Mark Smith's Analyst Perspectives

I hope this title captures your attention; I’m trying to make a point about the chaos going on in managing and operating marketing. What marketing needs in 2016 is to manage and optimize its efforts in a more unified manner. This perspective kicks off a new series on the challenges for marketing to automate or execute tasks and manage toward maximum performance. We all know that the craft of marketing is in need of significant transformation, from the CMO throughout the entire marketing organization and all the way out to the experience of consumers and customers. But this may be a fanciful mission, as applications and technology does not really automate marketing let alone manage it. Most marketing automation products are specialized applications that are not used by marketing management, let alone front-line marketing managers; they are for specialized needs in demand generation or digital marketing that personalizes inbound and outbound interactions with contacts for the purpose of advancing dialogue and creating relationships. Marketing automation, like its cousin sales force automation, has been a placeholder category that describes only a narrow slice of marketing, and the term has been co-opted by the industry for its own purposes. Though some observers predict that CMOs will outspend CIOs and other leaders of the business in technology investments, I have debunked this ludicrous idea; even if it were true, that would not make marketing departments much more efficient in their management and operations. To counterbalance the silliness of the marketing automation dialogue, I plan to bring you a series on key areas for investment to start the conversation. Evaluating them should help Marketing demonstrate its commitment to promoting effectively its organization and its products and services. Here is an overview of the many issues in the landscape.

Topics: Big Data, Predictive Analytics, Social Media, Operational Performance Management (OPM), Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Location Intelligence, Operational Intelligence, Uncategorized, Business Performance Management (BPM), CMO, Customer Performance Management (CPM), Financial Performance Management (FPM), Information Applications (IA), Information Optimization, Sales Performance Management (SPM)

For several years I have been advocating that sales organizations adapt their processes and applications to optimize both sales performance and the customer experience. For details see my research agenda for last year. However, it appears that not many sales organizations have responded to this challenge; many can barely maintain their quarterly sales forecasts and monthly pipeline, track progress toward quotas and ensure that sales commissions are processed promptly and paid accurately. A great many are still using spreadsheets for these critical activities. Yet our benchmark research finds that more than half (61%) who use them for commissions said this makes the effort more difficult. Elsewhere, I have seen B2B sales organizations continue down the old path of annoying prospects with direct cold calling and email instead of nurturing real relationships. For B2C sales, the digital age of search engine optimization (SEO) and pay-per-click (PPC) has begun to haunt prospects by inserting ads in our personal social media channels. My research suggests that these practices are not due to bad intentions but to force of habit and lack of desire, time and resources to develop a modern strategy and plan. Most are just managing the basics of their sales processes and relying on sales force automation (SFA) systems, reporting and dashboards, which will only produce more of the same, less than optimal results.

Topics: Big Data, Predictive Analytics, Operational Performance Management (OPM), Business Analytics, Business Collaboration, Uncategorized, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Sales, SFA, SPM, Sales Performance Management, Sal

Businesses and their human resource organizations feel pressure to maximize the value of their human capital in today’s intensely competitive world. Many have made or considered investments in new applications that better exploit information to efficiently recruit, engage and retain the best talent. Advanced applications not only advance these processes but also help management assess the performance of the workforce and compensate individuals fairly so that they advance their careers and find the level of employee satisfaction in the organization. A year ago I outlined the priorities in human capital management (HCM). During the past year our research found a significant number of companies lacking a unified HCM strategy that includes processes and the applications to support it. As others advance, HR organizations that are not equipped with such skills, resources and tools risk falling behind in human capital management as it contributes to business success.

Topics: Big Data, Predictive Analytics, HCM, HR, HRMS, Workforce Management, Learning Mana, Human Capital, Business Analytics, Business Collaboration, Cloud Computing, Governance, Risk & Compliance (GRC), Uncategorized, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Management (IM)

Technology innovation is accelerating faster than companies can keep up with. Many feel pressure to adopt new strategies that technology makes possible and find the resources required for necessary investments. In 2015 our research and analysis revealed many organizations upgrading key business applications to operate in the cloud and some enabling access to information for employees through mobile devices. Despite these steps, we find significant levels of digital disruption impacting every line of business. In our series of research agendas for 2016 we outline the areas of technology that organizations need to understand if they hope to optimize their business processes and empower their employees to handle tasks and make decisions effectively. Every industry, line of business and IT department will need to be aware of how new technology can provide opportunities to get ahead of, or at least keep up with, their competitors and focus on achieving the most effective outcomes.

Topics: Big Data, Predictive Analytics, Social Media, Human Capital, Operational Performance Management (OPM), Analytics, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Governance, Risk & Compliance (GRC), Location Intelligence, Operational Intelligence, Uncategorized, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Applications (IA), Information Management (IM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM)

Data is an essential ingredient for every aspect of business, and those that use it well are likely to gain advantages over competitors that do not. Our benchmark research on information optimization reveals a variety of drivers for deploying information, most commonly analytics, information access, decision-making, process improvements and customer experience and satisfaction. To accomplish any of these purposes requires that data be prepared through a sequence of steps: accessing, searching, aggregating, enriching, transforming and cleaning data from different sources to cre­ate a single uniform data set. To prepare data properly, businesses need flex­ible tools that enable them to en­rich the context of data drawn from multiple sources, collaborate on its preparation to serve business needs and govern the process of preparation to ensure security and consistency. Users of these tools range from analysts to operations professionals in the lines of business.

Topics: Big Data, Predictive Analytics, Operational Performance Management (OPM), Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Data Preparation, Location Intelligence, Operational Intelligence, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Applications (IA), Information Management (IM), Information Optimization, IT Performance Management (ITPM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), Workforce Performance Management (WPM)

Big data has become a big deal as the technology industry has invested tens of billions of dollars to create the next generation of databases and data processing. After the accompanying flood of new categories and marketing terminology from vendors, most in the IT community are now beginning to understand the potential of big data. Ventana Research thoroughly covered the evolving state of the big data and information optimization sector in 2014 and will continue this research in 2015 and beyond. As it progresses the importance of making big data systems interoperate with existing enterprise and information architecture along with digital transformation strategiesbecomes critical. Done properly companies can take advantage of big data innovations to optimize their established business processes and execute new business strategies. But just deploying big data and applying analytics to understand it is just the beginning. Innovative organizations must go beyond the usual exploratory and root-cause analyses through applied analytic discovery and other techniques. This of course requires them to develop competencies in information management for big data.

Topics: Big Data, MapR, Predictive Analytics, SAP, Human Capital, Mulesoft, Operational Performance Management (OPM), Paxata, SnapLogic, Splunk, Business Analytics, Business Intelligence, Cloud Computing, Cloudera, Hortonworks, IBM, Informatica, Information Management, Operational Intelligence, Oracle, Business Performance Management (BPM), Customer Performance Management (CPM), Datawatch, Dell Boomi, Financial Performance Management (FPM), Information Management (IM), Information Optimization, Sales Performance Management (SPM), Savi, Sumo Logic, Supply Chain Performance Management (SCPM), Tamr, Trifacta, Strata+Hadoop

Many businesses are close to being overwhelmed by the unceasing growth of data they must process and analyze to find insights that can improve their operations and results. To manage this big data they find a rapidly expanding portfolio of technology products. A significant vendor in this market is SAS Institute. I recently attended the company’s annual analyst summit, Inside Intelligence 2014 (Twitter Hashtag #SASSB). SAS reported more than $3 billion in software revenue for 2013 and is known globally for its analytics software. Recently it has become a more significant presence in data management as well. SAS provides applications for various lines of business and industries in areas as diverse as fraud prevention, security, customer service and marketing. To accomplish this it applies analytics to what is now called big data, but the company has many decades of experience in dealing with large volumes of data. Recently SAS set a goal to be the vendor of choice for the analytic, data and visualization software needs for Hadoop. To achieve this aggressive goal the company will have to make significant further investments in not only its products but also marketing and sales. Our benchmark research on big data analytics shows that three out of four (76%) organizations view big data analytics as analyzing data from all sources, not just one, which sets the bar high for vendors seeking to win their business.

Topics: Big Data, Predictive Analytics, SAS, Event Stream, Operational Performance Management (OPM), Analytics, Business Analytics, Business Intelligence, CIO, Data Management, Information Management, Location Intelligence, Operational Intelligence, Business Performance Management (BPM), Customer Performance Management (CPM), Discovery, Information Applications (IA), Information Management (IM)

At this year’s annual SAP user conference, SAPPHIRE, the technology giant showed advances in its cloud and in-memory computing efforts. It has completed the migration of its conventional application suite and portfolio of tools to operate on SAP HANA, its in-memory computing platform, and made improvements in its cloud computing environment, SAP HANA Enterprise Cloud. The last time I analyzed SAP HANA was when it won our firm’s 2012 Overall IT Technology Innovation Award. Now HANA has been transitioned from just a database technology into a broad platform. SAP wisely consolidated its efforts previously known as SAP NetWeaver into SAP HANA. This resolves some confusion regarding HANA and NetWeaver in the cloud, which I assessed. The recently announced SAP HANA Platform now provides the enterprise class of HANA implementation in the cloud. It comes with a trial edition of the data and visual discovery technology now called SAP Lumira, whose price has been reduced to encourage adoption (and which I discuss more below). The use of in-memory databases for big data is accelerating: According to our technology innovation research, 22 percent of organizations are planning to use this technology over the next two years, and through 2015 it will have a higher growth rate than other approaches.

Topics: Big Data, Predictive Analytics, SAP, Social Media, Teradata, Mobile Technology, Operational Performance Management (OPM), Business Analytics, Business Collaboration, Business Intelligence, CIO, Cloud Computing, Governance, Risk & Compliance (GRC), HP, Business Performance Management (BPM), CFO, CMO, Customer Performance Management (CPM), Financial Performance Management (FPM), Information Applications (IA), Information Management (IM), SAP EPM, SAP HANA, SAP Lumira, SAPPHIRE, Supply Chain Performance Management (SCPM), Tagetik, Workforce Performance Management (WPM)

I recently attended the annual SAS analyst summit to hear the latest company, product and customer growth news from the multi-billion-dollar analytics software provider. This global giant continues to grow its business and solutions to help with fraud prevention, marketing and risk. It lets users apply its analytic and statistical technology in practical applications for business. SAS can meet midsized businesses’ demand with packaging and pricing to ensure it is not seen as only affordable to Global 2000 companies. SAS’ growth in analytics should be no surprise, as our research finds analytics to be the first-ranked priority among technologies for innovating business.

Topics: Big Data, Predictive Analytics, SAS, Fraud, GRC, Operational Performance Management (OPM), Analytics, Business Analytics, Business Intelligence, CIO, Cloud Computing, Data Integration, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Applications (IA), Information Management (IM), Risk, Sales Performance Management (SPM)

Managing the access, storage and use of data effectively can provide businesses a competitive advantage. Last year I outlined what the big deal is in big data, as the initial focus on the volume, velocity and variety of data – what my colleague Tony Cosentino calls the three V’s – is only one small piece of how organizations should evaluate this technology. The more balanced approach is to include what he calls the three W’s – the what, so what and now what, which shifts the focus to an outcome-based view that can handle the time–to-value urgency found in business. Big data analytics can help assess the volume of data, while the velocity of data that is potentially in-motion is best handled by what we call operational intelligence. Beyond these, techniques and technology such as predictive analytics and visual discovery facilitate extracting more value from big data. Along with a wide variety of data, these tools help organizations focus on optimizing information assets. We will soon conduct benchmark research into information optimization to determine how organizations are dealing with their information today and what steps they are taking to improve. In-memory computing will surely be one of those steps, as it can significantly improve the time-to-insight equation.

Topics: Big Data, Master Data Management, Predictive Analytics, MDM, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, CIO, Cloud Computing, Data Governance, Data Integration, Information Management, Location Intelligence, Operational Intelligence, Information Applications (IA), Information Management (IM), Product Information Management, Sales Performance Management (SPM), Workforce Performance Management (WPM)