Business Intelligence

From Our Friends at Deloitte – the Planning Analytics Talent Shortage Is a Big Deal.

October 25, 2016 by MIAWebAdmin

A Deepening Shortage

By now it’s obvious that universities and colleges can’t crank out data scientists fast enough to keep up with business demands, and they certainly can’t produce experienced analysts from a two- or four-year program. In a 2015 MIT Sloan Management Review survey, 40 percent of respondents say they have difficulty hiring analytical talent. Only 17 percent of “analytically challenged” firms say they have the talent they need. Among companies reported to be “analytics innovators,” 74 percent said they had the analytics talent needed.

Getting Creative

International Data Corporation (IDC) predicts a need for 181,000 people with deep planning and analytical skills in the US by 2018 and a requirement for five times that number of positions with data management and interpretation capabilities. To complicate matters, there is no clear set of capabilities that define a “data scientist” because different problems require different skillsets.

Some organizations are taking a multipronged approach by supplementing campus recruiting with alternatives, such as turning to managed analytics, cultivating in-house talent, or outsourcing. With a rising number of analytics and data-science programs at universities—more than 100 in the US alone—recruitment efforts in analytics are red hot today.

Organizations recruiting at these campuses will likely find more success if they work closely with the programs on internships and student projects. Once recruited, these graduates are more likely to stay and do productive work if they have meaningful career paths and the opportunity to work with others with similar skills and backgrounds.

Tapping the Talent Ecosystem

Of course, analytics talent doesn’t have to be directly employed by the organization. Some companies are consciously developing ecosystems of external providers. One, for example, has selected multiple service partners in the areas of business intelligence, predictive analytics, data

science, and cognitive technology. The company continually monitors the efforts of these partners to recruit and develop qualified people and to keep up with new technologies and methods.

These are by no means extreme steps. Smart companies are realizing that analytical talent is critical to their success and in short supply. They know they must get serious about preparing or partnering with this strategic workforce if they hope to successfully execute their strategies.

Our take is clearly along the path of the wise and best use of assets, both human and financial.

That’s where and how you will see not only a greater adoption of planning analytics, but far greater measurable and sustainable results. Do your research. Ask a lot of questions. Engage a successful, seasoned team of data integration and planning analysts. We cost less and deliver more. A quick look at a couple of our success stories that will confirm that we deliver.

Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven corporate and healthcare innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

Up Your Game and Get Measurable Results with Planning Analytics.

September 20, 2016 by MIAWebAdmin

Even under the most supportive circumstances, the application of analytics can feel like a long journey. It can take years to gather data, put the appropriate technologies in place, build the necessary skills, and embed analytical decision-making into key organizational processes.

And once this is all done, many wonder whether they have really uncovered all the value their data has to offer.

In many cases, the circumstances are less than supportive. Senior managers may not be enthusiastic about having their intuition replaced—or at least augmented—with analytics. They may simply not understand the value of an analytics initiative. There may be competing priorities for investment dollars. As with any other change program, managers and organizations can resist analytics programs or may not fully endorse their adoption.

Many companies are focusing more on big data and analytics because they are seeing positive results from trial projects as well as anecdotal evidence from industry colleagues or competitors.

Perhaps most importantly, senior executives are realizing that good data can yield good decisions if it is captured, analyzed, communicated, and acted upon in an agile and efficient fashion. And that realization is at the heart of the analytics dilemma, as one or more of those criteria is often missing from an organization’s analytical capabilities. But those who have cracked the analytics code are reaping its rewards.

Of course, most companies implementing analytics to boost or optimize their marketing and sales performance are applying the analytics capabilities to numerous customer-centric projects and processes. In some instances, this includes aggregating and dissecting huge amounts of unstructured data generated through websites, call centers, social media, and other consumer-facing resources.

The director of commercial analytics for a global health care company recently interviewed by Deloitte stated, “We’re starting to do a better job of identifying who’s doing what and sharing best practices. That’s been a significant step toward a more vertical integration of our data analytics function.”

You can get your organization healthier, more profitable and more confident with a process for improvements based upon the data analytics processes that support savvy, cost-effective decisions.

That’s where and how you will see not only a greater adoption of planning analytics, but far greater results.

Do your research. Ask a lot of questions. Engage a successful, seasoned team of data integration and planning analysts. We cost less and deliver more.

Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven healthcare innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

Powering Planning Analytics.

September 13, 2016 by MIAWebAdmin

A Google search for “big data analytics” yields a long list of resources. And many of these sources provide big data platforms and tools that support the analytics process, such as data integration, data preparation, and other types of data management software. Let’s focus for a minute on tools that meet the following criteria:

They provide the analyst with advanced analytics algorithms and models.
They’re engineered to run on big data platforms such as Hadoop or specialty high-performance analytics systems.
They’re easily adaptable to use structured and unstructured data from multiple sources.
Their performance is capable of scaling as more data is incorporated into analytical models.
Their analytical models can be or already are integrated with data visualization and presentation tools.
They can be easily integrated with other technologies.

Who uses advanced analytics?

While some individuals in the organization are looking to explore and devise new predictive models, others look to embed these models within their business processes, and still others want to understand the overall impact that these tools will have on the business. In other words, organizations that continue to evolve and deploy big data analytics need to accommodate a variety of users, such as the ones below:

The data scientist, who likely performs analyses involving complex data types and is familiar with how underlying models are designed and implemented to assess inherent dependencies or biases.
The business analyst, who is likely a more casual user looking to use the tools for proactive data discovery or visualization of existing information, as well as some predictive analytics.
The business manager, who is looking to understand the models and conclusions.
IT developers, who support all the prior categories of users.

All of these roles typically work together in the model development lifecycle. The data scientist subjects a swath of big data sets to the undirected analyses provided, and looks for any patterns that would be of business interest.

After engaging the business analyst to review how the models work and evaluate how each of those discovered models or patterns could potentially positively affect the business, the business manager and IT teams are brought in to embed or integrate the models into business processes or devise new processes around the models.

As appetites for data expand among companies across an array of industries, big data analytics has found a place in a wider corporate population, including healthcare organizations. In the past, the cost factors for a large-scale analytics platform would have limited the adoption to only the very largest businesses.

However, the availability of utility-style hosted big data platforms (such as those available via Amazon Web Services) and the ability to instantiate big data platforms such as Hadoop on-premises without a large investment have reduced the barrier to entry. In addition, open data sets and accessibility to fire hose data feeds from social media channels provide the raw material for larger-scale data analyses when blended with internal data sets.

Larger businesses may still opt for high-end big data analytics tools, but lower-cost alternatives deployed on cost-effective platforms enable small and medium-size businesses to evaluate and launch big data analytics programs and achieve the desired business improvement results.

You can get your organization healthier with a process for improvements based upon a lean delivery system and the data analytics that support savvy, cost-effective decisions.

That’s where and how you will see not only a greater adoption of predictive analytics, but far greater results.

Do your research. Ask a lot of questions. Engage a successful, seasoned team of data integration and planning analysts. We cost less and deliver more. Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven healthcare innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

Healthcare Financial Viability and Planning Analytics.

August 31, 2016 by MIAWebAdmin

A main concern for hospital CEOs continues to revolve around the financial position of their organizations. Other concerns include evolving CMS mandates and rulings, patient satisfaction and quality scores, population health management, and personnel shortages—all of which end up impacting the bottom line if health systems can’t overcome these and related challenges.

Because of the significant trials the industry as a whole is facing, three major credit rating agencies (Standard & Poor’s Financial Services, Fitch Ratings, and Moody’s Investors Service) have all given the healthcare and hospital sectors negative outlooks for past calendar years.

But that can change for the better. It’s a process. And it’s vital to delivering improved care systematically at lower costs.

Performance improvement requires an analytics system that integrates the organization’s data sources (clinical, claims, financial, operational, etc.), and that facilitates quick and easy data sharing. Only with appropriate analytics can an organization identify specific areas of opportunity among strategic areas of focus.

Healthcare data analytics is required for any sustainable performance improvement initiative. It forms the foundation of discussion and informs decisions. Yet while healthcare organizations have mountains of clinical, claims, financial, operational, patient experience, and other data, most of it is locked away in point solutions built for a specific purpose.

Performance improvement requires an analytic system that integrates the organization’s data sources, quickly and easily unlocks data, and enables effective sharing of data and the addition of new data sources. Doing so allows interdisciplinary teams to analyze the data and discover patterns that lead to insights.

Take a look at our hospital success story. This case study might qualify for Super Hero status. The client brought us multiple systems with 17 different lists of physicians, including different identifiers, specialties, practice types, status, and clinic locations. Many of the lists did not agree, so we made the disconnected process both connected and valuable.

Organizations that effectively use data as part of their decision-making process gain a competitive edge in their respective markets. At Management Information Analysis, we provide solutions that allow organizations in various industries make better use of existing data sets and incorporate all relevant information into their strategic planning.

Most quantitative forms of healthcare strategic planning are population-based, in which the demand for services is driven by population growth and changing demographics. Additionally, it is important to understand historical and current trends and to be able to anticipate future changes.

Healthcare organizations routinely pursue performance improvement initiatives to improve clinical outcomes and patient experiences and reduce organizational costs. If these efforts are not well executed, however, they can become black holes that suck up time, money, and resources while yielding few real, sustainable improvements.

You can get your organization healthier with a process for improvements based upon a lean delivery system and the data analytics that support savvy, cost-effective decisions. That’s where and how you will see not only a greater adoption of predictive analytics, but far greater results.

Do your research. Ask a lot of questions. Engage a successful, seasoned team of data integration analysts. We cost less and deliver more. Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven healthcare innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

Tipping Point: from Planning to Predictive Analytics

August 16, 2016 by MIAWebAdmin

Predictive analytics has become an increasingly hot topic in analytics circles as analysts discuss how we effectively model and use big data, and more people realize that predictive modeling of customer behavior and business scenarios is “the big way to get big value out of data.”

But we’re not anywhere near broad implementation for understandable reasons: time and money top the list, along with a scarcity of talent to transform and match data with priority decisions. But let’s motor on for a couple of minutes. It will be worth it.

There are much bigger potential business benefits for organizations that have invested in predictive analytics software. If a company’s competitors aren’t doing predictive analytics, it has “a great opportunity to get ahead,” Mike Gualtieri of Forrester Research recently reported in a discussion with an online blog. The benefits of predictive analytics are immense and span across various industries.

Virtually all of us are overwhelmed with data and starving for information, but that doesn’t mean it’s just a matter of rolling out the technology and letting analytics teams play around with data. When predictive analytics is done well, the business benefits can be substantial. However, there are some mainly strategic pitfalls. Many companies perform analytics purely for the sake of “doing” analytics, and they aren’t pursuing analytics that are measurable, purposeful, accountable, and understandable by leadership.

Data scientists don’t know it all!

With that in mind, data scientists end up looking for experienced data analysts who have all the required technical skills and also understand their business practices—a combination that can be nearly impossible to find. Difficult, yes. Impossible, not really. An array of other people, from within the business leadership pool and IT, should also play roles in predictive analytics initiatives. When you have the right balance with your team, you’ll end up with a purposeful and thriving analytics process that will produce results.

Companies looking to take advantage of predictive analytics tools also shouldn’t just jump into projects without a plan. You can’t approach predictive analytics the way you do with many other IT projects, so it’s important to think strategically about an implementation upfront and to plot out a formal process that starts with a comprehensive assessment of analytics needs and internal resources and skills. That’s where and how you will see not only a greater adoption of predictive analytics, but far greater results.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

Curation . . . Just So You Get a Sense of Where Big Data Is and Where It’s Going

July 28, 2016 by MIAWebAdmin

Over the 2014-2019 planning period, annual spending will likely reach 48.6 billion dollars in 2019. A new IDC Special Study examines spending on big data solutions in greater detail across 19 vertical industries and eight big data technologies.

The ever-increasing appetite of businesses to embrace emerging big data-related software and infrastructure technologies while keeping the implementation costs low has led to the creation of a rich ecosystem of new and incumbent suppliers. At the same time, the market opportunity is spurring new investments and M&A activity as incumbent suppliers seek to maintain their relevance by developing comprehensive solutions and new go-to-market paths.

All three major big data submarkets (infrastructure, software, and services) are expected to grow over the next five years. Infrastructure, which consists of computing, networking, storage infrastructure, and other datacenter infrastructure, like security, will grow at a 21.7 percent CAGR; software, which consists of information management, discovery and analytics, and applications software, will grow at a CAGR of 26.2 percent; and services, which includes professional and support services for infrastructure and software, will grow at a CAGR of 22.7 percent. Infrastructure spending will account for roughly one half of all spending throughout the forecast period.

As big data matures, IDC expects its share of the larger Business Analytics market to increase; however, year-over-year growth within the big data market is forecasted to gradually slow. The reduction in overall growth will be largely caused by increased price pressures for infrastructure and higher rates of commercialization of open source software.

The availability and skill level of big data IT and analytics talent will also have a direct impact on the market.

While the business drivers, barriers, and potential benefits from deploying big data initiatives vary from industry to industry, these efforts are primarily focused on delivering a better customer experience, supporting product and service innovation, and optimizing business processes. Common barriers to adoption include security and privacy concerns, as well as the related challenges of collecting, using, and managing customers’ data. A shifting regulatory environment is another area of concern across certain industries.

Get help when and how you need it.

You DO NOT have to bet the farm and the horses to get where you want to go with your data and analytics assets.

Engage a successful, seasoned thought partner to get a value-laden perspective. Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

3 Things that Enhance Your Success from Planning Analytics in Your Hands

July 12, 2016 by MIAWebAdmin

When it comes to cloud planning and analytics, don’t compromise. Planning analytics goes beyond simply automating your planning, budgeting, and forecasting processes. The process provides self-service and self-paced analytics to all of your business users through an innovative planning workspace that empowers business users to seek better business results. It delivers insights automatically from your data and helps you pull ahead of competitors and stay agile for the changes ahead.

Here are some essentials to get you into a position to gain and grow with planning analytics that work.

Well-structured and funded planning analytics provides the following:

Flexible and Scalable: Planning analytics can be leveraged by an individual, team, department, or across the enterprise. Size or budget shouldn’t force you to settle for anything less.
The Cloud Advantage: Using a cloud-based, self-serve software, you get a complete cloud solution with a streamlined and integrated user experience. It provides the entire solution experience for you.
Security: Because you’re smart, your planning analytics solution follows the most demanding security protocols and standards in the industry to protect your data: it’s integrated, streamlined, and secure. Make sure your users respect your data.

We have said this before but it bears repeating for one compelling reason: creating and deploying data analytics is a process, not a destination. And that will continue as we get smarter about our owned data usage and applying big data to make better strategic and tactical decisions.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

From Foggy Bottom to Deloitte to Us and You – Cybersecurity and Analytics Together!

June 24, 2016 by MIAWebAdmin

With faster access to their data, organizations can follow a data-driven approach to bring in business data and statistical rigor to identify the cause-and-effect relationship between the specific behaviors, competencies, skills and knowledge, and critical business outcomes (e.g. sales, profits, productivity, etc.). But be careful. Be very, very careful not to leave the data door open.

Last year’s super trend—still front and center—continues to grow in importance as more and more organizations experience the losses in value and reputation that can result from a security breach. And we’re not just talking about protecting data. Product design and other IP are also vulnerable to theft and sabotage.

The problem is likely to grow as cybercriminals become more skilled in infiltrating technology architectures and systems that weren’t designed from the ground up through a security lens. Ironically, concerns about cybersecurity could—and perhaps in some cases should—slow the adoption of other trends that drive innovation.

Organizations with a sophisticated approach to cybersecurity are no longer satisfied with locking the doors after the robbery has been committed. International Data Corporation (IDC) estimates that US federal government agencies alone would spend more than 14.5 billion dollars on IT security this year, and the worldwide financial services industry would spend 27.4 billion dollars on information security and fraud prevention. Now that’s a lot.

Going on the Offensive

Organizations such as these are beginning to employ more predictive approaches to threat intelligence and monitoring. In short, they’re going on the offensive. This may mean automated scanning of Internet “chatter” by far-flung groups and individuals who may intend cyberharm.

It may involve analyzing past hacks and breaches to create predictive models of which threats are likely to surface next. In many firms, it also means systematic and continuous probing of the organization’s own defenses to make sure that others don’t find a security hole first.

A Moving Target Creates New Demands

Companies adopting these types of offensive steps will no doubt find that they need new capabilities. Many cyber professionals don’t have the skills to do predictive threat intelligence or predictive analysis of past breaches. At the very least, extensive collaboration between analytics and cyber professionals may be required. And cybersecurity projects will need to rapidly move up the priority list for analytics groups.

You can bring your data flow to its highest and best uses or you can let it languish while you guess and your competitors pass you on the back stretch. And you DO NOT have to bet the farm and the horses to get where you want to go with your data assets.

We are a good match to be your analytics thought partner and trusted virtual team that delivers your data to your dashboards. And we know how to interface with security teams.

Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512-478-3848to start a friendly, productive conversation.

Data-Based Analytics Accelerates Performance and Innovation

June 8, 2016 by MIAWebAdmin

The data used needs to be function- or workgroup-specific. For example, if “sales dollars” has been identified as a critical business outcome for the sales team, you will incorporate and statistically link the sales leader’s/rep’s 360 assessment data to the “sales dollars” outcome.

Using advanced analytics (e.g. structural equation modeling) as your methodology, you can identify which components of the 360 assessment (i.e. behaviors, knowledge, skills, and abilities) are key drivers of specific business outcomes for the various functions or workgroups being analyzed.

Specifically, the results of the analysis indicate the differential impact that each of the competencies evaluated using the assessment has on the key business outcome (i.e. how much improvements on each competency will contribute to improvements in the overall business outcome).

Discovering the competencies most responsible for business outcomes allows HR leaders to make data-driven decisions regarding where to invest developmental efforts and dollars and how to demonstrate a return on these investments on the back end.

Innovation has always been a key force in changing business and society. More and more, innovation is occurring as the result of aggregating and analyzing data to create new products and services. The Internet of Things (IoT) is evolving quickly from the arena of interesting gadgets to include tracking people to form new business models (think Uber) and to influence people’s behaviors.

A truly competitive enterprise needs a contemporary, on-call set of analytics that supports big data and everything else and is based on a streaming architecture. This is the era of visual analytics at the speed of thought. Performance improves and business outcomes accelerate.

You DO NOT have to bet the farm and the horses to get where you want to go with your data assets. We are a good match to be your analytics thought partner and trusted virtual team who delivers your data to your dashboards.

Our Austin, Texas location puts us at the epicenter of planning analytics and data-driven innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.

Let the Data Drive Direction, Not Wishful Project Planning and Spending

June 1, 2016 by MIAWebAdmin

The trend of shifting from inpatient planning to ambulatory planning will continue this decade. Considering only what the inpatient bed need will be in five to 10 years is limited in nature and could harm your organization, especially with the shift to value-based care.

Outpatient surgical cases, imaging procedures, and triage and trauma visits are where organizations are seeing more growth on average nationally; therefore, it is important for healthcare leaders to understand their impact and plan to deliver these patient services.

Clinic planning needs to be the foundation for all strategic planning. Whether you are a critical-access hospital or a large health system, the basis for future planning is dependent upon your physician and mid-level (i.e. physician extenders) planning.

This data is important as designers help to better understand the drivers and considerations to best plan and utilize hospital funds or future project budgets.

When undertaking clinic planning, important tactical items for management to consider and focus on include physician supply, recruitment, and in/out-migration of patient demand.

Technology, policy, value-based care, regulation, data availability and connectivity, and other factors are driving transformational change in healthcare. Healthcare leaders and board members need to understand these factors and leverage available resources to both plan for asset optimization now and for the future shape of wellness care.

The traditional approach is no longer enough. As a healthcare-focused firm, Management Information Analysis can offer many different partner and resource options in order to best provide direction and insight to a project before heavy dollars are spent on planning, especially brick-and-mortar projects.

Together, we can be better informed, determine right-sized needs, and plan for flexibility.

Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven innovation and keeps our global capabilities and services at the forefront of our industry.

Call us to start a friendly and productive conversation. 512-478-3848.