C-Suite Intelligence 14th September 2020

Winmark's C-Suite Intelligence service provides news, content and research to help leaders across all C-Suite functions overcome the significant challenges they are currently facing

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How can leaders prepare for the business impact of automation and AI?

Information Age

AI and automation are expected to drive the biggest business and societal changes over the next decade. 

By 2030, it is predicted that more than 10 million UK workers could be under-skilled in digital, decision making and communication. At current estimates, the digital skills deficit could be costing the UK as much as £63 billion a year.

Successful business leaders see AI as a tool for scaling business operations. Data can be used to plot customer journeys to identify key touch points for automation. Using AI to anticipate customer needs enables your sales team to focus on complex requests and building human relationships – serving more customers and providing a better experience.



How Tesco used AI to help deal with lockdown demand

AI Business

Tesco CTO Guus Dekkers explains how smart use of big data and the latest AI have helped him to meet the challenges of COVID.

“We've seen probably more change in the last handful of months than we've seen in the last couple of years. We have been forced to adapt and find ways to make sure we can continue serving the nation and make sure that there is access to food for everyone. Many of the changes which have been triggered in recent months are not going to go away.”

Where is AI making a difference in market analysis?

AI Multiple

AI simplifies analytics and makes it more Natural Language friendly: it takes longer to build models than just asking simple questions. New Natural Language powered analytics platforms can create Natural Language interfaces to complex queries. For example, an AI analysis product by Wacul-ai converts complex Google Analytics results into simple, understandable phrases.

AI can help merge disparate data sources to identify patterns and predict future results: with the help of historical data, AI is able to learn about the customer’s past behaviour and determine the probability that a customer will churn. With the help of such analytics, marketers are able to determine the future course of action for the organisation. Domo is an AI vendor that provides a solution for merging marketing data for analytics. 

AI paves the way for Social Media Analytics: AI technologies like Natural Language processing and computer vision aim to  understand, analyse and generate responses, which ultimately enables social media marketers to develop meaningful marketing outcomes and highly curated insights in real time. For example, AI vendor unmetric allows companies to analyse any competitors’ social media activity in detail, helping uncover new social media strategies.

AI enables automated decision management: analysis takes time to complete and implementing results of analytics is time consuming and not scalable. AI techniques can be used to build models that combine analytics and decision making, continuously improving marketing effectiveness.

How companies can transform information into insight

Strategy + Business

Organisations can think of their data and analytics journey as progressing along a maturity scale. At each stage, companies build their proficiency in six critical organisational elements:
  1. Business decisions and analytics: Prioritise analytics insights that fuel the business strategy, not those that just report what’s happening.
  2. Data and information: Let the data tell a story through the flexible integration of multiple data types, rather than forcing the data into a predefined model.
  3. Technology and infrastructure: Build tools that support the analytics ecosystem, including AI, and democratise insights through analytics-as-a-service (AaaS).
  4. Organisation and governance: Establish an operating model to empower the use of governed data and analytics.
  5. Process and integration: Ensure insights are rapidly integrated into decisions through an aligned, agile process.
  6. Culture and talent: Instil a data-driven culture that blends business knowledge and analytics insights across all levels.
Certain elements will play a more visible role at different points along the maturity scale but ultimately, excellence in all six is required to realise the full value of a data and analytics transformation.

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