Can I Ensure That My Analytics Project Gets Approved?

You have decided that your business can benefit from an analytics solution. Now, it is time to convince your executive team, your managers and your users. If you are to gain approval for your initiative, you must take the right approach.

In this article, we discuss some of the primary factors you must consider to build and present your initiative to the various audiences within your organization.

How Can Assure Approval of My Analytics Project?

A four-year study of businesses implementing analytics solutions found the following:

  • Less than 50% of the businesses reported measurable results
  • Only one third of the businesses met their objectives for user adoption
  • 77% said that user adoption was a challenge
  • Only 20% reported that analytics insights provided positive business outcomes

Before you give up on your initiative, consider this: most software projects fail because of poor planning and execution. So, if you can plan appropriately, you will be way ahead of the game. Here are a few factors you will need to include in your review and planning process.

IT Team – Be sure you include your IT team in your planning. You will need a comprehensive understanding of your existing technology, hardware, network and devices and you will need the help of your IT team to assist you in planning roll-out, estimating the cost of new technology to implement your plan, and interviewing prospective solution vendors and service providers.

To Gain Their Buy-In: Involve them, and ask for their opinion. Build a plan and allow them to review it and comment. Listen to their concerns. Ask for their support in working with users. Ensure that the vendor you engage will provide support for IT so that your IT team is not overwhelmed with new and expanded tasks and responsibilities.

Executives – Senior executives will be looking at investment costs, return on investment (ROI) and the total cost of ownership (TCO) and at the value you claim this solution will provide. Be prepared before you approach your executive team. Be sure you have involved all the right players and include representatives of these groups to address concerns and answer questions if the executive team wants to probe and challenge.

To Gain Their Buy-In: Be prepared! Keep your presentation at a high level, but be sure you have the details to answer their questions if and when they arise. Provide more detailed reports for them to peruse at their leisure. They probably won’t dive in, but they will be reassured that you have done your homework. Focus your presentation on a) reduction of cost, b) competitive positioning with EXAMPLES of how analytics will help achieve these goals, c) doing less with more and making the company more productive.

Managers – Managers will be concerned about putting more strain on business users and team members and, since the modern approach to business intelligence and analytics involves the business users and their transition to Citizen Data Scientists, you must focus on the managers and what’s in it for them. How does this help them to do their job? They are accountable for results, and they only have so many team members to get the job done. They are also evaluated, based on how their employees see their management style and effectiveness, and they will not want their team to complain.

To Gain Their Buy-In: Focus on their business processes and workflow and how augmented analytics and business user involvement can speed the process, ensure more fact-based decisions and make the managers look good, without putting more strain on the business user. Ensure that your vendor and IT team have a plan to reassure the managers so that they don’t worry about the use of sophisticated systems that will take a lot of training time. How will the roll-out be done? You want a controlled approach so that users are not spending a lot of time getting up to speed and neglecting day-to-day tasks.

Business Users – As usual, the buck stops with the team member. They are the ones who will be asked to change their processes, learn new systems and take on new responsibilities. Look again at the survey results reported above and notice how poor user adoption affected analytics projects. If you can’t get your users to adopt the solution, your project will fail. Your executives, IT team and managers may think this is a great idea, but they will blame you if the team does not respond positively. Involve users in advance to gather and thereby anticipate their concerns when you present your findings and your plan. Do not be defensive. Listen to their issues and incorporate those concerns into your review and selection of a vendor and a solution. With the right self-serve augmented analytics solution and service provider, you can assure them that a) the system will be easy to use and won’t take a lot of time to learn, b) will make their job easier and c) will give them a career advantage.

To Gain Their Buy-In: Listen, digest and address concerns. Understand that there is a culture shift involved in this process and be sure you acknowledge that at all levels of your presentation, including your executive team. Let’s not pretend this new idea will not require change. It will. But if you work with all levels to assure that new responsibilities will be rewarded in employee evaluations and that the team will be supported by managers who are true champions of the process, you will be ahead of the game. Try to meet with users without IT and managers in the room, and then regroup with the appropriate staff (managers, IT etc.) after you have had a chance to evaluate and address user concerns. Users are more likely to be receptive if they aren’t put on the spot. BUT be sure to control the discussion and the environment so it doesn’t turn into a complaint session. When you are ready to do your sales pitch and you have addressed all their concerns, focus on the user and their hot buttons. Tell them how this solution will help them and assure them that the vendor and your implementation team will be there every step of the way. And then follow through!

For more information and details on how to plan for and achieve success with an augmented analytics solutions, read our free articles: ‘A Roadmap to ROI and User Adoption of Augmented Analytics and BI Tools,’ ‘Making the Case for Embedded BI and Analytics,’ and ‘Integrate Augmented Analytics and Digital Transformation to Achieve Continuous Business Improvement.’

In this article, we have included just a few of the considerations and factors you will have to address in order to build a plan for your Augmented Analytics project. It is a good idea to engage an IT expert – one with the skills and experience to anticipate your concerns, work with you on industry and business issues and plan for a small, medium or large enterprise installation. An expert team can help you manage the technology review and requirements, and plan for your presentation, etc. Be sure you choose a vendor with sophisticated augmented analytics features and functionality in an easy-to-use environment that will support the transition of your business users to Citizen Data Scientists and ensure that your project will succeed. Contact Us to find out how we can help you plan and achieve your goals. It really IS possible!

Case Study : Smarten Augmented Analytics Case Study- Pharmaceutical, Clinical Research and Innovation Company

The Client is a global business governed by a foundation whose mission is to have a meaningful social impact, both for patients and for a sustainable world. With its unique governance model, the Client business can fully serve its vocation with a long-term vision and fulfil its commitment to therapeutic progress and to serving patient needs. The company has grown exponentially, first across France and then throughout the world, driven by the transformation of the business.

Predictive Analytics Business Use Cases Ensure Results!

Apply Predictive Analytics to Specific Business Use Cases for Real Results!

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Your business, like every other business in the world, has its own industry, domain and vertical concerns, and these concerns drive your competitive strategy, your products and your services.

Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. These techniques can help the business drive results, improve revenue, understand customer and client buying behavior, solve problems, plan for new locations and products, create accurate pricing strategies and plan for new resources and training, as well as for appropriate maintenance, supply chain services, etc.

‘Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.’

Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques. These techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.

In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies.

Minimum Viable Products (MVP) Produces Better Business Start-Up Results

Customer Churn

The cost of acquiring and interacting with customers can be expensive and each time a business loses a customer, it must spend money to replace the customer.

Fraud Mitigation

Businesses must mitigate fraud and control business costs and must develop and sustain fraud detection processes to monitor operations.

Quality Control

Businesses must control quality or risk losing customers and market share and exposing the enterprise to legal risk and liability.

Demand Planning

Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.

Product/Service Cross-Selling

Leverage customer satisfaction to cross-sell and upsell products and services and increase revenue and brand loyalty.

Maintenance Management

Focus on equipment maintenance to ensure that downtime is limited and equipment is up and running, anticipate resources, hours on the job and training needs.

Customer Targeting

Identify the reasons customers buy a product or service and use fact-based data to create products, marketing campaigns, ads and customer outreach. Target specific demographics and customers.

Human Resource Attrition

The enterprise must retain team members and to do so, it must understand what makes a team member stay or go, what makes them invest in the future of he business and what issues create issues and dissatisfaction.

Loan Approval

The enterprise must avoid bad loans, so as to enhance profitability and productivity and it must have a dependable process for identifying and attracting the right clients and for reviewing, approving and managing loans.

Marketing Optimization

Create attainable targets and goals with an understanding of what improves and affects sales and how customers choose a product or service, how to market and advertising to achieve objectives.

Predictive Analytics Using External Data

Integrate external data and analyze data to assess the affect on sales, marketing, finances, resources, productivity, etc.

Online Target Marketing

Optimize marketing funds and resources, understand what works and what does not work, and how, when and where to message and the ideal demographic and profile of the target customer.

Student Academic Performance

Predict academic performance of students to effectively manage student interaction and training and improve environment to assure student success.

Crime Type Prediction

Predict the type of crime that is likely to occur to plan for appropriate law enforcement resources, placement and strategies and ensure public safety and appropriate use of funds.

‘Predictive Analytical techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.’

Find out how Assisted Predictive Modeling and Augmented Analytics can help your business plan for success, and explore the potential of comprehensive Predictive Analytics here.

Get the Right Predictive Analytics Tools for Users!

Can Predictive Analytics Provide Accurate Results for My Business Without Burdening My Users?

If your business is struggling to forecast and predict outcomes and results, your management team is probably considering predictive analytics. The technology research firm, Gartner, states that, ‘50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage.’

For the average team member, the concept of predictive analytics may seem daunting and, if you are a business user whose management team has asked you to embrace and participate in analytics, the addition of predictive analytics to your day-to-day business processes may seem irrelevant or it may seem to mean you will be expected to work harder or produce more output. But don’t be too quick to assume the worst.

‘By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization.’

Let’s take a look at Predictive Analytics, the benefits of Assisted Predictive Modeling and its importance in the organization and how intuitive augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.

Predictive Analytics Can Make Business Users Happy!

What is Predictive Analytics?

Predictive analytics is comprised of sophisticated analytical methodologies that allow businesses to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques.

Understanding Assisted Predictive Modeling

When a business provides augmented analytics tools for business users, it allows the team to perform predictive analytics on a daily basis without the assistance or skills of a Data Scientist or an IT professional. Assisted Predictive Modeling provides auto-suggestions and recommendations to guide business users with recommended techniques, selecting the most appropriate techniques for the type and volume of data the user wishes to analyze. If the business chooses an augmented analytics tool with intuitive predictive modeling features, it allows users to work quickly and receive clear, concise results for decision-making so user adoption of the tools is more likely and forecasting and predictions are accurate and timely. All popular predictive modeling techniques are incorporated into the solution, so users have access to the most sophisticated predictive analytics and tools and can use these tools to model and review business use cases and issues.

The Benefits and Importance of Assisted Predictive Modeling

These tools allow the organization to apply predictive analytics to real use cases to analyze customer churn, to target customers, to identify cross-selling and product bundling, to find and set appropriate price points, to forecast where and when to open new locations, when the business will need new suppliers, when equipment will require maintenance, etc. A comprehensive augmented analytics solution also includes the benefit of integration with R Script, so that data scientists can capitalize on expertise and leverage enterprise investments in R open-source platforms, to perform statistical and predictive algorithms, and complex analysis to provide the depth of detail and advanced analytics and reporting the organization needs for strategic decision-making. By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization, encourage collaboration and data sharing, and improve data literacy – all without increasing workload or frustrating users and team members.

‘Intuitive assisted predictive modeling and augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.’

Find out more about Assisted Predictive Modeling and Augmented Analytics and explore the potential of comprehensive Predictive Analytics here. Find out how it can improve user adoption of analytics and increase accuracy of forecasting and results.

Why Does My Business Need NLP Search Analytics?

The What and Why of NLP Search Analytics and How it Can Help Your Business!

If your business is considering an advanced analytics solution, your IT and management team has probably already done some research and concluded that the concept of augmented analytics designed to support business users is the right way to go. To democratize data, improve data literacy and transition business users to the Citizen Data Scientist role, the business must select the right solution and plan for success.

Assisted Predictive Modeling is Your Secret Weapon!

Predictive Analytics That is Easy Enough for Any Business User!

Predictive analytics may seem too complex for business users but with advanced technology like machine learning and features like assisted predictive modeling users can dive into the process without the skills of an IT professional or a data scientist. Assisted predictive modeling frees the user by providing system recommendations that will suggest the right analytical technique and achieve the best fit for what the user wants to do, ensuring that they use the most appropriate algorithm for the data they wish to analyze.

What’s So Great About Augmented Analytics?

Why I Won’t Stop Talking About Augmented Analytics!

What Are the Benefits of Augmented Analytics? Where Do I Start?

Those who know me are probably tired of hearing me talk about the benefits of Augmented Analytics. To them, I say, ‘I am sorry’. I am about to talk about it yet again. The reason is simple. Most businesses are either considering the addition of augmented analytics to democratize data, improve data literacy and create Citizen Data Scientists OR they are still unconvinced and feel that they are just fine. Either way, your business professionals and managers can use a primer on the benefits of augmented analytics, whether it is used to support their decision or to convince the team that augmented analytics should be pursued!

Answer Your Business User Concerns About Augmented Analytics!

Users Might Think Augmented Analytics is Too Difficult. That’s Not True!

If you are a business manager who wants to enable a Citizen Data Scientist environment, but you find yourself up against resistance, it is often because your business users believe that advanced analytics is just too hard for them to learn and that the use of these types of techniques and systems will slow them down and confuse their otherwise familiar processes.

How to Assure Citizen Data Scientist Success!

Enterprise Culture Change Assures Success of Citizen Data Scientist Initiatives!

Many businesses have embraced the Gartner prediction that transforms business users into Citizen Data Scientists to help organizations democratize analytics with simple tools that will improve the quality and timeliness of decisions. You can read white papers, industry articles and other publications that will support and articulate this approach to business flexibility, agility and success. But, if you do not embrace the culture change required to deploy this strategy across your enterprise, your Citizen Data Scientist initiative will not succeed.

Combine Data Literacy and Digital Transformation!

Is Improved Data Literacy Really THAT Important for My Business?

Why do your business team members need to be data literate? If your business is like most, it struggles to keep up with trends and to understand whether, when and how to implement enterprise-wide initiatives. You must convince your senior team and board of directors that these changes (which may be time-consuming and costly) are worth the effort. So, when a business manager says that her/his team needs to be more data literate, these same questions will arise.