Empowering leadership from the top and ensuring reporting structures for CDOs and CAOs can drive real organisational change.  

Live webinar panel

• Where do you draw the line between analytics and IT, in what ways do the functions overlap and where should analytics sit within your organisation?  
• You can’t marry your tech partner, you have to date them! – Discussing the importance of involving the IT department in your activities. What strategies can you employ to encourage and foster harmonious working relationships with internal customers and stakeholders?  
• Discussing the importance of involving the IT department in your activities, clearly explaining the benefits and strategies for keeping them on side.   
• Strategies for finding mutual respect mutual understanding – battling the fear of becoming obsolete. 

• Assessing the integrity of your data – Understanding how to identify and address the most common causes of enterprise data quality problems and discussing strategies for data cleansing. 
• Does the democratisation of data defy governance? How to approach data governance in the new world of self-service analytics. 
• Debating data ownership – How to ensure a consistent approach to data recording and governance, and how to balance the issues of data access for business lines without compromising security? 
• Discussing the reality of achieving governance (for fully cleansed, conformed and trusted data) whilst also leaving room for and encouraging innovation in the organisation fueled by the big data world

On-Demand Presentation

• Discover how to turn skeptical executives and employees into advocates of analytics-driven decision making and action, by understanding what you can control and what you can influence.  
• Learn about how to leverage an energised centralised data and analytics team to drive culture change and lead by example.    
• Watch out for the roadblocks, challenges and potential setbacks along the way 

• The art of storytelling – The analytics leader as the bridge and translator – Examining why these skills are so important. 
• Examining the importance of tailoring the communication of your knowledge and insights for your audience. 
• Discussing the importance of having internal evangelists as well as a business partners that understand the capabilities of the data and insights. Creating an active feedback loop with your business. 
• The importance of knowing which questions to ask of your data – the business maybe asking the wrong question, prompting the wrong solution. 

• Creating ‘win-win’ scenarios through cross industry and academic partnerships  
• In what ways can specific partnerships help drive growth and innovation? 
• What communities are out there already that enables data sharing, and innovation?  
• Establishing collaboration between academia and business – How best can we facilitate data science knowledge exchange between academia and business to benefit both sides and train the next generation of analytics leaders? What skills will be needed in the future? 

• How can the way in which your department is structured impact the value you can add as well as your pace of change and implementation? 
• In what ways can you optimise business and operational processes to drive enterprise wide innovation? 
• It’s not only about insight – Discussing the journey from insights to decisions at scale to drive commercial outcomes. 
• The analytics Holy Grail – staying ahead of market trends, increase competitive advantages through prediction and prescription, whilst improving customer satisfaction, engagement, spend and increasing end-user productivity. – How do you get there? Case study examples discussed. 

• Facing the challenge of implementing enterprise-wide data strategies? Learn how to deliver tangible wins without sacrificing security, agility, and transparency.  
• Deploy a solution that leverages and extends existing investments while meeting changing organisational needs.  
• Best practices for taking your data strategy through the last mile.  

• How can business value be shown at board level; both in quantitatively and qualitatively? 
• How do you quantify efficiency savings vs. cost savings and revenue? 
• Overcoming the hurdles to monetising your data and lessons learned on the journey. 
• How do you attribute business success to actual data?  
• Selecting the most important business challenges to solve using data science techniques to engage stakeholders and secure future investment. 

On-Demand Presentation

• Understanding the complexity of methodologies, the increasing importance of Machine Learning, and the scale of data sets. 
• Transforming how you organise, operate, and create value. 
• Exploiting advanced analytics to offer the maximum return. 

• Examining the opportunities of digital and third-party data – Determining what’s relevant, for how long, and its practical applications for your business. 
• Strategies for determining relevancy and actionability – Hearing through the ‘data noise’ – For how long does digital data remain relevant, and for what duration should it be stored? 
• Is dark data a greater opportunity then third-party data? 

On-Demand Presentation

• As the use of data & analytics grows, what are the potential ethical dilemmas and reputation risks that can arise, and how should these be mitigated?  
• Aligning data selection/availability and algorithms with corporate values. 
• Dealing with bias – What steps can be taken to avoid biased models and algorithms leading to discriminatory decision making?  
• Communication with customers – How can we ensure transparent use of data in which customers are fully informed? 

• Data monetisation – Turning your data into a true area of value generation. 
• At what point does your data become a capital asset and how do you value it? 
• Strategies for monetising customer interaction data – The importance of lifetime customer value and not just short term gains. 

On-Demand Presentation

• Discussing strategies for keeping current in a technological environment which is rapidly changing and developing. How do you determine what technology to invest in, and how can you stay current without tones of investment?   
• Bleeding edge technology – Where is the optimal point to be on the technology adoption curve? And how do you balance risk vs. reward whilst trying to stay current? 
• Which tools should you have within your analytical tool kit, and how do you go about building a winning portfolio of technology and tools? Which areas are worth more investment that others? 
• Preparing your analytics capability for the present and the future – Balancing longevity and new technology. 

• Assessing the modelling and analytical environment. 
• In a world where everyone is using analytics, how do you really compete? Discussing strategies for maintaining your competitive edge. 
• What new tools and capabilities are available and how is it impacting ‘the bones’ of modelling – data, tools platform, monitoring. 
• Discussing data vs. modeling and how they have evolved – which is going to gain you a bigger advantage in your market place and how do you manage them? 
• Assessing the availability of new data sets, how do you decide what is relevant for your business? 

• With new technologies come new possibilities – In what ways can new technological advancements transform your business and provide new opportunities?  
• How will changes in company culture and hunger for data and analytics shape the future of businesses and in what ways might this impact company structure and expectations? 
• How is new technology going to shape the team of the future and change needs? And what are the possibilities in relation to tackling the skills shortage? 
• Looking to the future – which new technologies are going to fizzle away and which is going to be impactful?