VMware recently announced that it has signed a definitive agreement to acquire AirWatch, a leading provider of enterprise mobile management and security solutions. The acquisition is expected to provide customers with the most complete solution to manage users, devices, and applications across server, desktop, and mobile environments.
VMware obviously has had to expand its penetration beyond the server-centric virtualization market. So far, it has had mixed success with selling virtualization as a platform in the region, even though it has successfully entrenched itself as a leading hypervisor provider (unfortunately, VDI has proved a difficult sell for VMware in AP). In order to gain much deeper penetration and traction, VMware needed to add an end user computing offering to its portfolio. The pairing should result in:
On January 22, 2014, a new mobile security player was born. This is the date that VMware announced its intention to purchase the mobile device management (MDM) firm AirWatch. With a price tag of $1.5 billion, this acquisition confirms that the mobile security market is scorchingly hot. This news comes on the heels of the November acquisition of Fiberlink by IBM. I expect additional mobile security market consolidation to occur throughout the remainder of 2014. This acquisition is a shot across the bow of any other major vendor looking to play in the mobile security market. If you don't step up and spend now, you might just be left holding the bag.
Information workers in India are increasingly using their personal devices, applications, and web services to accomplish both personal and work-related activities. Results from Forrester’s Forrsights Workforce Employee Survey, Q4 2012 indicate that at least 85% of employees use phone/tablet applications and web-based services for both purposes which is putting corporate information security under serious threat.
My interactions with numerous infrastructure and operations (I&O) professionals from large enterprises in India over the past six months have revealed that there is a high degree of awareness of the need to develop a bring-your-own-technology (BYOT) policy. However, actual implementations aren’t yet common, as I&O professionals are unable to address management’s three key concerns. These are, in order of priority:
How can we ensure that information on employee-owned hardware and software is secure?
Big data gurus have said that data quality isn’t important for big data. Good enough is good enough. However, business stakeholders still complain about poor data quality. In fact, when Forrester surveyed customer intelligence professionals, the ability to integrate data and manage data quality are the top two factors holding customer intelligence back.
So, do big data gurus have it wrong? Sort of . . .
I had the chance to attend and present at a marketing event put on by MITX last week in Boston that focused on data science for marketing and customer experience. I recommend all data and big data professionals do this. Here is why. How marketers and agencies talk about big data and data science is different than how IT talks about it. This isn’t just a language barrier, it’s a philosophy barrier. Let’s look at this closer:
Data is totals. When IT talks about data, it’s talking of the physical elements stored in systems. When marketing talks about data, it’s referring to the totals and calculation outputs from analysis.
Quality is completeness. At the MITX event, Panera Bread was asked, how do they understand customers that pay cash? This lack of data didn’t hinder analysis. Panera looked at customers in their loyalty program and promotions that paid cash to make assumptions about this segment and their behavior. Analytics was the data quality tool that completed the customer picture.
Data rules are algorithms. When rules are applied to data, these are more aligned to segmentation and status that would be input into personalized customer interaction. Data rules are not about transformation to marketers.
It is easy to get caught up in the source and target paradigm when implementing master data management. The logical model looms large to identify where master data resides for linkage and makes the project -- well -- logical.
If this is the first step in your customer MDM endeavor and creating a master data definition based on identifying relevant data elements, STOP!
The first step is to articulate the story that customer MDM will support. This is the customer MDM blueprint.
For example, if the driving business strategy is to create a winning customer experience, customer MDM puts the customer definition at the center of what the customer experience looks like. The customer experience is the story. You need to understand and have data points for elements such as preferences, sentiment, lifestyle, and friends/relationships. These elements may be available within your CRM system, in social networks, with partners, and third-party data providers. The elements may be discrete or derived from analytics. If you only look for name, address, phone, and email, there is nothing about this definition that helps determine how you place that contact into context of engagement.
Ultimately, isn’t that what the business is asking for when they want the promised 360-degree view of the customer? Demands for complete, relevant, and timely are not grounded in the databases, data dictionaries, and integration/transformation processes of your warehouses and applications; they are grounded in the story.
So, don’t start with the data. Start with the story you want to tell.
Information workers in organizations across Asia Pacific (AP) are increasingly using personal mobile devices, applications, and public cloud services for work. Forrester defines this as the bring-your-own-technology (BYOT) trend. This behavior is more prevalent among employees above the director-level (C-level executives, presidents, and vice presidents) than those below that level (individual worker, contractor or consultant and manager/supervisor). Data from Forrester’s Forrsight Workforce survey, Q4 2012 corroborates this trend in AP.
We believe that the BYOT trend will strengthen over the next two years in AP, primarily fueled by employees below the director level. Increasing options, quality and affordability of devices, apps, and wireless connectivity, coverage, and capacity will contribute to this expansion. In order to secure corporate data, organizations will need to:
Develop Corporate Mobile Policies: Organizations must build cross-functional teams to plan their mobile strategies. This should include representatives from different LOBs like finance, HR, legal and sourcing. Moreover, the policy must clearly define guardrails to provide flexibility to employees but within boundaries and in compliance with local regulations.
Identify Technologies To Secure Corporate Data: 29% of business-decision makers in AP report that the rising expectations of younger workers require businesses to push enterprise IT to keep technology current. This is why it is critical to identify both back-end and front-end technologies and suppliers that can optimize mobile device and application management in a secure manner. Focus should be on networking layer security and mobile device management solutions.
There is a shift underway with master data management (MDM) that can't be ignored. It is no longer good enough to master domains in a silo and think of MDM as an integration tool. First-generation implementations have provided success to companies seeking to manage duplication, establishing a master definition, and consolidating data into a data warehouse. All good things. However, as organizations embrace federated environments and put big data architectures into wider use, these built-for-purpose MDM implementations are too narrowly focused and at times as rigid as the traditional data management platforms they support.
Yet, it doesn't have to be that way. By nature, MDM is meant to provide flexibility and elasticity to managing both single and multiple master domains. First, MDM has to be redefined from a data integration tool to a data modeling tool. Then, MDM is better aligned to business patterns and information needs, as it is designed by business context.
Enter The Golden Profile
When the business wants to put master data to use it is about how to have a view of a domain. The business doesn't think in terms of records, it thinks about using the data to improve customer relationships, grow the business, improve processes, or any host of other business tasks and objectives. A golden profile fits this need by providing the definition and framework that flexes to deliver master data based on context. It can do so because it is driven by data relationships.
Across Asia Pacific (AP), expanding mobility support for employees, customers, and/or business partners will be the top strategic telecom priority for enterprises in 2013, surpassing other telecom priorities like performing network management and consolidating operations equipment, rationalizing/consolidating telecom/communications service providers, and moving communications applications to the cloud.
While enterprises will invest in a range of mobility products and services, there are five key areas in particular which will attract the most investment in 2013. Vendors need to focus on the solutions and engagement models that meet customers’ needs in these five areas and target the industries and countries where the demand will be greatest:
Business consulting services. Specifically for defining a formal enterprise mobility and/or BYOD program strategy, including devices, applications, data access, and provisioning. Moreover, AP organizations will likely need help in drafting compliance and legal policies related to enterprise mobility.
Telecom expense management solutions. This is one of the most critical telecom requirements for AP CIOs in 2013. Across the region, 50% to 60% of organizations pay the entire cost of voice and data services for company-supported Android and iOS phones and tablets. For BlackBerry phones, this proportion is nearly 70%.
I recently had a client ask about MDM measurement for their customer master. In many cases, the discussions I have about measurement is how to show that MDM has "solved world hunger" for the organization. In fact, a lot of the research and content out there focused on just that. Great to create a business case for investment. Not so good in helping with the daily management of master data and data governance. This client question is more practical, touching upon:
what about the data do you measure?
how do you calculate?
how frequently do you report and show trends?
how do you link the calculation to something the business understands?
I just came back from a Product Information Management (PIM) event this week had had a lot of discussions about how to evaluate vendors and their solutions. I also get a lot of inquiries on vendor selection and while a lot of the questions center around the functionality itself, how to evaluate is also a key point of discussion. What peaked my interest on this subject is that IT and the Business have very different objectives in selecting a solution for MDM, PIM, and data quality. In fact, it can often get contentious when IT and the Business don't agree on the best solution.
General steps to purchase a solution seem pretty consistent: create a short list based on the Forrester Wave and research, conduct an RFI, narrow down to 2-3 vendors for an RFP, make a decision. But, the devil seems to be in the details.
Is a proof of concept required?
How do you make a decision when vendors solutions appear the same? Are they really the same?
How do you put pricing into context? Is lowest really better?
What is required to know before engaging with vendors to identify fit and differentiation?
When does meeting business objectives win out over fit in IT skills and platform consistency?