The 4 Es of Social Media Strategy

Jill Dyché in her Information Management Blog "The 4 Es of Social Media Strategy" contests that companies

are pretty vague about the drivers for the new "Social Media"initiative.

Apart from the usual platitudes of “getting closer to employees, partners, and customers via lower-cost channels” it turns out very few business leaders can answer my question about the desired outcome of social media analytics.
In our experience, there needs to be at least one prevalent driver for social media.

She calls these the “4 Es of Social Media Strategy.”

A 4 Step Approach for Selecting the Right BI solution

Boris Evelson  in his Information Management Blog - Forrester Muse, titled "Use a Four-Step Approach to Select the Right BI Services Provider" contests that the fast-paced business environment often introduces new requirements, enhancements and updates before you're even done with your first Business Intelligence implementation. 

Therefore, we typically recommend doing sufficient due diligence upfront when selecting a BI services provider — as you may be stuck with them for a long time.

We recommend the following key steps in your selection process:

Social Business Intelligence: The Pipeline Dream

James Kobielus in his Information Management Blog "Social Business Intelligence: The Knowledge Management Connection" contests that Business intelligence (BI) has always had a “pipeline” orientation- known as “simplex” information transfer; in other words, a primary focus on the one-way flow of data, information and insights from “sources” (e.g., your customer relationship management systems, enterprise data warehouses, and subject-area data marts) to “consumers” (e.g., you).

However, many real-world intelligence flows are full-duplex, many-to-many, and person-to-person in orientation. This fundamental truth will continue to drive the spread of “social” architectures in core BI and advanced analytics...

Analytics in Retail

Mark A. Smith in his  Information Management Blog titled "Analytics in Retail: An Operational and Financial Mandate"contests that for

every role in a retail organization, marketing, selling and serving customers are critical  for converting shoppers to profitable customers. functions.  As volumes and sources of data continue to expand, the retail industry is going through a transformation in using all forms of data to advance its efforts. And Analytics in Retail, can help determine the best actions to optimize future efforts in the most cost-effective manner.

Why Consumer Goods Companies Need Analytics to Compete?

Mark A. Smith in his Information Management Blog titled "Consumer Goods Companies Need Analytics to Compete" contests that given the cutthroat competitive landscape among consumer goods manufacturers, from food and beverage to electronics and automotives, capturing the minds and wallet share of customers, by reaching out to them with the right product and right price is no easy task.

Optimizing business efforts from manufacturing to product and throughout the supply chain to customers requires a comprehensive set of tasks that cannot be done without insights on what has happened in the past and where current activities are going. Those event-driven and demand-driven insights can come through analytics that assess the small but important details of pricing, trade promotions and processes in the supply chain to keep retailers satisfied with inventory levels.

How Analytics can Help the Hospitality Industry

Mark A. Smith in his Information Management Blog titled "Analytics Help Hospitality Industry Thrive" contests that nowadays consumers of hospitality and entertainment, from hotels and travel to events, theme parks and cruises, are very demanding.

Faced with intense price pressures and the influence of consumers on others through social media, the hospitality industry struggles to adjust to shifting demand fast enough to optimize operations to reach the desired financial outcomes.
The best way to understand, demand and tailor services to it is to use analytics to understand the voice of the consumer.
The goal is to provide high-quality service at prices that deliver optimal margins for the organization, but it's a combination not easy to balance.

Marketing Analytics Measures Effectiveness of Investments for Market and Business Objectives

Mark A. Smith in his Information Management Blog titled "Marketing Analytics Measures Effectiveness of Investments for Market and Business Objectives" that the ability of marketing to measure its contributions to specific objectives is rather limited. The recent economic environment has placed extreme pressure on marketers to evaluate the performance of investments in a range of brand, category and demand-generation processes to ensure that marketing budgets are spent wisely.

New approaches and tools can simplify marketing processes, both internal and external, to deliver results on those objectives in timely fashion. To measure the value of marketing investments, a range of analytics are available that help produce metrics to manage and optimize its processes and track progress to objectives.
To really understand their existing investments and processes, marketing organizations should not just measure them in hindsight but also project future results using predictive analytics and planning; for example, the likelihood that customers will respond positively to an offer that will improve the company’s brand ranking or category market share.

Analytics on Analytics: Is Decision Management, the Last Frontier in BI?

 

Boris Evelson in his Information Management Blog / Forrester Muse titled "Decision Management, Possibly the Last Frontier in BI" leans on an excellent article on the subject by Tom Davenport and reports on Forrester Research and the trend for 'Thinking Ahead" companies  to venture into combining reporting and analytics with decision management along the following lines:

• Automated (machine) vs. non automated (human) decisions, and

• Decisions that involve structured (rules and workflows) and unstructured (collaboration) processes.

Unfortunately, current best practices and technologies to address these four distinct, but closely related requirements, come from different vendors, technologies and experts.

Results of The Forrester Wave: Open Source Business Intelligence, Q3 2010

Boris Evelson  in his Information Management Blog / Forrester Muse titled "Results of The Forrester Wave: Open Source Business Intelligence, Q3 2010" contests that BI  continues to be one of the top priorities on everyone's mind. 

The main reason?
Enterprises that do not squeeze the last ounce of information out of their data stores and applications, and do not focus on getting strategic, tactical, and operational insight into their customers, products, and operations, risk falling behind competition.

Another finding relates to the fact that developers increasingly use open source to run key parts of their IT infrastructure.
Over the past few years, we've seen that developers adopt open source products tactically without the explicit approval of their managers. And management has grown increasingly comfortable with it. In fact, throughout 2009, most client inquiries Forrester received regarding open source were focused on how to move from tactical adoption to strategic exploitation.

Yet, when you put the 2 and 2 together (OSS and BI), you mostly get a mixed market, where one unfortunately has to compare apples to oranges.
Why?
Before plunging into a tool evaluation and selection process, ask yourself the following questions, and make sure you are doing a like-to-like comparison:

Six Steps to Governing Analytics

This approach deals directly with behavioral change and the actions to help ensure that value is being achieved

Information Management Magazine, July/Aug 2010

Greg Todd

Predictive analytics takes the information made available through descriptive analytics (historical facing) and combines it with more sophisticated statistical modeling, forecasting and optimization techniques to derive insights which help to anticipate the impact on business outcomes. Where are organizations when it comes to leveraging predictive analysis? Research shows that while some organizations may analyze data to predict what might happen in the future in terms of competitor activities, market trends, product/service development, risk management, financial/economic trends and skill requirements, many organizations are still using predictive analytics only to a minor extent, if at all.It's clear that companies need to move from descriptive analytics (the "what") to predictive analytics (the "now what?"), from "what happened?" to "what's the best that can happen?"
During previous economic downturns, companies that thrived used data-derived insights made by informed decision-makers to produce lasting competitive advantage...

3 Ways Real-Time Information is Changing Decision-Making

August 26, 2010 | 11AM ET REGISTER TODAY! In a recent survey by Vanson Bourne, 94% of respondents say  that responding to information immediately is critical to their business,  yet only 8% currently report information in real time.  Many are unable to filter through the enormous deluge of information  coming at them from every angle.  With the speed of business constantly accelerating,  a company’s ability to respond to information quickly,  defines their competitive advantage.  Trouble is most IT systems and architectures  were not built to handle real-time situational awareness  and in-the-moment reaction.  Operational decisions can no longer be made exclusively  with dated information. This webinar will discuss 3 ways that real-time information  and business events affect your decision-making process.  Through real-time visibility and immediate sense and respond,  you get the right information at the right time.  The result is decision management that is “in the moment”  and operational responsiveness that meets the speed of your business.