President's Management Advisory Board Part 2

Uploaded by whitehouse on 11.07.2012

Speaker: Gigantic.
Speaker: (inaudible) Dennis' thing up?
Speaker: (inaudible).
Speaker: And he was a touch act to follow,
as was the earlier discussion on strategic (inaudible).
I'm going to actually --
Speaker: Dave, I'm going to ask you to try to pull this in
in about 35, 40 minutes so we back on schedule.
Speaker: Absolutely.
And I actually think, and I joked at the end of
Dennis' discussion that I could create a tie between the
national security (inaudible), and I wasn't kidding actually,
and you'll see what I mean in a minute.
But first let's go just over some basic information
on improper payments.
On slide 16, you see the scale of the issue that we have.
$115 billion annually in improper payments.
And this is an enormous challenge to
the federal government.
The chart there shows you that Medicare and Medicaid,
unemployment insurance and earned income tax credit are
the big players here.
What is -- just to ground everyone,
what is an improper payment from the federal perspective.
It's very intuitive, we send funds to the wrong recipient,
we do it in the wrong amount, and sometimes go and audit our
payments and there's no documentation,
so with the absence of proof, we call it an error.
Or we have recipients using two funds and in an improper manner.
And there's a whole range of different errors we see
in practical terms.
Just to give you a flavor, in the Medicare world,
we could reimburse a provider for a -- for an MRI,
but we go back and audit it and only a chest X-ray happened,
and so we just reimbursed for a procedure that was five or six
times more expensive than actually happened.
These are the types of things that can occur.
We also have in the Medicare world a huge challenge with what
we call medical necessity, so when a hospital admits a patient
for inpatient procedures, but you go back and you look
at the regulations, it should have been an outpatient,
that's very difficult to kind of fix,
it involves doctor training and Medicare outreach.
When you think about improper payments, before I move on,
I want you to think about it in terms of some buckets.
There are a bucket which is really,
really challenging to navigate and fix.
And medical necessity is an example.
Another example would be that the payment that the government
makes is based on household size,
or number of children living with the person who is filing
for the benefit.
We don't have a global childhood -- child residency
database to know.
So for example, earned income tax credit,
which is one of the big ones, to be -- to get the payment right,
we have to know whether that individual has lived with their
dependent child for six months or more during the year.
Very, very difficult to assess.
I don't -- we're not planning to focus our discussions on
that bucket.
There are, however, a bucket of errors that exist that are
within, we think, a greater degree of proximity of control
for us to fix, and those involve areas where we're making basic
mistakes because we're not integrating data effectively or
looking at data effectively, and included in that is where
we're being defrauded.
So, for example, we're not supposed to pay entities that
have been suspended or debarred by the government, yet we do so.
We do so because we don't have tools in place that better
integrate that information into our payment processes,
so we know before we make the payment has this person been
suspended or debarred.
It gets more complicated, but also (inaudible),
sometimes we have a company that is suspended or debarred,
and then they reincorporate themselves with a new name and a
new structure, and then they're back doing business with us.
We need to capture that.
And then you need more multi-dimensional analysis
of the data.
Another thing that we're not very good at at this period of
time when we're trying to get that.
And then there's obviously there's fraud,
there's identity theft, people setting up,
this happens to the tune of billions of dollars.
In particular, IRS faces that challenge where people
with false identities file for tax refunds,
and we have challenges in rooting that out
before it occurs.
So let's flip to slide 17.
With our working group with the PMAD members,
we've talked about and focused our discussion around the data
and technology, and essentially how do we move out of the
embryonic phase of -- that we're in right now of thinking about
leveraging the information age, more data, more analytics,
more forensics.
We're getting the sense in areas such as national security and in
areas such as law enforcement, that there is somewhat of a
revolution that's been going on for quite some time in how
information is being used to look for anomalies,
to understand what's going on in the broader sphere and to build
into risk management a much more smarter approach to how we can
dedicate resources to attack particular types of risks.
But in this area, we have not yet -- we're not anywhere near
where I think we need to be in terms of level
of sophistication.
So we need to take that journey that law enforcement and
national security has taken before us,
and we think pressure testing these ideas and these thoughts
with our corporate partners makes a lot of sense.
So we have both an agency-specific focus, and so,
for example, you'll hear from the Labor Department,
they've had a challenge they have that you (inaudible) here
from CMS who is tackling that issue for Medicare and Medicaid.
And then we want to try to tackle this
problem governmentwide.
And Neal Wolin from the Treasury Department is here to help talk
to us about a governmentwide forensic solution that we
currently have under development.
So with that, let me turn it over to Seth who is going to
give the unemployment insurance (inaudible).
Speaker: Thanks, Denny.
Good afternoon, everyone.
Let me start by introducing the actual experts on this subject.
Behind me is Gay Gilbert, the director of our office
for unemployment insurance.
And Jim Taylor who is the Labor Department CFO and a
former deputy IG.
So really quite knowledgeable in this area.
So I'm going to jump back and forth between slides 18 and 19.
UIPE is the joint state and federal program based
on federal law, but it's administered by the states
based on state laws that vary quite significantly.
So there are 53 systems using different state laws.
For example, with respect to eligibility,
they use a different process for operation,
they have different methods of delivery of checks.
We regulate the states' systems, monitor state administration to
ensure that they're in compliance with state law.
We oversee the federal UI trust funds,
and we give states that administer the funds technical
assistance to help them with their operations.
Now, we've been working quite aggressively over the last two
years with our state partners to try to get at improper payments.
And if you'll turn to slide 19, you'll see the latest data that
we have, which is from calendar year 2001.
The latest data show that we have been able to make some
progress in bringing the improper payment rate down.
The middle column is calendar year,
the preceding column is fiscal year,
so that's the latest in the middle.
So we've brought it down, but obviously we have a lot
more to do.
On slide 19, it shows you the principal causes of -- or all
the causes of the improper payment rate.
The principal causes, the largest causes and the ones
that we think we can influence are a 4, benefit year earnings,
which is a fancy way of saying people keep collecting UI even
though they've gone back to work.
Work search, same UI laws uniformly require that while
you're receiving UI you've engaged in active work search.
Some claimants fail to perform a report when they're engaged
in work search.
Separation errors, this is employers failing to tell us why
somebody has been separated, that is relevant to eligibility
under UI.
And employment service registration,
claimants just fail to register with their state's employment
service which is the principal method of providing the
employment services to unemployed and
dislocated workers.
For the 2011, IPI -- so those are the principal areas that
we're focusing on.
For the 2011 reporting period, and this is in the right corner,
bottom corner of slide 19, we estimate that about 26% of
all UI overpayments were due to fraud,
or about 3% of the total benefits paid.
As you can see, over two-thirds of fraud overpayments are due to
claimants continuing to collect after they've gone back to work.
So they are misrepresenting to us that they are unemployed
rather than back at work, rather than simply making a mistake.
So flipping back to slide 18, what are some of the challenges
that we face.
First is this is a decentralized program that we have very
limited tools to influence.
We're using the full toolbox that Congress has provided to
us, we're using policy guidance, we're putting performance
measures in place, technical assistance, shaming,
we put a website up that shows every single state's improper
payment rate broken out, we've also shown whether or not
they're doing the set of things we think they need to do to
bring their rate down.
We're funding incentives, and we're using the bully pulpit
all over the country now.
Another problem is information technology capacity.
Most states' IT systems in UI are quite antiquated.
The median age of a state UI IT system is 20 years old.
We have one that probably is more than 40 years old.
There are states that are still programming in cobalt.
Data sources to prevent -- to support prevention and detection
are limited.
Cross matching of databases is one of the most important things
that you can do to address this issue.
For example, the National Directory of New Hires helps
states to identify when a claimant has gotten
back to work.
The problem is, there's a five to six-week time lag in that
data, so that BYE problem, that people going back to work but
still collecting UI isn't really addressed by the MDMH as well as
we'd like it to be.
Also federal law prohibits states from simply acting on a
data cross match.
They have to verify it by some kind of personal contact under
federal law, that obviously means a tremendous resource
investment by the states to try to go after these problems.
So we're working now with three states to pilot the use
of financial data from banks to try to get the data much,
much more quickly.
And also states don't have expertise in the capacity for
data analytics and for predictive modeling.
I'll talk a little bit more about that when I talk about how
I think you can be helpful to us.
So we've been focused on the largest causes.
As I mentioned, there are four.
There are three that we're really focused on, BYE,
employment service registration, and separation.
We addressed BYE.
We've given money to states to engage in much more frequent
cross matching with the national directory of new hires to
identify when a claimant may have gotten back to work.
States are now, when they find out that somebody has gone back
to work, immediately notifying them, saying, hey,
we know you're back to work, don't collect any more
UI benefits.
And we'll also develop some messaging tools to
remind people.
Some people think legitimate -- well, not legitimately,
but mistakenly, that if you go back to work,
you can continue to collect UI until you get
your first paycheck.
That's not right.
We're reminding them with a messaging campaign nationally.
To address separation issues, we've worked with states to
develop a standardized IT application that's called SIDES
to enable very quick electronic communication between states and
employers on separation and the reason for separation.
And now we're turning to strategies that have been
focused on work search and fraud.
So let me quickly identify three areas,
I think these will match up with the list that Danny is going to
give you shortly, of three areas where I think that this group
could be most helpful to us.
The first is, to be blunt, we are not using advanced data
analytics for identifying trends or risks or patterns of behavior
prediction at all.
Second, if you have ideas about organizational structure,
we've gotten all of the states to get cross functional teams
together, we've supported them in doing that.
But you may have thoughts about what kind of team or what kind
of structure is effective in going after this problem.
And then third, communications and messaging.
We have the problem both of internal communications to our
state partners and to our own organization,
but also external to our potential customers.
Speaker: What -- a question, if I may.
What is the penalty to the individual,
what happens to the person who may have been overpaid in the
context of this where you discovered they started a job
and continued to get benefits?
Speaker: The money is taken back out of your -- correct me
if I'm wrong, Dave, the money is not clawed back,
it is taken out of your next set of unemployment benefits.
So if you're unemployed weeks 1 through 5,
week 5 is an improper payment, when you are unemployed again in
week 20 to week 25, they will reduce the amount
of your payment during that period.
Speaker: So there's no punitive aspect --
Speaker: To -- no, it's not -- if it's not fraud,
there's no punishment.
Speaker: It's whacky.
Speaker: And then the reason we be can't -- the reason we
can't solve that right away is that we don't have the
processing systems (inaudible).
Speaker: I think it's a priority question, Deb.
Speaker: That's correct.
We, first of all, would like (inaudible) so our primary way
to get them independence back is often through benefits or
(inaudible) agreements with the person to pay back the money.
Or other states use (inaudible) and garnish wages (inaudible).
Speaker: And the TOP -- should we
mention the TOP program?
Speaker: Right.
We now have the authority to offset (inaudible) the states
are beginning to implement that now.
Speaker: So we're now working with the states to get them
signed up for the Treasury Department's TOP program so that
way the money can come out of the federal tax returns rather
than coming out of future (inaudible)
Speaker: But it's dollar for dollar,
no penalty for having done it.
Speaker: Right.
Speaker: That's only for fraud.
Speaker: Only if it's fraud.
Speaker: We have (inaudible) the federal requirement of 25%
(inaudible), I think it's (inaudible) penalty for fraud.
And obviously (inaudible) more rigorous penalties than
any other law.
Speaker: Sorry, what was the number that is improperly paying in this
specific situation, I've gone back to work and I didn't --
Speaker: About 30% of -- our estimate is about 30%
of overpayments.
So (inaudible)
Speaker: So about 3% overall?
Speaker: 3% of the total is improper payments.
Speaker: What's that?
Speaker: So what's the number?
Speaker: The total unemployment insurance annually
right now is what?
Speaker: (inaudible) our overpayment or improper payment rate
is roughly 13 billion (inaudible).
Speaker: Right.
Speaker: So a hundred -- so (inaudible)
Speaker: They think it's --
Speaker: About a hundred billion-ish, so $3 billion.
Speaker: 3 billion, yeah, yeah, so --
Speaker: No, that's -- no, that's not right.
It's the -- it is a third -- it's a third of the total
overpayments, which is --
Speaker: It's 400 billion.
Speaker: Yes.
So now, if you have the ability the next time you go
on unemployment to hold it back, right,
and so that means you know, that means we have a (inaudible)
to know that this person has been overpaid, right?
Meaning if we could hold back in the future --
Speaker: We must know now.
Speaker: We must know now.
So the issue is really we don't have the authority to claw back
right away.
Speaker: We know in realtime or we know in retrospect?
Speaker: As soon as we're able to detect,
it's adjudicated and get them back so -- make a decision,
we can stop the (inaudible) at that point and then begin to
Speaker: But our knowledge is highly imperfect for the
universe of when this is occurring.
Speaker: Yeah, (inaudible).
Speaker: When we see it, we can do the offsets.
Well, part of this discussion is is we have blind spots
Speaker: The cost of a claw back,
where it's in the public or private sector,
would be I think probative, so in terms of how do we stop
the problem before it occurs.
Speaker: Yeah, right.
Speaker: And the other thing is we're not -- we're talking
about claw back from people that are uninsured,
so presumably there's no money to claw back.
So I just would question the wisdom of throwing money for --
claw backs are hard enough in the private sector (inaudible)
Speaker: Right.
Speaker: Well, they're getting paid, though.
At this point they're actually getting get paid
and just garnish the wages, but I agree with your point,
let's prevent it.
Speaker: I've never --
Speaker: (inaudible)
Speaker: Somebody -- the cross benefit,
I could be surprised it worked out (inaudible).
Speaker: Do you want me -- why don't we -- oh, go ahead.
Speaker: Sorry (inaudible).
Speaker: No, I was saying except many times by the time
you identify an improper payment,
they no longer have income.
Speaker: That's why --
Speaker: So you got to wait until they either go back to
work or they come back on unemployment or whatever
Speaker: That's right.
Speaker: (inaudible) does the state pay money as well as
the federal government?
Speaker: Yep.
Speaker: Are the state and the federal government aligned
in the goal of trying to reduce this, i.e.,
do they pay money, too.
Speaker: The money goes back into the UI trust fund,
so it's tabbed -- it will end up paying out additional -- it will
pay out benefits (inaudible).
Speaker: That (inaudible) overall structure between state
and federal on UI.
Speaker: Right.
Each state has its own trust fund,
which is overseen by the federal trust fund,
sort of aggregated to a federal trust fund,
the money goes back into the trust fund,
so we don't -- we have no incentive to -- we have no
disincentive to getting that money back,
the states have no disincentive to getting it back.
It's fair to ask whether or not they have a sufficient incent to
Speaker: That's what I meant (inaudible)
Speaker: To go out and get the money,
because the effect is somewhat attenuated,
so they get the money back, the money goes into the trust fund,
it gets paid out at some point in future benefits,
theoretically if you collected enough money,
it would reduce the tax rate for employers in your state by some
amount, or it would give you additional money to pay
out additional benefits to more unemployed people,
but it's several steps attenuated from
that policy result.
Speaker: So, Neal, why don't we shift to the government
buy-in solution.
Speaker: So let me first introduce my colleague,
Dick Gregg who is fiscal assistant secretary,
he's in charge of making about 85% of the payments that the
government makes, doing the lion share of the debt collection,
and also financing (inaudible) all of our notes and bills and
public debt auctions.
He supervises.
So we are trying, as Danny suggested,
to create a -- it's still in its (inaudible) setting it's fair to
say, a utility for the government at large that would
allow us to better capture payments that shouldn't be made
before they're made, both at the moment of eligible -- before the
moment of eligibility for programs or for qualifying folks
who do business with the government before payments are
actually issued, and then a capability that would allow us
post payment to do the kind of analytics that, you know,
every financial services company in the America does in the main,
both with respect to fraud and tax (inaudible) other weaknesses
in the system that are helping contribute to the enormous
amount of improper payments that Danny identified at the start.
Treasury is sort of the natural place because we are sort of the
core payments function of the government,
because we've done something relatively analogous on the debt
collection side over the last ten years to, I'd say,
reasonably good effect although still striving to
improve there as well.
So the basic idea, we're working with the Kansas
City fed who are, in fact, our contractors on this,
have some capacity and some IT that is useful to us,
are working on creating a portal, it exists now,
it's still I think without important aspects
of functionality, that allow agencies,
the Treasury and other agencies, again,
both at the moment of eligibility and at the moment of
payment on a continuous basis, that's the goal,
to look at a series of databases that the government has that
looked at -- and they're listed on this page, who has died,
who is ineligible to do business with the government either
because they've been debarred as procurement contractors or
because in the national security world they're subject to some
sanction or another by the U.S.
Government, or ineligible to receive payments for Medicare or
Medicaid, other federal health programs, et cetera.
And to really be able to do this in realtime,
have agencies send files, you know,
huge files of potential beneficiaries or contractors
or with respect to payments, payees,
and see who is not eligible.
And if the government already understands,
and some part of the government isn't eligible for a payment and
do that kind of core pretty straightforward matching
exercise that, again, is done, you know,
in your all's world every day, and that we just haven't had the
capacity to do.
We are working on the back end piece of this with respect to
the data analysis and the sort of post payment sense of things
that will help inform how we do the front end,
both with the Kansas City feds I mentioned,
but also with the Financial Crimes Enforcement Network,
which is a bureau of the Treasury that focuses in a range
of capacities on financial crime and on following flows of money,
mostly in the money laundering space,
but in other spaces as well, and have we think a lot of
expertise that can be brought to bear on this set of challenges.
The challenges are not insubstantial,
apart from this being early days and are really just trying
to ramp up on the IT and on the functionality on the
governments, all I think topics where your all's input could be
particularly useful.
We face a set of challenges that are maybe not uniquely,
you know, governmental, but I think exacerbated by, you know,
our particular circumstance.
One relates to this set of issues about privacy and
balancing information sharing, which at the end -- you know,
at the core of this is what this is about with privacy concerns,
we have a, you know, a set of statutory constraints there and
political constraints on top of those that are -- that are not
unsubstantial and working those through will be important.
So for example, in order for agencies to continuously monitor
the databases that we have available to us that, you know,
suggest names of payees who shouldn't be eligible for
payments, we at Treasury have to work through on an
agency-by-agency basis matching agreements,
actual data sharing agreements with each agency one by one.
So it's an arduous kind of task.
And in order to change that, you need a change to -- to statute,
that's I think unlikely to come any time soon.
There's another set of challenges I think that relate
to the basic tension between, you know,
constituencies and our own policy goals on when to make
payments on the one hand and taking extra care to not make
improper payments on the other, those are both important
objectives in getting that balance in the right place is a
very complicated thing.
And moreover, it's probably a different balancing act for
different programs and for different kinds of payments,
and so it's -- it's very, very textured.
Speaker: Do you think --
Speaker: I think the last thing that --
Speaker: Do you have a question?
Speaker: Sorry, sure.
Speaker: Do you need data matching agreements in
place before you do the --
Speaker: We do.
Speaker: -- matching service?
Speaker: We do.
So we have a few, but, you know, there are lots and lots of parts
of the government, and we need one with each one of them in
advance before we can actually do this continuous feed of
data back and forth.
Speaker: Is that the longest pole in the tent?
Speaker: I don't know, these are all pretty long poles.
I think the politics on privacy complicate it.
The issues around -- so there are lots of kinds of payments
that we make, the federal government in the aggregate,
Treasury included, where there's an overwhelming impetus for
policy reasons to make the payments, to sort of pay first,
ask questions later.
That's the basic sort of context in which we find ourselves.
And then so the question is how to recalibrate that balance with
respect to a circumstance in which, you know,
that may have gone too far and the level of improper
payments obviously --
Speaker: So I don't want -- I don't want to (inaudible)
but what caused the two or three agencies that gave you
agreements, the comfort to do so and overcome the privacy and
other process concerns?
Speaker: I think it's not so much comfort,
I think this has just been put online in April,
we're just early days, it's just a question of doing
the mechanics of getting that --
Speaker: Okay.
Speaker: -- worked through.
And my strong sense is that more will come and
reasonably quickly.
And moreover, the functionality of this,
of the system as it exists today,
the portals exist today is not -- none of you would find it
overly impressive, and as it gets more impressive and as we
roll out more capacity, it will bring I think more
people to want to take advantage of what it has.
Speaker: And how long do you estimate until you're where
you want to be with the match agreements, six months,
nine months, four months, a year?
Speaker: Well, no, it's pretty arduous.
I mean, I -- so for example, I think there is a possibility,
especially if Jeff and, you know, his colleagues, you know,
help us push forward with other agencies and say here's a
template, maybe there's a reason to deviate from a template,
but here's a basic template that we could expedite that process.
But left to its own devices, dealing with each, you know,
agency and in particular a set of independent agencies who are
not, you know, cabinet agencies, who have some measure of
independence from the President and from the -- and from the
Treasury is going to be a long arduous --
Speaker: How long?
Speaker: Could be years.
Could be years.
Speaker: What's a good scenario to where we could be at
sort of 80% of (inaudible).
Speaker: You know, I think -- you know,
I hate to hazard a guess, 18 months.
Speaker: So I -- I mean, I think Neal is right,
there's a lot of elbow grease to these privacy agreements,
but in running parallel to having what can be a painful
meeting, bringing in the agency's, all their lawyers and
working out the details, and I've sat in on a few of them.
Parallel to that, we're also working with some privacy legal
experts in the government to see if there is a framework,
kind of a generic solution that could -- almost like the GSA
schedules, get everyone on a similar train,
and we're trying to do that.
Speaker: Kind of at a baseline.
Speaker: We need a huge database of information that is
deeply relevant to this conversation that, you know,
as yet, we haven't tapped, and it's even -- it's a database
within Treasury, our tax data --
Speaker: Yeah.
Speaker: -- which obviously is sort of the third rail of
data privacy with respect to, you know,
government information.
And -- and, so you know, it puts them quite quick I
think and clear relief just just how tricky some of the
issues around this are.
Having said that -- excuse me?
Speaker: That's the most valuable data set by far.
Speaker: It's enormously valuable and it's incredibly
constrained for our use statutorily.
I mean, the detail with which we are managed with respect to what
we can do with tax information is -- is, you know,
I think substantially more than you imagine.
And so I think there's a bunch we can move forward pretty
quickly, we need help, and I think your insights,
your experience and, you know, those of others in the private
sector who, you know, can help us with things like, you know,
process issues, state integrity issues, you know,
just basic blocking and tackling that, you know,
is prevalent in the private sector,
but which we are struggling to, you know,
accelerate our efforts around would be enormously useful.
And then we'll continue to work through these thickets that have
a more political and statutory dimension.
Speaker: So there's a lot of different ways to take
this conversation.
On slide 21, basically taking a kind of a macro angle,
but we're -- I'm really happy to go into any direction.
Let me just talk you through what we've -- kind of our
overview from the macro standpoint is that when we take
a step back from this, we recognize and what we see
is state of the union here is like -- is very
embryonic or nonexisting use of technology to attack this
problem of cross government.
Neal described we have a governmentwide solution,
it's (inaudible), you know, Seth said we don't really have
that capacity at Labor.
Peter is here from CMS, and they're -- they've started out,
it but again, one question that we're raising is why is that and
how do we get to a better place.
This question, that's why I was joking earlier,
someone said earlier why can't we take what Dennis talked about
and apply it to paper clips.
And we had a similar discussion in some of our earlier
discussions that we call it the NASA effect,
we don't have to worry about NASA ending on the cutting edge
of technology, the reality of NASA's mission and the reality
of that organization, its culture, it just happens,
they are going to be at the cutting edge of technology on
any endeavor that they take, but when you look at less priority
functions like how are we looking at fraud and error in
government payments to individuals,
contractors and grantees, we don't have the incentives,
the longstanding culture, the infrastructure to do that.
And so one global question that we have is how in this
particular and any of the government do we position our
organization better to be at the cutting edge, not just, hey,
here's the latest technology, but also understanding what's
going on there, because Neal said earlier,
just about every finance company in the world is using
sophisticated stuff to find identity theft,
credit card companies, et cetera,
they are -- they have run out 100 yards ahead of us.
Speaker: But they've got clear incentive,
it's the -- I'm sorry.
It's the bottom line of the company,
and so credit card fraud used to be 1% in the '80s,
and if they had done nothing, it would be 10%,
but they kept managing it down.
And that's profit, bottom line profit.
So that's -- that's how you drive their motivation.
So the question is what's the equivalent --
Speaker: Well, see, that's why our -- our motivation is
much more complicated, and that's why the political tension
that I talked about, you know, people want payments to go out.
Speaker: Right.
Speaker: The same thing is --
Speaker: And so --
Speaker: Exactly the same problem.
Speaker: You know, the presumptions
in a sense are flipped.
Speaker: We talked earlier, I mean,
it comes down to exactly what Enrique was saying,
human nature, which is -- honestly if you're not going to
incent the behavior change that you want to have happen,
it's not a matter of getting the database in, right,
it really isn't.
Because it's just so -- so I guess my question is, you know,
people only change when they have to, right,
no one fixes the roof not when it's sunny,
so if you've identified how much the improper payments are,
you do have a mechanism that says we can cut your budget by X
or Y, because we know this -- this percent -- you can't
do that, you --
Speaker: Congress gets to do that.
Speaker: And you can't present that we've identified
this much and so, you know, how do you hold people --
Speaker: Well, you might, but Congress is going to say,
you know, we want these payments to go out, right,
and we want you to fix the improper payments thing because
that's, of course, waste, but -- but how you organize the one and
the other is not so clear.
So I understand the normal tools that you have to -- to penalize,
you know, P and L in effect, you know,
to put a constraint on it, I'm not saying there aren't things
in the direction (inaudible), I think there are plenty,
but there is this kind of core reality that the tools
are different.
Speaker: Well, what (inaudible), right,
so we've had -- we do stuff internally with improper
payments and whistle blower and everything like that,
with everything you save, you know,
what's your skin in the game on it?
Speaker: Well, let me --
Speaker: Right?
You can't do any of that?
Speaker: Well, in the SSNAP program, food stamps,
we actually were rewarding states that would bring down
their improper payment rate, and in the budget cutting
scenarios that we're in now, that's the first thing that the
appropriators cut out because it's not necessary.
So we don't have full control over some of these --
Speaker: Sounds like a great program,
you're on a great program, I like your program.
(inaudible) cut that program.
Speaker: I think (inaudible)
Speaker: How was that -- how was that working before
it was cut?
Speaker: It was working well.
It doesn't set -- it caused the stars to shine and be
models for other states, it provides an incentive.
And we also helped the people who are the worst in the
improper payment, too, we target some money to them to bring them
up to -- up to the (inaudible)
Speaker: That's (inaudible), that sounds like a great
program you have.
Speaker: Yeah, I mean, you guys, we started the PMAP on,
you know, how do you do pride
performance management, it's the exact same thing,
when you have a whole system built around rewarding the
status quo and the average performer,
the answer is is that, of course,
you're not going to get a structural shift.
So unless you can find your way to having skin in the game and
rewarding the top performers in a meaningful way, you know,
you can data mine all you want.
Speaker: I guess the question I had is when the -- when your
budget is reduced, is that amount of money reduced or is
that line item removed and you are prohibited from spending the
money on that line item?
Speaker: The (inaudible)?
Speaker: I'm sorry?
Speaker: The latter.
I mean, there's certain things get -- it depends what the
Speaker: Depends on whether they reduce the top line in the
agency, right, or whether they just reduce this element of it
and leave the top line alone.
And the Congress can do either, and they do both all the time.
Speaker: Yeah, I mean, my -- the point I was trying to
understand is what is simply a matter for you if we all gave
your many resources or whether it is a prohibited activity.
But let me suggest something here,
I guess I can ask a question first about a point of clarity.
Is the issue that you don't have the human and technological
resources to aggressively pursue the initiative outline here,
is it a skill and (inaudible) resource capability and
technical capability in these agencies?
Speaker: I think that's part of it.
Speaker: That's part of it.
Speaker: What percent of the problem would that address?
Speaker: A quarter.
Speaker: Quarter percent is like there's no incentive to it.
Speaker: Maybe there's a bunch of that.
I mean, so for example, if you -- if you make -- if you stop a
bunch of improper payments, and just take a benefits program,
the savings are not going to rebound to the benefit of that
agency, they're going to just go away.
So at an agency level --
Speaker: Well, they go to taxpayers.
Speaker: What I'm saying, they go in and they drop
to the general fund, to the basic general fisc.
But at the organizational level, the department of X,
Y or Z is not going to be an immediate beneficiary of that
virtuous behavior.
Speaker: So let me ask you a question.
I'm thinking about the conversation we just had where
the reason that people don't want to buy off a GSA schedule
is because of control, trust, they think they can do it
better, the question I have for you guys is there -- is there a
feeling out there that, you know, makes people angry,
people are committing fraud, they want to stop it, or is it,
it's hardly on my radar screen?
Because this feels like a different kind of set of
incentives than handing over your purchasing,
this feels like the way to motivate people is, you know,
there's crimes being committed here.
Speaker: Yeah, but -- (simultaneous talking)
Speaker: I think we really need to clarify that the
majority of, for instance, of the overpayments or proper
payments in SSA are not fraudulent is the complexity
of the program, also the due process --
Speaker: So people can be well intentioned and they are
doing this by mistake.
Speaker: So -- (simultaneous talking)
Speaker: Of the 115 billion, that's the point I was
going to make, the 115 billion of improper payments,
about what is fraud, percentage wise?
I know, but --
Speaker: It's in the 5%.
Speaker: That's what I thought.
Speaker: Let me make this -- you know this is a
strategic plan.
I've struggled with this, I've been at this for almost
a decade now, this improper payments issue.
At first, I had Carolyn's reaction.
This is not all fraud.
But then I started to feel like the notion of the importance of
(inaudible) is elevated, so I make a big deal, for example,
when a treasury IG report comes in and talks about identity
theft in IRS, I make a big deal about that because I'm trying,
as you said, galvanize energy and accountability that this is
at the foundation of why we are at government for stewardship
reasons and trying to create that incentive.
Because without those financial tools -- because going back to
the NASA effect, what's the incentive at NASA to use --
obviously safety incentives and lives,
so there's a safety component.
But also, there is other scientific exploration.
But it's short of financial.
It's not that NASA administrators get to keep a
cut if they do more technology.
So I've been trying to find what that nexus is.
And you mentioned --
Speaker: You're kind of on the side of the angels here,
if you're thinking of how to motivate people around it.
It's not like, hey, hand this over because there's another
group that can do it better.
You know, the question is how do you just get people to realize
that this is just pure and simple waste.
And I don't know if you have to give them a cut of the waste --
I'm not sure that's true.
It just seems like the common person --
Speaker: There's got be some skin in the game.
Let me ask you something.
You've been at this for a decade --
Speaker: I don't think that there has to be --
Speaker: Not financial.
It doesn't have to be financial when I say --
Speaker: It is the greater good.
I mean, that's why smart people like this are serving
government, right.
Carolyn Colvin: It's much more compact than that.
At Social Security we send out $720 billion a year.
Our Title II, which is the trust fund area, we only have
about 2% fraud.
What we are beginning to do with the SSI population,
which is a assessed program, and you're looking at resources
and assets, and you look at the population that we are serving,
we have to find tools that allow us to identify whether they have
access up front.
So we've been very successful with our partnership with, say,
the financial industry where we have the access to financial
institutions, and we are able to go out and very quickly ask,
you know, five (inaudible) right now in their area,
identify whether or not they have assets.
And then we can then look at that.
But we don't do that with the initial applications.
We don't have the ability or the resources to do it.
We do it later often.
And so they have already received benefits.
Then we learn that they have resources and we have
the challenge of going back.
What we need to do is get to a point where we have resources
where every time someone makes application we can automatically
go out and discern whether or not they have assets
or resources.
And then you during dealing with the population that has
many times, no permanent address, they move a lot,
their living arrangements change.
But every time any one of those things happen they are supposed
to report it to us.
We have 1500 data batches and we are very effective in
using those.
But those are not adequate, so I'm hoping that you can sort
of offer some other ideas or other tools that we might use.
We got to get a prevention, how to prevent it from going
out the door.
And we've had a number without out simplication proposals that
have gone to Congress and they have never moved.
But, to give you an example, if we want to move someone off
the rolls, and they appeal due process,
it could be months before a decision is reached.
We have to continue to pay them until that appeal is finished,
when we know that they are going to come off the rolls.
And they probably know it too.
And then, once they have a decision that's in our favor we
have to go back and try to collect.
Speaker: Neal (inaudible)--
Speaker: I totally agree with Elizabeth,
having -- set a structure and doing classic
performance, management.
Using those tools is a big thing.
I'd say there though, I think there's a constraint with
respect to the tools available.
I think in the main -- we are talking about people who are
administering this program that really do want to do
the right thing.
Now exceptions of course.
Speaker: That's been my sense.
Speaker: And are very focused on doing -- feel pride in how
they are administrating these things.
I think what they don't have, I think what we are finding as
we work through this, what you're hearing from Seth,
what you're hearing from Carolyn and so forth,
is they don't have tools.
Their IT, sort of -- their ability to do what they'd like
to do is -- inability to actually, you know,
figure out who is getting money that they ought not
to be getting.
And I think you know, my own -- Danny and Jeff,
is that you know the price here is well suited to help us figure
out how we can bring the set of tools that would bring big
advantage in this area.
And that we basically don't have.
Or very --
Speaker: Let me make one suggestion,
which is as you look at the specific types of tools you
need, there's a process that I use,
I don't know if it's applicable in this setting,
something that we use called cold sourcing,
where we basically identify a capability we did not have,
both in terms of human resources and skills.
We would find the vendors who had those capabilities.
And we would contract with that vendor for the express purpose
of building that capability in our organization.
So, we would bring them in, they would operate it,
they would help us recruit and train the staff necessary to
maintain the capability.
And then over a two or three year period,
their contract goes away, and we are left with the residual
capability that's been institutionalized and used.
So if you think about that in the context of the technology,
the tools that you need, because if you don't have the tools,
you don't have the capability, it's going to be hard to
invent one.
And what you also don't want to do is be permanently captive of
the vendor as opposed to a cold sourcing arrangement in where
the vendor is paid to do an essence of technology and
tool transferring --
Speaker: If I understand you correctly the (inaudible)
instead of hiring the consulting firm to come build you a tool,
you hire the credit card company who's already using a
particularly effective mechanism to --
Speaker: They know how to do this.
You don't know how.
And the objective of the assignment is to leave you both
with the capability of the hardware, the software,
and the human resources as part of your organization able to
really institutionalize this, build operation transfer.
Speaker: Say that again.
Speaker: Build operation transfer.
Speaker: And you don't want to build,
you want to implement and you want to institutionalize.
Implement means to institutionalize.
Speaker: So for us -- I think it's great -- the challenge
would be where the sort of parties with whom we might be
able to do that.
So for us treasury (inaudible) firms,
has a set of complexities.
It's (inaudible)-- (laughter) But absolutely.
Speaker: There are many software companies who would
be interested --
Speaker: Make sure you check first,
anybody you hire hasn't been debarred.
Speaker: You know for what it's worth,
we also have unbelievable legacy systems, Cobol (inaudible),
I think we have some of machine language,
I mean they are really old.
And we started revamping our IT going to the usual suspects to
figure this out.
And I woke up in the middle of the night in the sweats,
thinking so much has happening in the technology world,
are we just getting to the point where we are about to
throw this away.
So we actually went on a technology quest.
We went to Silicone Valley, we talked to VC's,
we talked to Start-up's,
we talked to usual suspects, like, you know,
Google and Apple.
And the whole thing is what is new under the sun.
Because I do think that particularly in data
warehousing, Cyber security, fraud, there's a lot going on.
And your legacy systems may be a good place for you to leap frog
ten more versions of this stuff in a way that isn't as painful
as some of the credit card companies had to go through.
Speaker: Let's do five minutes on what we need to do
between now and October.
I'm focusing on tools.
(inaudible) take this away, take through July through October --
let's use five minutes (low audio) -- (simultaneous talking)
Speaker: So have you had those meetings with the outside,
you know, IT experts, and you know --
Speaker: Yeah, we've had a bunch.
But again, you know, we tend to go to IT (inaudible).
So whatever -- (simultaneous talking) or American express.
So we've had some, but I think you know,
my pretty clear sense is we could benefit from
a whole lot more.
And I'll let Dick speak for himself.
But I think we can do plenty more of that.
And there's a lot we can learn.
Speaker: One of the -- let me reverse engineer.
I think by the fall where we want to be is in a place where,
where Seth and his team have a very effective plan for how they
are going to deploy a new solution for the organization.
I think Neal and his team can have their -- they have already
initial launch -- but their expansion and their critical
path going forward, pressure tested against a global review
that involves a lot of input from --
Speaker: It sounds like your challenge is multiple -- many
times more complex because you have to depend on the
state systems.
So Neal's challenge is pretty daunting to begin with,
but at least it's in the federal system.
So you have to deal with 50 state systems,
including people that are still using COBOL.
So, I don't -- I don't understand the respective
responsibilities of you versus the states and how you solve
through that problem.
Speaker: Right, the big problem that we have is that we
don't have the data.
So if the problem is one of the problems is data analyst and
data mining we don't have it, the State's have it.
But we have had success in other contexts,
actually UI as well bringing states together in
consortia, for example, trying to get over this incredible
technology mountain that some of the states are facing
bringing them together in consortia.
In funding the consortia, so that they can test ideas
or develop infrastructure is one way to deal -- it doesn't
get you all 53 jurisdictions involved,
but it allows you to test some propositions.
We've had some very preliminary conversations about that.
We are not going to get everybody to, you know, windows,
2010 business doing that.
But it's a way --
Speaker: Going back to the earlier discussion about
incentives, what is the State's financial incentive
to participate?
Because the payments are coming -- there's a disconnect
between who's paying and who's administering,
if I'm understanding this right.
Do they get a benefit for avoiding improper payments --
Speaker: To the extent they can save money,
it either allows them in theory to reduce taxes or pay
more benefits.
Because this is employers -- this is the money you all are
paying in your futa tax that is in some number of cases,
not all of our improper payments, but in some number,
those cases more people should get it.
So if you can keep that from happening it's more money either
so you don't have to raise taxes, you can reduce taxes,
you can pay more out in benefits.
Now that incentive as I said before is a little
bit extenuating.
But I think they really want to do the right thing,
we've given a lot of visibility into how each state is doing
with this website and by publicizing it fairly broadly.
And every state has responded enthusiastically,
particularly those that we see being
most at risk, the worst actors.
Speaker: I want to ask something about the book.
I have a problem jumping straight to tools, because,
I think what you need -- I don't even know what architecture,
what governance, what you want to do.
So every time I've always had to clean up a mess is because
someone bought a new tool, or partnered with a co-source
and bought a new tool.
What is the end game?
What is the end vision?
So spend your time up front thinking what is the -- what
does the architecture need to look like?
What does the governance need to look like?
The tools will then come.
I have seen so many failures of going after the sexy new tool,
unless you have that end game in mind -- I've written off more
tools that I can count because the strategy hadn't been there,
the structure, the governance, the decision rights
hadn't been there.
I would encourage you -- I'm not -- I have no -- a devoid,
a censure, I don't know why you're going to JP Morgan or
to the banks.
You need to figure out I would think first and foremost,
what is the structure and the wiring that we want,
and then go to the tools.
I get very nervous when I think about let's go talk to
this and that.
Speaker: So just to add to that.
I mean, I'm actually further upstream than that.
Is this one that we should think about rescoping the problem?
Speaker: I agree.
Speaker: Like before we go into it's analytics,
it's collaboration, it's organization, it's design,
it's this tool, it's the data matching agreements, I like it,
but I'm not even sure what problem we are trying to solve.
I'm aware of it esoterically, high level,
but should we rescope and say, should we go after Medicare,
Medicaid, earned income tax credit,
unemployment or much like (inaudible) on the other one
where you said let's go for the common denominator,
the baseline, hotel, transportation (inaudible)
is there a baselining, I don't know what that is,
on a category called improper payments,
and it's not 115 million, maybe I'm making it up, it's 40 or 50,
it's a subset that you don't have the interdependencies and
the lack of control you're describing.
Maybe it's a smaller impact area around improper payments.
So I would think about rescoping,
and then we could talk about -- it's really,
you're talking about technology, process,
and I think the organization --
Speaker: Don't you think we need to know the structure to
attack it first --
Speaker: Can I just add something to this?
Speaker: One of the questions I raised when I was getting
briefed about this is I'm not clear myself on how we come up
with these numbers of what was improper payment.
Whether we do it retroactively, how we know you know,
and how we count that.
Because you don't know what you don't know.
So, one of the things that I would find helpful, at least,
maybe you guys have done this is what is that universe and what
are the different ones that we can attack,
and what-- now this is not necessarily relevant to your
issue, Seth, within labor, because the 400 million may
be very impactful for you.
But from a government wide point of view,
if we looked at the big number this is another case of not
letting the perfect to be the enemy, the good,
going after the low hanging fruit.
It may be that the tools necessary to go after the big
numbers are easier to come by and so it would be helpful when
we scope the problem to understand what are the big
buckets, how do we go after them,
what are the different kind of tools,
before we try to invent a machine to go after everything.
One of the baseline pieces of data that I was wondering about
is when we say there's X dollars of improper payments,
how do we know that, what is it, how do we monitor?
Do we go back in time when we recover payments?
How do we sort it?
What is the nature of this problem?
Speaker: Page 16 has the breakdown at a high level.
So that's a fair question you just asked about the
(inaudible) --
Speaker: (inaudible) background in the world on how
we get those numbers.
Speaker: There's a set of numbers on page 16.
What we did was we then went to Seth,
on unemployment insurance and then he broke down on page 19 --
I agree with what both said, but if you look at 19,
it's got the root cause of where these payments are going.
Speaker: But what I'm suggesting is let's
go to strategic source.
We said 538 billion, 150 billion is what -- it's
a subset of that number.
You have the 115, we believe the 115.
You've given the five areas --
Speaker: Big number.
Speaker: We believe it.
Speaker: -- is all 115 from a capacity standpoint and
interdependency standpoint, a complexity standpoint,
is that all resonable to go after, or is it a subset of 115?
It's 80, it's 60, it's 40.
I think we need that number first.
And then when you get that number, then we,
using the strategic sourcing as an analogy say,
what are kind of the baseline things?
Their data service matching agreements?
Maybe they are what they are.
And let's go after that and start to -- the low hanging
fruit analogy applied to the proper payments.
That's all I'm suggesting.
Speaker: Let me -- then we need to wrap -- let me wrap this
with the following thought because I want to go back to
Jeff's question that he asked -- (inaudible) I'll tell you,
again, been at this for a decade.
What do I think we need more than anything?
And I could come in, I might not be right,
but I keep coming back do this question,
our organization is in line to attack the problem.
So let's look at one example if someone,
he said -- he went over it quickly,
someone came to us with this idea,
they said you know when corporations pay direct deposit
to their employees to banks, banks know that when they are
getting it in that it's a payroll deposit.
They could tell that to you and you could know that a person is
back at work.
You don't have to rely on the W-2 or the W-3 forms which
you're having trouble with.
You can actually get that information direct from banks.
So as a result, now we are working with the banks to see if
this information (inaudible) that is an opportunity.
And the issue that I have from the Labor Department is how do
they -- that came to us by luck, by happenstance.
It didn't generate out of the organization.
I want to make sure that within the Labor Department there's an
organizational approach that's looking for these solutions,
understanding what their portfolio of errors are and
where the highest part of the buy in is.
Where I think we need help right now in the government is how do
we go from zero to 60 in building that organization
around this particular problem, because you're right,
master card, these other companies are doing well,
but they started at 16 miles per hour.
Speaker: I don't think we are quite as far along as to what we
do in the next few months here (inaudible) -- (low audio) I
agree with (inaudible) that we need to disaggregate this and
get it down to the early wins, the low hanging fruit.
I think when we do that Danny, it will
enable us to on surface things, like your bank relationship
piece you just did on payroll.
I think do some of this aggregating prioritization
and then try to drive it off of that.
I think we are going to get a phone call,
at least from the subcommittee to do another round of that.
Let's break now.
I want to do quick updates on our 2011 initiative IT,
SES (inaudible) thank you.
Speaker: Thank you.
(simultaneous talking)
Speaker: As of right now we should probably leave
here in 15.
So we'll run these two updates as 6, 7 minute updates.
Speaker: We are supposed to be there in 20 minutes?
Speaker: (inaudible)
Speaker: It's that big white.
Speaker: Steve, is John coming too?
Why don't we start with you.
We are going to try to do -- the point of this session is we do
not want to have a set of 2011 initiatives that happened in
2011 and ended in 2011.
You guys got us off to a good start.
I'm saying in 2011 on SES and IT you got us started in a good
direction which is early win.
The whole point is to hard wire, institutional it.
So at each meeting we are going to come back to you and give you
a quick update in IT to see where you are.
Why don't we start with IT.
You've got 15 minutes at most between the two of you.
So why don't you each run 6 or 7 minutes.
Speaker: I'm going to take about 5, if I can.
So thank you all for hearing this update.
I know the last time we sat down and talked about vendor managed
organizations (inaudible).
You heard from the pilot agencies who are
doing this work.
And, I thought today I would just give you a quick update.
Slide 23, spend 30 seconds on.
On vendor management, and you heard a lot last
time from the agencies that are doing this work,
the key milestones we could sense the last time we saw each
other is, one is the establishment of maturity
models across government, so we are now assessing working
with Joe Jordan, who I think you heard from this morning,
who runs federal procurement policy.
The dovetail strategic sourcing with vendor management to think
about how do we create centers of excellence that know areas of
technology and then how do you apply that with relationships
with the vendors.
So this maturity model has been the first step.
And the second is, setting goals and aligning those goals across
those agencies.
And I thought I'd -- the great update for you is that we've,
since establishing this we've hit a milestone of saving about
$40 million in the last six months of renegotiating
contracts to this new model, setting goals.
The veteran's administration has a group they call the ruthless
reduction task force.
Speaker: The 40 million --
Speaker: Just the six months.
Just through this.
Speaker: Six months --
Speaker: Wow.
Speaker: So patent and trademark office,
general services administration, heard from Dan,
are also doing this and Treasury is probably the
farthest along as well.
So a group that's doing veteran management.
As far as the next steps on this, it's all scale.
Taking and scaling across government.
I'm excited that Joe Jordan is now in seats.
I think we can take that forward.
Slide number 24, this is probably the most exciting area,
focus for me, and one where I'm very hands on,
is investment review boards and portfolio management, NIT.
Last (inaudible) meeting, if you remember,
Jeff and I launched this initiative called portfolio
staff, which is a process, data driven process that ends up
being a face-to-face assessment, working with agencies ongoing
through their IT portfolio, and assessing where they are,
relative to the agency, although what is amazing that is in many
cases hasn't been done, in these organizations.
And what's very apparent is the amount of duplication across
agencies, the culture of sort of fiefdoms,
wrapping their arms around work that is happening.
And lot of opportunity to break that down.
We kicked portfolio stats off this week.
Over the last month or so agencies have been gathering
data for us and kind of building the case of evidence of the
things from the farthest corners of their other agencies and the
face-to-face meetings started this week.
I thought I'd give you a quick example.
So I'm doing six of these this week, with different agencies.
I'm meeting with every single cabinet level agencies and
others to do really two things.
One is to run through the rationalization of
their portfolio.
And second is teach them how to run an investment review board.
So we use this meeting bringing the deputy secretary,
the chief financial officer, the chief acquisition officer,
the chief information officer, the budget side of OMB and
myself in the room to really kind of show them what an
investment review board really needs to be.
So we start and end every meeting with a mission of the
agency, the objectives.
We don't start the tactic, we start the mission,
talk about what they are trying to accomplish and then work our
way down to how we are doing that,
rationalizing the portfolio.
So as an example, the date that's come in, six agencies,
I won't name them, but they represent about 6.2 billion of
federal IT spending which on the civilian side is about 16% of
our portfolio the whole portfolio with DOD is about 80
billion cash out lay every year.
So this small snapshot of 6, 6.2 billion,
and as far as the opportunities that we see in there,
we have self reported in those six agencies about $3,400
per employee on main frames and servers.
If we just bring that down to the government average and
industry average of about 2,000, we'd save $376 million,
one time.
This group spends about 9% of their IT budgets on
telecom systems.
If we bring that down to an average of about 6% that's
$187 million, $252 per employee
on identity management.
We bring that down to 195 which is our average.
That's $15 million.
Those three stats right there is a half a billion dollars.
And it's six agencies across a body of 24, 16%.
So that's one-fifth, half a billion dollars in one-fifth of
the government agencies waiting for us out there if we want to
seize on that.
So it's not -- these aren't hard and fast.
I'm not setting these -- they are certainly achievable goals,
I don't want to over promise, under deliver.
But it's really kind of shows us the writing on the envelope from
which we can reach savings, portfolio's,
rationalization side and more importantly is building
a culture of both looking at the bottom of the IT list,
cutting it in favor of putting it on to the cap side of the
equation and it's still in culture of getting the key
players in the room together to rationalize this stuff together.
And so, the -- what we are going to see, I am of course meeting,
have all of these meetings set up.
They are set up through the beginning of August.
End of August, agencies (inaudible) final plan on the
rationalization of their portfolios,
with an implementation timeframe.
The key point of that is just we are going to drive really hard
to get agencies to be very aggressive in these areas,
to run this consolidation and get through this.
We are doing a lot on computing, investment vehicles,
and acquisition vehicles, make it much easier for them to
do this rationalization.
So I think we have the right elements of the one-two punch to
get this stuff done.
To close, again, thanking you for all of work.
Sitting down with many of your agencies.
I just sat with the Department of Education yesterday.
And they talked about their time with Adobe.
And they now have a model on measuring there IT investments.
It's very unique in government, not unique in the private sector
and certainly was a model from our time there.
And we, you know, with our imperative from the President to
really innovate with less, I think this presents a huge
opportunity for us to take the saving side of the equation and
pour it into the innovative side.
And I think there's good things happening.
Speaker: John.
Speaker: Thank you.
Page 26 and 27.
I will be very brief.
I want to thank everybody for helping us on this,
especially Seth Holden and Cummings
in terms of executive development and
training programs.
They are up and running now.
We have done two of them.
And I want to thank Gayle who's been one of our first speakers,
and Jeff and Greg and Sam, who all of you have helped us by
coming and helping to speak at these.
You'll see at the bottom there some upcoming training events
where we'll have a significant number of -- we'll probably be
reaching over 1,000 at these three events.
So it will be a real great opportunity.
If your schedules allow.
You can see the dates.
So if any of you are available, we will very graciously take you
up on this, and it will be a huge help to us.
The other thing that's also been launched,
that program we've been doing with the federal executive
institute and the on-board approach with new executives,
but also an existing training program for all of the other
on-board executives already.
And we've called that leading edge.
It has four components, thanks to your all's help and you
advised us with that, sort of having a good speaker training
series, having an executive network that was sort of
confidential, that they could share information and questions
among each other, coaching component to it and then a
service project component that would be multiagency,
trying to get us at that, you know, working across silos,
working across departments with the original intent of the
senior executive service.
So, first session was held, very great attendance.
We did it in the largest auditorium we had in town,
full house.
And so, we'll be keeping going with that.
On the SES appraisal system, again, thanks to you guys,
and loaning us so much of the work that you had
done on that.
We now have that up and running at the VA at Labor,
and we are five, OPM, five months into it.
It's looking good, and you know, now the trick is getting each
and every agency to come on board with this.
Speaker: 18 --
Speaker: Yep.
We will have over 80% done by 2014 is the goal now, but,
I'd -- I've challenged my people,
what do we need to do to make that 100 and do it in
the same timeframe?
So we'll be back to you on that.
I hope to get the gap closed between the 80 and the 100 by
the next time we get together.
Speaker: Now my notes for the next session say 11 are online
already and the rest in two years, is that true?
Speaker: Yep.
Speaker: Eighteen are fully committed, 11 are online,
and John said we'll have 100% by (inaudible) --
Speaker: I don't see why we can't.
They are saying, well, it's up to the agency -- you know,
between Jeff and I, we ought to be able to get,
one real quick question.
Employee viewpoint surveys, we do surveys of our employees,
but we do it as an in-house, big cumbersome, 89 questions --
Speaker: Big satisfaction.
Speaker: Only have about -- less than sort of
40 to 50% uptake.
We are looking right now, how we can do this better, smarter.
And I know a lot -- I know you all must be doing this,
and I'm wondering if you could help us with some advice on
employee viewpoint survey.
It would be really great.
Speaker: So we use a thing to measure customer -- (inaudible)
we actually turned that into an internal employee survey.
And so ultimately you could actually get so much data out of
a much smaller set of questions.
And (inaudible) one question you really --
would you recommend it?
And that really gives you a sense of what people
really feel about the organization or agency.
If you want we'll put you in touch with the person who runs
it for us.
Speaker: You know, there's a lot of discussion,
sort of at the 12 questions, meta analysis approach,
I don't want to name any companies,
but is anybody -- is that one --
Speaker: I used it in two companies.
And I loved it.
I used it in two companies and we really loved it.
It's a lot more expensive than this approach,
but you get 90% participation, like this.
Because it's less than 10 minutes to fill it out.
Speaker: We get 80, 90% every time.
Speaker: That's what I feel like we --
Speaker: We used a different type of approach,
but the main thing we got out of it was (inaudible) but also at
the unit level how important (inaudible) culture of the unit.
So that was a very helpful in management performance.
In fact over time, (low audio)
Speaker: Boy, that would be fantastic.
It maybe through Scott we could send out an email -- if you guys
could give us a contact.
Speaker: Also we have to email to everyone,
gather some thoughts -- (inaudible) thanks guys.