\u201cThere’s an overload of data and a very short amount of time\u2026 frontline team managers, supervisors, executives are spending hours trying to mix all of this information together, but by the time they’ve done that analysis the opportunity has passed.\u201d<\/p><\/blockquote>\n
The manual approach of the past no longer matches the pace of the environment. \u201cThe speed to deliver has changed,\u201d Higgins said, \u201cUsing the manual, time consuming process does not make it easy for you to drive continuous optimization.\u201d<\/p>\n
Too Much Data, Too Little Clarity<\/h2>\n
Speakers acknowledged a repeating cycle. Enterprises face the same issues year after year but struggle to move forward. As one speaker put it, \u201cEven though we’ve had the same challenges and outcomes for the last 10 plus years, organizations are stuck,\u201d<\/p>\n
\u201cAnd why is that? Because there’s too much data that we don’t make enough sense of.\u201d<\/p>\n
Describing the challenge as \u201csuper hard\u201d, Higgins noted that \u201cdemands keep increasing and the challenges are rising\u2026 the speed to deliver has changed, and that’s what makes it difficult.\u201d<\/p>\n
In the rush to respond quickly, teams confront a wall of questions: \u201cWhere is my data? What data do I have? And how on earth do I go about it for any particular solution?\u201d Higgins said.<\/p>\n
The issue is not the lack of data but the lack of time, capability, and coherence to make it usable.<\/p>\n
\u201cThere is a massive disconnect between the strategic direction that a business wants a company to go in and actually, how do you get to that insight?\u201d said Andrew Tucker, Solution Engineer at NiCE<\/strong>.<\/p>\n\u201cYou know that the data exists for you to be able to make the decisions and roadmap these initiatives.\u201d<\/p>\n
Data silos make it difficult to move with agility. \u201cThere is a massive time lag between \u2018I want to achieve a certain thing,\u2019 and \u2018here is a roadmap for how you achieve that,\u2019\u201d Tucker added.<\/p>\n
To make matters worse, \u201cwe’re layering on an extra level of complexity\u2026 caused by every single vendor out there\u2026 pushing the AI narrative.\u201d<\/p>\n
Data Connection, Not Just Collection<\/h2>\n
When it comes to data management, teams often lack the ability to translate it into meaningful action. \u201cHow do we make a data-driven decision\u2026 to be able to influence that?\u201d Tucker asked, describing organizations that spend \u201cweeks and months worth of work\u2026 to say what is happening, why it’s happening, and how do I forecast outcomes?\u201d<\/p>\n
Building bigger datasets won\u2019t solve the problem. What matters is linking information in a way that reveals what\u2019s really happening.<\/p>\n
\u201cThis isn’t about data collection. This is about data connection,\u201d Higgins said.<\/p>\n
There is much debate in the industry about the level of data organization needed to be able to roll out AI-based applications.<\/p>\n
Kim Baker<\/strong>, Head of Operational Support Services at UK Housing Association L&Q<\/strong> warned: \u201cThere’s no point launching AI if your data is not right in the first place, because where’s it going to look to answer these questions?\u201d<\/p>\nWhen enterprises can get a handle on their data, they can draw out actionable insights, and AI can be a tool to help manage and extract data, making it AI-ready.<\/p>\n
\u201cData is becoming more readily available. It’s more insightful. We can make better data driven decisions as organizations,\u201d said Chris Rainsforth, Director of Learning and Innovation at The Forum<\/strong>.<\/p>\n\u201cSome people haven’t caught up with that data yet and are still sitting back in that old way of thinking. That change will continue, and it’ll continue to drive us.<\/p>\n
Marco Ndrecaj, Director of Customer Experience Management at Shared Services Connected<\/strong>, described large-scale operations facing overwhelming customer segments and datasets: \u201cYou’re like, oh my god, what am I looking at first? And I think that’s where the strength of AI comes to play.\u201d<\/p>\n\u201cLet AI take care of the data, take unstructured data, the structured data, and then turn it into insight. Once that’s done\u2026 let the human with empathy and with care to take it from there.\u201d<\/p>\n
As the conversations made clear, it\u2019s imperative that enterprises turn data \u201coverload into clarity,\u201d and strike the right balance between automation and human judgement.<\/p>\n","protected":false},"excerpt":{"rendered":"
Enterprises are tasked with managing an overload of data and limited time to act on it. That\u2019s one theme that kept resurfacing across the Contact Centre Expo at Excel London. Speakers pointed to the widening gap between aspiration and execution, especially as AI exerts increasing pressure to demonstrate innovation. As Natalie Higgins, Solutions Sales Executive […]<\/p>\n","protected":false},"author":11074,"featured_media":76558,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[61014],"class_list":["post-76554","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-crm","tag-artificial-intelligence","tag-big-data","tag-enterprise","brands_to_track-nice","editorial_type-interview","intent-evaluation","target_audience-industry-professional"],"acf":[],"yoast_head":"\n
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