Cisco will be featured in two Big Idea sessions at this year’s NRF conference starting tomorrow, and I’m happy to introduce guest blogger Lisa Fretwell, who will be leading one of these two seminars. Lisa is the Managing Director of Retail at Cisco Consulting Services, specializing in the Internet of Everything and analytics, and how these new capabilities can transform and differentiate retail and consumer product businesses:
In today’s digital era, stores are clearly challenged in terms of sales and profitable growth. Every retailer is faced with needing to change and innovate their store to deliver results.
Overall, the majority of stores across all categories are demonstrating flat or declining like for like, exacerbated by price deflation. Cisco’s recently concluded annual survey on shopper behavior of 10,000 shoppers highlights the ongoing shift away from the store to online. Twenty percent of consumers now make more than 50% of their purchases online, and this number is expected to continue to grow.
However, when you dig down into the data, you may be surprised by some of the changes. As just one example, we asked shoppers which categories they had significantly moved from store to online. We learned that 41% of the consumers surveyed have somewhat or significantly increased their online purchases of apparel in the last two years – clothing, shoes, and accessories. Traditionally, these products are the life blood of why shoppers go to a store – to touch, feel, try on.
So is it all doom and gloom for shops? No, not if you’re up for innovation and change. There are still significant reasons for shoppers to visit stores. Our research highlights some key insights that retailers must leverage to drive healthy results and make the store experience hyper-relevant.
Our experience from retail engagements suggests the answer lies in two areas: being able to deliver dynamic experiences, and to improve ways of working. From instant response to customer needs to improved process digitization, we are seeing that retailers are increasingly relying on a combination of sensors, analytics, automation, cloud, and edge computing.
If we apply this model to a $20 billion turnover retailer with 900 stores, Cisco estimates that there is $312 million of incremental benefit to be had: $170 million from digitizing ways of working: staffing optimization, store routine digitization, and colleague collaboration; plus $142 million from improved customer conversion through insight, digital offers and loyalty, service, and cross-channel selling. We believe this approach offers the next much-needed step change in store economics.
In Part 1 of this blog series, I talked about how data integration provides a critical foundation for capturing actionable insights that generate improved outcomes. Now, in Part 2, I’ll focus on the two other challenges that must be met to extract value from data: 1) automating the collection of data, and 2) analyzing the data to effectively identify business-relevant, actionable insights. This is where things, data, processes, and people come together.
Let’s start with automation.
After IoT data is captured and integrated, organizations must get the data to the right place at the right time (and to the right people) so it can be analyzed. This includes automatically assessing the data to determine whether it needs to be moved to the “center” (a data center or the cloud) or analyzed where it is, at the “edge” of the network (“moving the analytics to the data”).
The edge of the network is essentially the place where data is captured. On the other hand, the “center” of the network refers to offsite locations such as the cloud and remote data centers — places where data is transmitted for offsite storage and processing, usually for traditional reporting purposes. The edge effectively could be anywhere, such as on a manufacturing plant floor, in a retail store, or on a moving vehicle.
In “edge computing,” therefore, applications, data, and services are pushed to the logical extremes of a network — away from the center — to enable analytics knowledge generation and immediate decision-making at the source of the data.
On January 13th, 2015, Cisco will celebrate the 1-year anniversary of its launch of Application Centric Infrastructure (ACI), a ground breaking SDN architecture. It will include a public webcast with the participation of early ACI adopters and our ecosystems partners. One of these inaugural partners was Splunk, the Operational Intelligence company for all types of IT organizations. At the webcast, Splunk and other partners will describe a range of new solutions with ACI, that dramatically simplify Data Center operations. Here is a preview of Splunk’s solution.
A large portion of the data center operational effort is consumed in managing application health. This includes:
Ensuring the end-user experience for distributed users with different types of performance needs
Discovering the physical and virtual resources associated with applications and the user experience
Detailed monitoring of resources and events in the infrastructure that affect application performance
These activities have become more complex as applications have become distributed, interconnected or cloud based because they cause applications to move, scale and evolve rapidly.
Splunk Enterprise can monitor and analyze millions of infrastructure events through logs and agents, in real-time. This can provide rapid visibility and isolation of infrastructure that affect application performance. Cisco has been collaborating with Splunk to combine the application visibility of Cisco Application Centric Infrastructure with operational analytics of Splunk Enterprise. The result is “Cisco ACI for Splunk Enterprise” a highly scalable application that is orderable immediately at Splunk.com.
ACI and Splunk have enabled a comprehensive view of application health with the ability to monitor the entire end-to-end environment in real time and proactively prevent issues from impacting end users.
ACI provides visibility to application health from the network perspective by tracking all network dependencies and events that impact application performance and security. Splunk complements Cisco ACI by bringing actionable intelligence across the entire data center infrastructure including storage, compute, virtualization endpoints, as well as application tiers and components provided by ACI. Splunk’s analytical and visualization tools provide real-time insights to data center teams to optimize performance and ensure security policies in a highly dynamic environment.
How does it work
Cisco ACI exposes a wealth of networking data previously inaccessible to Splunk. The Cisco ACI app for Splunk Enterprise gathers data from APIC (Application Policy Infrastructure Controller) including APIC network events, health scores and inventory of logical constructs (e.g. tenants, application profiles, end point groups) and physical constructs ( e.g spines, leafs, VMs).
This data is used to:
Reduce resolution time with accelerated root-cause analysis
Splunk enables users to reduce the mean time to investigate/resolve problems up to 70%
Centralized management of operational health of ACI environment & underlying entities in real-time
Detect issues or anomalies in performance or response times and proactively resolve
For multiple tenants, quickly navigate to the source of problems using flexible per-role views, including 1) Help Desk view, 2) Tenant View and 3) Fabric view
Provide Central Proactive Monitoring of Cisco ACI
Get real-time proactive notification of network traffic and device faults with location, affected objects.
Track trends and anticipate application impact
Operational Analytics across the entire virtual and physical infrastructure
Optimize network capacity and prevent service deterioration with detailed visibility into fabric path degradation.
Meet compliance/security with user analytics, including authentication tracking reports.
Correlate data from Cisco ACI with data from storage resources, operating systems, applications, security devices, endpoint and more for enterprise-wide visibility.
Trace and monitor transactions through all tiers of a distributed application architecture
Gives application managers a perspective on the underlying Cisco ACI infrastructure’s effect on applications without being directly involved in ACI Ops.
Monitor key operational metrics such as end-to-end response times to ensure SLAs met.
As an example, a Fortune 100 company is using Splunk with ACI:
for operational visibility for their ACI cluster with ability to quickly identify faults and troublesome tenants and determine corrective action.
to provide centralized visibility as ACI expands across multiple data centers and for proactive monitoring to establish baselines and triggered alerts when key thresholds exceeded.
This approach to Application Health is part of the broader discipline of Application Performance Management (APM). According to Gartner, “By 2018, 60% of APM deployments will use and integrate data extracted directly from log files alongside wire data and agent-derived data as a foundation for reporting, prediction, and analysis, up from less than 5% today.” With our collaboration, ACI for Splunk Enterprise provides important new capabilities for Application Performance Management.
Billions of devices are changing how organizations compete and disrupting traditional data management and analytics.
This Internet of Everything world presents an exciting new opportunity to discover and take advantage of market, customer, and operational insights. And by making sense of captured data quickly, organizations can take action at that point, in that moment, in ways that differentiate versus competitors and drive significant new business value. TimeWarnerCable’s intelligent home initiative is one example.
But all this data is massive, messy, and everywhere, spanning many sources – cloud, data warehouses, devices – and formats – video, voice, text, and images. To address this challenge, new solutions beyond traditional data warehousing and even big data are required.
Cisco Enters the Data and Analytics Market
When Cisco acquired data virtualization market leader Composite Software in mid 2013, Cisco signaled a clear intent to begin connecting this data via intelligent networking the same way it connected LANs; the Internet; voice and video over IP; and more in it’s 30 year history.
And with our December 11, 2014, Connected Analytics Portfolio announcement, Cisco adds a rich suite of analytics solutions that help organizations capture insights that create new opportunities, simplify business operations, enhance the customer experience, and resolve potential threats.
New Methods for the New Challenges
Today’s analytic solutions need to advance beyond traditional methods that move data to a warehouse or data lake before commencing analysis. Cisco’s Connected Analytics Portfolio provides analytics with immediate access to data, as well as brings analytics to the data – no matter where the data resides on the network.
Further, Cisco is uniquely qualified to implement analytics at the point of data, because so much of the data worldwide resides on our networks, providing the ideal platform for embedded analytics. Along with 30 years of networking experience, Cisco now has the data and analytics tools, software, and services to help our customers instantly capture, analyze, and interpret critical data out to the network edge.
Wealth Management firms are spending billions on IT to differentiate in the market place. Yet the question remains, can “Big Data” have a material impact on the business? Can it deliver business outcomes by reducing risk, increasing assets under management, driving profitability, client satisfaction, products per client, client and financial advisor retention, all while improving the cost/income ratio and return on equity?
These are questions that are being discussed in board rooms across the financial industry and topics that I will cover in this blog series.
In order to answer these questions we need to put the wealth client at the center and understand changing client needs and expectations around how the client wants to be served by the firm. We need to examine external factors such as the impact of game changing consumer technology and unprecedented client access to information, as well as understand how new market entrants are challenging the traditional financial advisor value proposition and business model as a new round of Robo-Advisors hit the market.
Up until recent years, banks enjoyed an account centric transactional business model. What is changing is the onset of unstructured social interaction data as smart mobile devices and mobile broadband Internet usage reach high penetration levels. Device proliferation is leading to the availability of “data exhaust” from mobile phones, tablets, automobiles, video cameras, and from sensors in buildings, streets, consumer wearables and footfall traffic counters. Correlation of such data to better attract, retain, and serve clients can create market advantage.
The “Big” in Big Data comes from the fact that worldwide data volume is doubling every two years with unprecedented volume, variety, and velocity. Ninety percent of the all data in the history of the world was created in the last two years (SINTEF)! The concept of Big Data is about the correlation and analysis of transaction data, social interaction data, and machine/sensor data in a way that can turn data into knowledge, knowledge into insights, and insights into actions in real-time.
So what does this all mean for wealth managers?
As a wealth manager, what impact would it have on your business if you were able to increase the understanding of your client exponentially? Actions derived from data are informed by highly personalized needs predictions that can arm wealth managers with deep insights about their clients, increase their relevance in every interaction, and directly contribute to business outcomes. Big Data can help wealth managers transform the client value proposition and re-imagine the client experience.
The new vision for financial services is that a firm must be present in the financial lives of its clients, any time, any place, on any device, and across any channel.
The firm can no longer wait for the client to come to it. It must be proactive in delivering highly relevant value-added services in real-time and anticipate client needs. The firm needs to aspire to creating a “market of one” experience for each wealth client, understand the needs of and the hierarchy within the household, and move to a client centric versus account centric go-to-market approach.
When it comes to Big Data in Wealth Management start with the foundation, put the client at the center, and define business outcomes. Focus on building capabilities around what is possible while re-imagining the client experience.
Wealth management firms can take concrete steps in the form of measurable business outcome based projects to significantly enhance the client experience. These include:
Define a roadmap for wealth client data analytics maturity. This will identify gaps that can be addressed resulting in more relevant advisor-client interactions.
Establish a wealth client listening system across all channels. Early detection of client behaviors can lead to the identification of issues and sales opportunities.
Create a real-time single view of wealth client data with data virtualization. Substantial savings can be had by leaving disparate data in place while providing managers with a single view.
Establish an analytics driven financial advisor collaboration platform. This helps create market differentiation by maximizing advisor productivity, sharing best practices daily.
Deploy mobile virtual advisor video capability and establish branch analytics. This improves client experience and gives advisors more minutes per day with clients increasing cross-selling opportunities.
Empower advisors with real-time client insights to drive business outcomes. This helps the advisor manage to client life events with much greater granularity and speed.
The choices that wealth management firms make around data analytics in the next two years will determine their position in the marketplace. Can Big Data help wealth managers? With a client centric and business outcomes solutions approach, the answer is an astounding YES!
I will discuss each of the above steps in more detail in my next blog. As always I welcome your suggestions, stories, and feedback!