Analytics for the Business

Everybody has metrics on their customers and sales. These are typically one dimensional - sales by customer, sales pipeline by stage in the sales process, customer satisfaction score. One metric based on one data source. These lack insight, are not actionable and give a false sense of understanding the business performance. How about some real analytics that can help real sales executives drive real revenue and profits with real customers? We believe analytics have 3 characteristics:

1. Incorporates different types of customer data (financial, operational, customer satisfaction; historical and projected)

2. Understands both performance and the root cause of that performance

3. Empowers users to act on the insight

We believe there are eight analytics that will help drive customer profitability along three key dimensions:

· Focus on the right customers

· Improve sales team performance

· Improve performance for customers

These analytics include:

1. Product / Customer Growth Matrix

2. Customer Experience Map

3. ...

Join us for a webinar discussion on October 28 to learn more about these metrics and analytics.

• Services data resides in many disparate planning and execution systems across various locations and business units

• The Service Enterprise is typically geographically dispersed and the customer and install base footprint is ever-changing

• Leaders lack integrated views and cannot analyze their business across dimensions such as offering & event types, business units, customers, product lines, regions, and segments

Success requires that multiple sources be accessed and integrated to achieve complete customer visibility and Service Enterprise optimization.

If you lead a Services Enterprise P&L or Cost Center, lead a Services Sales, Marketing or Operations function, or are responsible for customer advocacy and experience, join us for an upcoming Webinar that will:

1.Provide the opportunity to learn more about specific findings from Aberdeen's June 2009 Service Benchmarking and Measurement research report and illustrate what Best-in-Class Service companies are doing to leverage their disparate data and KPI's

2.Highlight examples from Thermo Fisher Scientific where integrated data is providing opportunity and an enhanced customer experience

3.Introduce a unique technology platform to help drive your Service business and customer experience

Hidden Benefits of Business Intelligence

Gut Check: Managing Data Proliferation to Create Opportunity

Time for Supply Chain Management Leaders to take on Business Intelligence

The Economy: Good or Bad for SaaS Business Intelligence?

Take Time to Get the Metrics Right

Timeless Software at SAPPHIRE 2009

The 360 Degree View

Under The Customer Experience Big Tent

"I used to spend 30 hours assembling information in spreadsheets to understand and analyze the details of my transportation operations. With my Oco BI solution, I now spend minutes and am able to analyze any aspect of my operations. More importantly, I have time to work with my carriers and customers to address and fix the issues I find from our powerful Business Intelligence solution. I can act and see marked improvement, rather than run in circles." - Quote from Kevin Kilcoyne, Senior Manager of Transportation and Logistics, Welch's Foods.

I have always felt that managers and analysts in most companies spend 90% of their time assembling the information they need, and 10% really analyzing it and acting on it.  If a company can reverse this ratio and spend 10% assembling information and 90% of their time responding and executing, companies would be much better off.  I see thoughtfully applied Business Intelligence as a very effective way for companies to reverse this "prepare information vs. analyze and act" ratio.

It takes a lot for companies, customers, and vendors to alter behavior and make changes. However, when you free up time to work on these issues, it really make a difference.

Lessons from Best-In-Class Service Organizations

Gut Check: Managing Data Proliferation to Create Opportunity

Time for Supply Chain Management Leaders to take on Business Intelligence

The Economy: Good or Bad for SaaS Business Intelligence?

Take Time to Get the Metrics Right

Timeless Software at SAPPHIRE 2009

The 360 Degree View

Under The Customer Experience Big Tent

I do not believe anyone would disagree that we live in a time where available information is scaling exponentially both in the consumer and B2B domains. This can create both paralysis and opportunity at the same time. After all, a once small company you may have heard called Google has had some success bridging the chasm between data anxiety and opportunity.

In fact their corporate mission statement reads:  Google's mission is to organize the world's information and make it universally accessible and useful.  There are three thematic threads in this statement which are worthy of discussion to help focus the data proliferation solution:

1.Organizing and integrating data

2.Universal access

3.Usefulness

•Total Spend and Purchase Price Variance

•Supplier Cost Productivity

•On-Time Delivery

•Order Fill Rate

•Inventory Days of Supply

•Defect Rate

•Invoice Accuracy

Lessons from Best-In-Class Service Organizations

Time for Supply Chain Management Leaders to take on Business Intelligence

The Economy: Good or Bad for SaaS Business Intelligence?

Take Time to Get the Metrics Right

Timeless Software at SAPPHIRE 2009

The 360 Degree View

Under The Customer Experience Big Tent

• BI is providing a full view of the transportation spend for many companies, allowing them both a broader and a deeper view.  It is allowing visibility to the total transportation spend on contract carriers, common carriers, private fleet including all maintenance expenditures, and the transportation overhead.  So now, the full budget can be monitored and tracked at the lowest level of detail.

• In the inventory area, BI can bring all the information together to gain new insights, as well as the information needed to act to avoid problems.  BI solutions identify items at risk of excess inventory or stock-outs, and provide information in the same report on open purchase orders that need to be pulled in or pushed out to avoid inventory imbalances.  Beckman Coulter was able to reduce its global parts inventory by over 15% with a BI solution.

Advanced Metrics—Very few companies are able to track advanced supply chain metrics such as cost-to-serve, the perfect order, the vendor scorecard or customer, product or channel profitability. BI solutions are making these advanced metrics more easily available.

Collaboration—BI solutions, and especially web based Software-as-a-Service (SaaS) BI solutions, are increasingly being used for collaboration with customers, suppliers, and carriers.  It becomes very easy to allow a shared view of critical metrics and reports that keeps all parties aligned.  Moreover, we are seeing more Sales and Operations Planning Meetings (S&OPM) supported by BI that can allow manufacturing, inventory planning, sales and others to view and engage in “what-if” analyses using the same information during S&OP meetings.  This provides one version of the truth and allows much better communication among the participants.

What BI applications have you looked at or are using for supply chain management?  What benefits or issues are you finding? I welcome your comments.

Hidden Benefits of Business Intelligence

Lessons from Best-In-Class Service Organizations

Time for Supply Chain Management Leaders to take on Business Intelligence

The Economy: Good or Bad for SaaS Business Intelligence?

Take Time to Get the Metrics Right

Timeless Software at SAPPHIRE 2009

The 360 Degree View

Under The Customer Experience Big Tent

With the economy continuing to struggle, many people I speak with in the industry feel optimistic that the Software-as-a-Service (SaaS) business model is holding up well and is, in fact, poised to benefit.  If one were to look at the SaaS bell weather, Salesforce.com, it would be easy to support that argument.  The problem, however, is that while Salesforce.com is doing well in recent times (despite the gloomy economy) the vast majority of other SaaS vendors are either:

a) Privately held and therefore hard to gauge in terms of "how they are doing", and

b) Are still too young in their evolution...meaning that even if they were growing at a healthy clip in the down economy (ie: double-digit growth), it is hard to tell if "they are doing well".

Also, what metrics would one look at to assess growth for these firms?  What might be a meaningful metric to measure some of these firms may be far less meaningful for the others.

Measurements aside, here are some thoughts about why the SaaS Business Intelligence segment should be doing well:

• It's faster to deploy vs. on-premise, therefore, can provide faster business benefit
• It offers a better economic model vs. on-premise....lower TCO
• Customers can "stretch" their existing budgets more (the SaaS model usually means little-to-no capital expenditure) and still get a solution
• An already over burdened IT staff can off load much of the low-value work associated with hardware provisioning, software provisioning, software configuration, database tuning, backups, etc. to the SaaS provider...therefore freeing them to focus on higher-value tasks to support the business
• Some SaaS Business Intelligence offerings are geared to specific functional areas and business problems and can therefore drive some tangible business benefit (ie: Inventory Cost Reduction, Increased Customer Retention, Lower Transportation Costs, Improve Gross Margins, etc.).

These points all make sense to me.  If you were to say to a CFO..."you can have a BI solution up and running in 8-10 weeks, with little-to-no upfront investment, minimal disruption to your IT staff, and it would be well aligned to your strategic business initiatives..." why wouldn't he/she not want to give it a try?

Here are some reasons why many organizations are still not making the leap to SaaS BI:

• The SaaS model is disruptive to many of the traditional ways of procuring and deploying software....it's different, therefore, it requires change and a lot of people don't like change
• The "trusted advisors" of many organizations are not recommending SaaS solutions yet because they don't fully understand the benefits and/or they have a vested interest in doing things the old way (meaning they make a lot of money from that)
• Control...the nature of SaaS is that if you are going to use a SaaS solution, a lot of things are no longer going to be in your control
• Trust...you need to take a leap of faith in your provider to trust that your data will be secure, your solution will be available/responsive and recoverable should there be a "disaster"
• Misplaced Fear...Many IT organizations are resistant to the SaaS model because they perceive it will impact job security.

But times are different now (didn't General Motors just go bankrupt?) and doing things the old way may not always be working anymore.  Can we afford not to look at new and different ways of doing things?

Lessons from Best-In-Class Service Organizations

Hidden Benefits of Business Intelligence

Gut Check: Managing Data Proliferation to Create Opportunity

Time for Supply Chain Management Leaders to take on Business Intelligence

Take Time to Get the Metrics Right

Timeless Software at SAPPHIRE 2009

The 360 Degree View

Under The Customer Experience Big Tent

Okay so you are ready to launch your customer experience and satisfaction initiative.  Referencing my initial blog on this site, "The Customer Experience Big Tent," the first critical activity is taking the time to understand and implement meaningful customer metrics.  You might be wondering why I even raise this somewhat self-evident topic.   Self-evident yes, but there are some nuances.  It all starts with a deep understanding and involvement with your customer... simply put you need to ask!  

 This planning activity is best framed by addressing two fundamental questions:

1. What should we measure?
2. How should we measure it?

1. What should we Measure:  The biggest risk at this stage is launching a customer satisfaction program and a metrics structure that is internally-facing.  The common response is "of course we know what to measure.  After all we have been working with these customers for years"... wrong answer.   To do this properly you need to have an outside-in mindset and internalize your custom's business.  The service or product provider's perspective needs to morph.  Metrics that are tracked and monitored need to reflect the real impact on the customer's business and processes.  The only way to do this is to invite the key customer stakeholders to the table and mutually define these metrics with them. This discussion should cover three distinct components:

Metric Selection: Understand the "Critical to Quality" (CTQ's) drivers of your customer's business and jointly define what metrics should be included in the program.  You must ask your customer's what measures are important to them and understand how they directly impact their business performance.  Metrics outside of the core operations, quality, and cost areas that you might consider of tertiary importance, might in fact be very significant.  Take for example paperwork accuracy and ease of processing (invoices, credit notes, warranty claims processing, etc) as some simple examples.

Customer Context: Define the chosen metric within the context of how it impacts your customer performance and process, not on how you conveniently like to track the measure. Let's take a simple example from relevant capital equipment industries where a services repair depot operation exists.  Instead of measuring classic repair depot turn-around-time (TAT) from shop induction to shipment from the depot, one might instead calculate end to end TAT as time measured from shipment from the customer facility to the time the unit was received back at the same facility for re-installation into service (dock-to-dock).

Thresholds and Limits:  Establish mutually agreed to Service level Agreements (SLA's) with clear thresholds of what constitutes good, neutral, and needs improvement performance.

2.  How Should we Measure It:  Do not forget about process variation measurement.   Most customer-facing organizations measure their performance and impact to their customer's business based on average performance.  While important, it is perhaps more relevant to measure and communicate your process variation. Of course customer's desire both world-class average performance that is repeatable (low standard deviation).  However, best-in-class average performance with wide process variation is problematic.  Take on-time delivery (OTD) as an example.  Imagine you had industry leading (top 15 percentile)  OTD metrics but:

• You missed a critical flight-line spare part component shipment date for a commercial airline resulting in the cancelation of a 747 and the need to reschedule 200+ passengers
• You missed a spare part shipment for a MRI device in need of repair in a major regional hospital resulting in patients being turned away for critical imaging tests
• You missed a spare part shipment to a semiconductor fab resulting in critical equipment downtime costing hundreds of thousands of dollars per hour of facility downtime

For all of upcoming meetings with these customers I suggest not leading with your industry leading average OTD charts.  The bottom line is if you understand and can effectively communicate your process repeatability or variation then customer's can plan around this.  They might for example stock a higher level of safety stock... more expensive, sure, but better than the impact and associated costs of the scenarios identified above.

This variation analysis doesn't need to a rigorous standard deviation exercise. Simply measuring and tracking some proxy for variation with mutually defined thresholds starts to get at the issue. For example, the number of times this month that a delivery date was missed.

Next up on this customer experience blog topic will be a discussion on the importance of Data Breadth & Reporting --- Providing interactive, intuitive, and accessible measurement, analysis, and reporting solutions that considers all cross functional data and sources.

Léo talked about innovation without business disruption and benefits including less time deploying and less time managing the software.  These are truly benefits of cloud computing or timeless software.  However, more importantly, the idea of innovation quickly delivered is where the real value lies.  Software-as-a-Service solutions are typically deployed very quickly.  In the case of SaaS Business Intelligence, these solutions are up and running in weeks, often providing unique insights into the business that were previously not visible or simply took a laborious manual process to achieve. 

And the hits keep coming.  SaaS models allow for continuous enhancements in the form of functionality, unique analytics, and best practice approaches to be rolled out seamlessly to customers and users.  That is, innovation out of the SaaS providers engineering department right to the customer with an upgrade over the weekend. 

Innovation in the SaaS model is not one way.  Customer feedback, usage and requests for enhancements play a role in identifying where the next innovation lies.  This isn't new in the software industry.  However, the ability to take that input, incorporate it into the solution and roll it out to the user base in 3 months is unheard of in the traditional on-premise software world.

In summary, timeless software is really about real-time innovation.  Getting ideas understood, incorporated and deployed faster than previously possible.  At the end of the day, software is an enabler for people and processes.  Improving that software as quickly as possible to "move the needle" for users is where the value lies. 

What do you think?  Are the biggest SaaS benefits around getting innovation in the hands of the users quickly or around the well told total cost of ownership?

Recommended Reading:

• Calculating ROI for Business Intelligence Solutions in Small and Mid-Sized Businesses
• What You Need to Know About Business Intelligence TCO
• BI for SMBs, Part 3: Driving Down TCO
• Managing the TCO of Business Intelligence

The Power of Disparate Data Integration Delivered via Software-as-a-Service (SaaS) Business Intelligence

When speaking with prospective partners and customers I frequently talk about the power and value of a "360 Degree View of the Business".  I have come to use to this term to describe the importance of integrating disparate data into a meaningful data model in order to drive deeper insight into a particular functional area.  Of course, this idea is nothing new as it forms the basic premise of an enterprise data warehouse or data mart. 

Using Inventory Performance as an example in the diagram below, one can see that the key metrics required in order to thoroughly uncover opportunities (like Inventory Reduction) come from multiple places.  Further, the dimensions that an Inventory Planner may want leverage probably exist in more than one place.

My argument, however, in distinguishing a broad enterprise data warehouse from a purpose-built Business Intelligence solution delivered via SaaS, is that the former takes a lot of time, money, technology, and human capital to develop, deploy and maintain.  In addition, enterprise data warehouses seldom start with a specific end in mind (the goal is usually to build a comprehensive environment for lots of people in an organization to use).   Several SaaS Business Intelligence vendors have developed unique tools to significantly accelerate the data integration and data mapping process. This capability, combined with taking more focused scope, allows for the population of a warehouse with the associated linkage of analytics and reporting in one to two weeks versus many months for a traditional approach.  And these SaaS BI providers can deliver a complete production-ready solution in just six to ten weeks.

With the emergence of Business Intelligence delivered in a Software-as-a-Service model, there are now solutions available to line of business owners that are focused on delivering tangible business benefits in a rapid time-frame, at an affordable price point (often in a pure subscription model) and with minimal investment of human capital (sure, you still have to provide the data and provide requirements, test the output, etc.). 

What are some of the capabilities that should be considered when evaluating a SaaS Business Intelligence approach?

• Data Integration in the Cloud - the solution must be able to effectively and efficiently incorporate the disparate streams of data coming from the pertinent source systems
• The target data model must not only be designed to store the data, but it must also have context - not only in terms of the data itself, but also the relevant dimensions, behaviors, transactions and customer-specific business context (this being org structure, nomenclature, etc.)
• Security and data privacy - a high degree of both should be provided and well documented
• Comprehensive data representation - a broad mix of tools and capabilities for reporting and analysis - Dashboards, Exception Reports, Multi-Dimensional Reporting & Guided Analysis, Ad-hoc Query & Analysis, etc.
• Time to Value - The solution must be delivered in weeks, provide adequate flexibility to be changed as needed (the speed of business today isn't what it used to be...it's very fast!)
• Should compliment an organization's overall Business Intelligence strategy - allowing you to leverage existing investments whenever possible (tools, data sources, skills, etc.)

If you have been struggling with a limited view of your business, perhaps now would be a good time to consider such an approach. 

Please don't get me wrong there are some very good insights and dialogue in this area.  In fact one of my favorite thought leaders in this area, Bruce Temkin, has a very comprehensive blog of his own, Customer Experience Matters.  As expected, he comments on the NPS science, along with other customer-centric topics, and is quite comprehensive, especially in the consumer products domain. But what strikes me in all of this discourse is the relatively little attention given to the rest of the story, that is, the critical intersection of customer satisfaction with operational performance, and strategic account significance... perhaps measured by revenue growth and total spend.  Being able to quickly analyze your business and customers within the context of a three-dimensional Customer Experience Map (see below example) by any relevant dimension (segments, product-lines, regions, business units) enables alignment of execution with strategy, targeted resource prioritization, and the identification of meaningful growth opportunities.

Let's pose some simple questions:

• How do you quickly understand the operational performance of your team, services, or products for strategic customers with a demonstrated propensity to spend across your offering portfolio?
• How does actual operational performance compare to customer perception and satisfaction scores?
• How do you effectively perform root cause analysis for poor performing areas?
• What is the real or actual cost-to-serve for each customer or segment?
• Can we provide better insight and communicate more effectively with customers?
• Who are the most profitable customers and segments and are we allocating the appropriate resources at these accounts?
• Is our NPS distribution across the customer base "okay", what should the targets be, and what constitutes a sustainable NPS improvement program?

Relevant and I imagine top-of-mind questions, for any business leader.  I would not expect much argument on this point. The real challenge is how effectively and quickly can you reply to these issues and chart the right course?  Does measuring NPS or any other customer perception / satisfaction score in isolation get you there?  Of course not... you need a 360 degree view of the customer and a prescriptive customer execution journey to nourish and leverage your most important asset.

Based on years of working in customer facing roles at General Electric, including leading a global support business and driving the Six Sigma Customer Dashboard initiative, I found there are five principle tenets required in any successful customer initiative:

1. Get The Metrics Right --- Take the time to understand and implement meaningful customer defined metrics and processes... you need to ask!
2. Data Breadth & Reporting --- Provide interactive, intuitive, and accessible measurement, analysis, and reporting solutions that considers all cross functional data and sources
3. Customer Experience Mapping --- Deploy a dynamic Customer Experience Mapping (CEM) rigor that integrates customer, operational, and financial information for a 360 degree customer view
4. Enterprise Accountability --- Instill a culture of customer accountability across the enterprise... it is not the sole responsibility of the services team

And my personal favorite

5. Action & Response Plans --- Don't ask for your customer's input or relentlessly measure your teams, processes, and operations unless you have the bandwidth and focus to implement and communicate fixes with achievable timelines. 

"You can't create a reputation on what you are going to do"... Henry Ford

I will expound on each of these foundational bedrocks in upcoming blog posts here.  Stay tuned, and until then, keep those assets smiling!