Strategic advice & alerts to leverage data analytics & new technologies
Leverage data and the technologies that generate it, from IoT to AI/machine learning, wearables, blockchain, and more, to improve decision-making, enrich collaboration and enable new services.
This Update highlights the role of the cloud in big data strategies. In particular, it builds on the characteristics of the cloud and how big data analytics can utilize them.
According to our research, the biggest obstacle to enterprise artificial intelligence (AI) adoption is a lack of available experts skilled in AI development. So how are organizations meeting or planning to meet their AI implementation needs? Results from our ongoing survey examining the adoption and application of AI technology in the enterprise — based on the initial responses from 107 participating organizations worldwide — helps to somewhat clarify this question.
A new breakthrough discovery — the Wallet Allocation Rule — is solving the CX metric and ROI problem and opening the door to strategic advances that elevate the role of CX for leading companies by changing the way we track metrics, understand key driver analyses, define marketplace differentiation, and develop strategies to win share of wallet.
Merchant mobile payment applications represent a first step toward frictionless commerce but achieving this initial milestone has been challenging in the US.
As you read through the articles in this month’s issue, we invite you to consider the customer experience that your organization provides and what lessons our authors offer for improving CX and making it great.
Data-driven decision management is an approach to managing business that focuses on decision making that can be backed up with verifiable data.
In this Executive Update, we present the Data Value Map (DVM), a discursive template that facilitates the development of a shared understanding around data. The template helps enable open conversations and a co-construction of understanding between the parties involved, which can promote a value-driven approach to data projects.
A key question I’ve had for some time is: how well are enterprise AI applications living up to expectations? Initial results from our ongoing survey covering the adoption and application of AI technology (based on initial responses from 105 participating organizations) provides some insight into this question.