Businesses have more information stored on their customers and their business processes than ever before, which adds complexity in trying to collect, manage and interpret data into information that can help guide a business to success. Here are ten ways to use analytics to handle this complexity.
1. Get organized and get feedback.
The first step to any goal is to get organized. This could be an entire post in itself, but put simply, get rid of clutter in your computer and on your desk. Obstacles like bad file management (on your desk and in your computer) can eat up valuable brain cycles and time. Second, know what your resources are. This includes people, places, and things. Third, know where you want to end up. Begin with the end in mind. And four, which related so the first, have a place to store the plan once you create it. If you’ve done this before and have templates, use them. If you’re comfortable with a specific type of software that can help you, fine – use it. But don’t mistake learning a new process for moving forward on a project. Only tasks that move the project forward can be considered ‘working on the project’. If you have no idea what business analytic tools to use or where to start, go on to idea 2.
Web resources like Google Analytics can show you how far you’ve come in many customizable ways–number of visitors, sales goals, conversions, traffic sources, and top content. It can also tell you were your visitors are located, how long they stay on the site, which pages they enter and exit, and what day of the week they tend to visit. All of this information helps you know your visitors so you can improve their experience and improve your sales. Social places like Facebook, Twitter, & Youtube are also great places to get feedback from visitors on the products and services you offer. The more information you collect, the better your business will be. It’s true – content is king, but what you do with that content can make all the difference in the world.
2. Look for business analytics tools that are easy to use, flexible, and support a wide range of roles.
Usability and functionality—that is, business capabilities—stand out as manufacturing organizations’ most important considerations in selecting business analytics regardless of company size, individual role or functional area. These should be central focuses in evaluating tools. To be usable and functional, analytics systems must provide a range of options for how to include the information in presentations, which are increasing; participants indicated an interest most often in the standard charts, reports and tables. However, documents, visualizations such as gauges and sliders, text, Web pages and maps were also identified as important by one-third to one half of these companies. Determine which of these are important to your organization today and may be tomorrow.
The most important capability for an analytics system is to make it possible to search for specific existing answers. Because anomalies are common in business, individuals need to be able to drill down to find underlying causes. The second-most frequently chosen capability is exploring data underlying analytics, also deemed important or very important by nearly three-fourths. The participants rated similarly (22 percent to 28 percent deemed them very important) four other capabilities: to publish analytics and metrics; to explore data by working with maps, charts and tables; to set alerts and thresholds; and to collaborate in the review of analytics. The most important capability is being able to source data for the analytics. Without this capability it’s difficult to compile meaningful analytics. Equally important is the ability to take action based on the outcome of the analytics.
3. Prepare for growth by analyzing personnel.
Most people who have primary responsibility for designing and deploying analytics have experience with sophisticated tools. About half the time, analytics are designed and deployed by the business intelligence department, a data warehouse team, or by general IT resources. Line-of-business (LOB) analysts are involved the least, but in some cases collaborate. It helps when IT and the (LOB) work together on analytics. One example is to document tasks and documentation for each item in a ‘process map’ so that you are prepared for if you need to split a role, hire, or outsource some or all of those tasks due to volume or an influx of new tasks. The LOB analyst can then begin building a ‘staffing model’ which multiplies task volume by average task times to anticipate future personnel needs and analyze current business practices.
4. Assess the maturity of your business analytics.
While the Ventana Research Maturity Index placed 12 percent of respondents at the highest Innovative level in their use of analytics, 60 percent are in the bottom half of the maturity hierarchy. In people-related issues, the index identified lack of skilled resources and lack of executive support. Process-related issues included taking longer than a week to provide metrics from analytics, formally reviewing metrics no more often than quarterly or annually and low prioritization and lack of budget. In information-related issues that negatively impacted business analytics use, the research identified stale, outdated and inaccurate information as well as failing to prioritize basic informational needs. In the category of technology, the research found immature technology that is not working, unsophisticated technology known to be ineffective and a failure to prioritize forward-looking and predictive analytics. These shortcomings all impede a manufacturing organization’s effectiveness and performance and all need to be addressed.
5. Ensure business analytics are widely accessible.
In Ventana’s overall research on business analytics, only one-third of senior executives and one-fourth of vice presidents, directors and managers have analytics always available. While it is true that a large majority of executives have most of what they need, this is insufficient for optimally effective performance. Almost nine in 10 manufacturing organizations regard making it simpler to provide analytics and metrics to those who need them as important or very important. Also keep in mind that doing this from mobile devices such as smart phones and tablet computers will only increase in demand; already more than one-third of participants said this is important or very important.
6. Don’t let inferior data undermine use of business analytics and metrics.
Business analytics should be about determining what is happening and will happen to an organization. Most time is spent waiting for data, preparing data, and reviewing it for quality and consistency. Conversely, only a fraction of time is actually spent on true analysis processes such as assembling scenarios, searching for causes, and determining how changes will impact current business. If these preparation obstacles could be addressed, the amount of time people work with analytics could be reduced. Take steps to ensure your source data for analytics is both fresh and correct; if it isn’t, you risk undermining the use of metrics and KPIs as business improvement tools.
7. Replace spreadsheets as tools for business analytics.
Spreadsheets are well established as a tool for analysis in organizations of all kinds and sizes, but they are ineffective for repetitive analyses shared by more than a few people. Spreadsheets are the tools companies most commonly use to generate analytics, business intelligence technologies (for querying, reporting and performing analysis), and analytic warehouses and databases, but while they may be familiar, organizations using spreadsheets least have more accurate, timely data—and they deliver periodic reports about 40 percent sooner. Organizations should limit the use of spreadsheets as data stores and for repetitive analyses, particularly in cases where the results are reported to and used by more than a few people. Their failings, limitations and necessary work-arounds undermine the needs identified by participants to simplify analytics and metrics and ensure technology usability in the process of producing business analytics.
8. Understand the value of predictive and forward-looking analytics.
Predictive analytics can give a business glimpses of what may happen, the consequences of actions and scenarios for how to respond to change. Technology has advanced to a stage where it is feasible to provide them to a variety of users in manufacturing businesses. Yet the research shows predictive analytics are not yet high-priority analyst capabilities for the lines of business (LOB) nor are what-if and planning-based analytics; each is deemed very important by less than 30 in the LOBs. Exceptions were contact centers, in which predictive analytics ranked second-most important, and supply chains, where they are third-most important. Finance departments are the least likely to use predictive analytics even though they could be widely applicable within this function.
9. Resources must be adequate to enable investment in technology to make analytics easy to access and use.
Driving change and addressing barriers require understanding the benefits of investments. Demand that vendors show how their products deliver clear benefits such as these and address issues such as total cost of ownership and return on investment that can help lower the barriers in your organization. Consider cloud computing for deploying for business analytics. Slightly more than half of manufacturing organizations still prefer on-premises deployment for business analytics, but the research found a significant preference for software as a service, or cloud computing. Consider evaluating if your organization is looking to avoid the effort and expense of having in-house technology resources manage your business analytics.
10. Address barriers standing in the way of improving business analytics and performance.
The most significant barriers to making changes in analytics are fundamental:
- Lack of resources
- No budget
- A business case that is not strong enough
- Too low a priority assigned to the effort
To make matters worse, these barriers are interrelated. Failure to provide a compelling business case results in a project receiving a low priority and therefore not being allocated the resources or budget sufficient to implement the changes. And a failure to properly organize, begin with the end in mind, and forging on without gathering feedback, will all be obstacles in the way of having a successful project or business.
